THE PROCESSES OF CARE AFTER COLORECTAL CANCER SURGERY … · Table A.1 OHIP fee codes used to...

THE PROCESSES OF CARE AFTER COLORECTAL CANCER SURGERY IN ONTARIO

By

Jensen Tan

A thesis submitted in conformity with the requirements

for the degree of Master of Science (Clinical Epidemiology)

Graduate Department of Health Policy, Management and Evaluation

University of Toronto

©Copyright by Jensen Tan 2008

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Abstract

THE PROCESSES OF CARE AFTER COLORECTAL CANCER SURGERY IN ONTARIO

Jensen Tan

Master of Science 2008

Graduate Department of Health Policy, Management and Evaluation

University of Toronto

Introduction: Colorectal cancer (CRC) is common in Ontario. This study described the processes of care

following CRC resection, and identified CRC relapse from administrative data.

Methods: CRC patients aged 18-80 from 1996-2001 with a colorectal resection were identified from the

Ontario Cancer Registry. Linked discharge abstracts and physician billings were examined for physician

visits, body imaging and endoscopy over the 5 year follow-up period. Administrative codes suggesting

disease relapse were compared with patient charts.

Results: Overall, 12,804 patients were identified and 8,804 had no evidence of relapse. Most (96.2%)

patients had general practitioner follow-up, while 49.3% had medical oncology and 80.4% had general

surgery follow-up. Greater than 90% of patients received endoscopy, while only 68.7% of patients

received body imaging. Detecting disease relapse was 87.5% sensitive and 93.0% specific.

Conclusions: There is potential for improving post-resectional follow-up in CRC patients. It is possible

to detect relapse through administrative databases.

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Acknowledgments

First I would like to thank Vivian for her support during my research time and Alyssa for being the

perfect child. Sincere thanks to my committee members for the time they put into my entire journey:

Alex Kiss for his statistical expertise and insight; Steve Gallinger for his content knowledge; Nancy

Baxter for her methodologic expertise and attention to detail; David Hodgson for his guidance and

support; and last but not least Calvin Law for his mentorship, friendship and building my confidence. To

my colleagues for their support and constructive criticisms – Nick Daneman, Girish Kulkarni, Laura

Rosella, Anand Govindarajan, Karen Devon and Nicole Look Hong. Finally, I acknowledge my PS3 and

Guitar Hero 3 for maintaining my dexterity while away from the clinical stream.

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Table of Contents

List of Tables vi

List of Figures viii

List of Appendices ix

Introduction 1

Colorectal cancer epidemiology 1

Natural history and management of colorectal cancer 1

Colorectal cancer relapse and management 5

Post-resectional surveillance for colorectal cancer 9

Variation in care after colorectal cancer resection 13

Population based studies on CRC relapse and management 14

Rationale 16

Objectives 17

Methods 18

Data sources 18

Selection Criteria 20

Demographic and Patient related variables 22

Definition of high risk for recurrence 22

Definition of disease relapse 22

Descriptive statistics 23

Preliminary analyses 24

Objective #1: Visits and tests 25

Objective#2: Treatment for disease relapse 26

Secondary Objective: Comparison with primary chart reviewed cohort 28

Data Analysis 29

Results 30

Inception cohort 30

Exclusions 30

Baseline characteristics 31

Preliminary Analyses 36

Objective #1: Visits and tests 37

Objective #2: Treatment for relapse 47

Secondary Objective: Comparison with primary chart reviewed cohort 55

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Discussion 58

Cohort formation 58

Visits and tests – group #1 59

Endoscopic follow-up 61

Body imaging follow-up 62

Visits and tests – group #2 64

CRC relapse and treatment 64

Secondary objective: Comparison with chart reviewed cohort 69

Limitations 71

Summary and future directions 74

Appendix 75

References 80

vi

List of Tables

Table A. Tumor-Node-Metastasis definitions, AJCC 6th ed.

Table B. Tumor-Node-Metastasis (TNM) Staging for Colorectal Cancer, AJCC 6th ed.

Table C. Summary of eight randomized trials comparing surveillance strategies after CRC resection.

Table 1: Types of CRC by ICD9 diagnosis code

Table 2: Number of patients meeting each exclusion criteria

Table 3: Pair-wise summary of first year exclusion criteria

Table 4: Excluded patients – Direct age-sex standardization to Ontario population 1996

Table 5: Baseline characteristics of excluded cohort

Table 6: Characteristics of study cohort, eligible for postoperative surveillance

Table 7: Total visits and tests over follow-up years 2-5 in patients alive at 5 years without evidence of

disease relapse

Table 8: Mean number of MD visits or tests per 6 months of follow-up

Table 9: Model #1. Univariate and multivariable analysis for having at least one endoscopic examination

in follow-up years 1-5, among patients alive and no evidence of relapse at 5 years, who did not receive a

total colectomy

Table 10: Model #2. Univariate and multivariable analysis for having at least one body imaging modality

in follow-up years 2-5, among patients alive and no evidence of relapse at 5 years, stratified by high and

low risk primary

Table 11: Relapse based on site and high/low risk status of primary, by year of relapse

Table 12: Relapse rates and treatments for relapse, by income quintiles

Table 13: Relapse rates and treatments for relapse, by LHIN of residence

Table 14: LHIN of institution performing liver and lung resections

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Table 15. Model #3. Univariate and multivariable analysis for receiving surgical (lung or liver) resection

for CRC relapse, among patients who had evidence of disease relapse in follow-up period

Table 16: 2x2 Frequency table for eligibility for follow-up using administrative data compared to the

reference standard of primary chart review

Table 17: 2x2 Frequency table for relapse detection using administrative data compared to the reference

standard of primary chart review

Table 18: Location of relapse and surgery for false negatives (relapsed by chart review, but not detected

in administrative data)

Table 19: 2x2 Frequency table for detection of relapse over all follow-up years 1-5 using administrative

data, compared to the reference standard of primary chart review

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List of Figures

Figure 1.Algorithm for classification of disease relapse

Figure 2. Schematic timeline representing censoring period for measuring test and MD visit frequency in

relapsed patients

Figure 3. Number of medical oncology follow-up visits over follow-up years 2-5 for low and high risk

CRC patients, among those patients with no evidence of relapse

Figure 4. Number of general surgeon follow-up visits over follow-up years 2-5 for low/high risk colon

and rectal patients, among those patients with no evidence of relapse

Figure 5. Number of endoscopy tests in follow-up years 1-5 among patients with no evidence of relapse,

who did not receive a total colectomy.

Figure 6. Number of body imaging tests in follow-up years 2-5 for patient s with no evidence of relapse

Figure 7. Sensitivity analysis: Forest plot of odds ratios and 95% confidence intervals of body imaging

frequency, depending on censoring interval prior to first evidence of relapse

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List of Appendices

Table A.1 OHIP fee codes used to identify colorectal resectional surgery

Table A.2 CIHI procedure codes for colorectal resectional surgery

Table A.3 ICD-9 codes for secondary disease

Table A.4 Surgery and biopsy codes for lung and liver, OHIP claims and CIHI procedure codes

Table A.5 Chemotherapy codes, OHIP claims

Table A.6 Physician consultation codes, OHIP claims

Table A.7 Imaging and endoscopic modalities, OHIP claims

1

Introduction

Colorectal Cancer Epidemiology

Colorectal cancer (CRC) represents the second highest cancer related cause of mortality in Canada (1). In

a report from the National Cancer Institute of Canada (1), it is estimated that for the year 2007, there were

approximately 20,800 new cases diagnosed and 8,700 estimated deaths. In Ontario alone, the age

standardized incidence rate for CRC is among the highest in the world (2); with 60 cases per 100,000 for

men and 41 cases per 100,000 for women (1).

The incidence of CRC has been observed to increase with age, with the highest incidence among the 70-

79 age group (1). The anatomic distribution also appears to change with increasing age. As age

advances, proximal cancers increase in incidence relative to that of distal (rectal) cancers. However, the

cause of shift is not known.

A statistically significant reduction of the overall mortality rate from CRC patients in the population of

Ontario has been observed (3). For males the CRC mortality rate decreased by 1.3% and for females by

1.7% over 1992 to 2002. This decrease in mortality rate is thought to be due to improved awareness in

screening, improvements in treatment (particularly with the introduction of newer chemotherapy agents),

and increased attention to quality indicators in surgery such as lymph node retrieval. These health

services delivered to a patient are known as processes of care (4), which may in turn affect the health

status of patients, or outcomes (4). In addition to improving patient outcomes by conferring the

appropriate processes of care for the treatment of the primary tumour, there is also a potential for

improvement in outcomes by optimizing processes of care after treatment of the primary tumour.

Processes of care following CRC surgery can include modalities such as physician visits, and performing

surveillance tests such as body imaging to detect disease relapse. To assess the processes of care after

CRC surgery, the management and various available treatments for CRC must first be understood.

Natural history and management of colorectal cancer

Histologically, the vast majority (99%) of CRC are adenocarcinomas. Adenocarcinoma of the colon and

rectum originate from benign, adenomatous polyps (5) (although not all adenomatous polyps will develop

into cancer). This polyp to carcinoma sequence has been well described, and has become the recognized

process of development for most carcinomas. Colonic polyps may be discovered during endoscopy, and

are treated by local excision. Sessile, or flat, polyps occasionally are problematic for endoscopic removal,

and a segmental colectomy is required to fully excise the lesion. When left untreated or undetected, the

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adenoma-carcinoma sequence takes approximately ten years. Hereditary forms of CRC exist where

patients may present in their 20s, but the vast majority of carcinomas are sporadic, where patients present

in the 6th decade of life.

The gold standard for colonic evaluation is colonoscopy. This allows for biopsy and histological

diagnosis of CRC, in addition to completely surveying the entire colon for any synchronous polyps or

primary carcinomas. However, in patients that present with obstructing lesions, complete colonic

assessment is not possible, and therefore complete colonoscopy is recommended following surgical

resection of the primary tumour.

Surgical resection

The primary curative modality for colorectal cancer is surgical resection. The surgical procedure of

choice is dependent on the location of the primary tumor, the presence of other polyps or primary

tumours, and whether or not it is considered safe to restore bowel continuity. Commonly, proximal

(right-sided) and transverse colon tumours are resected with a right hemicolectomy, while left sided

tumors and sigmoid tumors receive a left hemicolectomy or sigmoidectomy, respectively. Proximal rectal

tumors may be treated with a low-anterior resection along with a sphincter preserving reconstruction,

while most distal rectal tumors are treated with an abdominoperineal resection with a permanent end-

colostomy. Important surgical considerations for resection are the establishment of clear resection

margins, to ensure no microscopic traces of the primary tumour are left, and the adequate sampling of

lymph nodes. As lymph nodes are typically the first tissues to be involved in the development of

metastatic disease, adequate lymph node sampling allows for proper staging of the carcinoma.

Staging

Staging of CRC is important for several reasons. The stage of the tumour allows prognostication of the

patient, as higher (or more advanced) stage is associated with a higher risk of disease relapse, thus

affecting patient survival. Staging of the primary tumour also helps direct subsequent therapy, as patients

with higher stages are recommended to have adjuvant chemotherapy to reduce the risk of disease relapse.

Table A and B summarizes the American Joint Committee on Cancer 6th edition tumor-node-metastasis

(TNM) staging of colon cancer (6). This common staging system is based on the depth of invasion of the

bowel wall, extent of regional lymph node involvement, and the presence of distant metastatic disease.

With increasing stage of disease, the 5 year overall survival decreases from greater than 90% to less than

10% (7).

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Table A. Tumor-Node-Metastasis definitions, AJCC 6th ed.

Primary Tumor (T)

TX Primary tumor cannot be assessed

Tis Carcinoma in situ

T1 Tumor invades submucosa T2 Tumor invades muscularis propria

T3 Tumor penetrates muscularis propria and invades

subserosa T4 Tumor directly invades other organs or structures or

perforates visceral peritoneum

Nodal status (N) NX Regional lymph nodes cannot be assessed

N0 No metastases in regional lymph nodes

N1 Metastases in one to three regional lymph nodes

N2 Metastases in four or more regional lymph nodes Distant Metastases (M)

MX Presence or absence of distant metastases cannot be

determined M0 No distant metastases detected

M1 Distant metastases detected AJCC, American Joint Committee on Cancer

* Adapted from Greene et al. (6)

Table B. Tumor-Node-Metastasis (TNM) Staging for Colorectal Cancer, AJCC 6th ed.

Stage TNM Classification Five year overall survival (%) I T1-2, N0, M0 >90

IIa

IIb

T3, N0, M0

T4, N0, M0

60-85

IIIa

IIIb

IIIc

T1-2, N1, M0

T3-4, N1, M0

T (any), N2, M0

25-65

IV T (any), N(any), M1 5-7 AJCC, American Joint Committee on Cancer

* Adapted from Greene et al. (6)

Chemotherapy

An important component in the treatment of colorectal cancer is chemotherapy. Due to the risk of

developing disease relapse in stage III cancer, current guidelines (8) recommend adjuvant chemotherapy

in this setting to improve survival. The foundation of adjuvant chemotherapy agents is flurouracil (5FU).

The benefit of 5FU was demonstrated in the 1989 North Central Cancer Treatment Group (NCCTG) trial

(9) and 1990 Eastern Cooperative Oncology Group (ECOG) Trial, where significant reductions in

recurrence and mortality was observed with administration of 5FU based chemotherapy. Therefore in

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1990, National Cancer Institute consensus guidelines recommended, as the standard of care, 5FU based

adjuvant chemotherapy for all patients with resected stage III colon or rectal cancer (10).

With regards to chemotherapy for stage II colon cancer, the evidence remains controversial (11). Though

all stage II patients are “node negative”, there is a range of local tumor characteristics (from little bowel

wall infiltration to extensive tumors with extramural spread), and differences in adequacy of lymph node

assessment and accuracy of nodal staging (12) that may render a patient at higher risk of disease relapse.

One further consideration is that although survival may be statistically improved with the administration

of adjuvant chemotherapy, the clinical or absolute improvement may be minimal because of the overall

lower risk of recurrence compared to stage III disease. Therefore the benefit of adjuvant therapy in this

setting may not exceed the potential harms of therapy such as toxicity.

In light of this, the Cancer Care Ontario guidelines (8) recommend 5FU-leucovorin for stage III colon

cancer, once a day for 5 days, repeating every 28 days, for a usual total of 6 cycles. In total, this amounts

to 30 doses of chemotherapy over approximately 6 months. In addition, initiation of chemotherapy is to

begin within 5 weeks of resection of the primary tumour. Adjuvant chemotherapy is currently not

recommended routinely for patients with stage II colon cancer, although it is acknowledged that it should

be considered for patients with stage II disease who have high risk features.

Considerations for rectal cancer

Due to the anatomic location of rectal lesions, lack of a mesentery, and proximity to other structures such

as the bladder, uterus, prostate and sacrum, rectal cancers have a much higher rate of locoregional

recurrence than colonic primaries. Preoperatively, the location of the lesion must be precisely defined in

relationship with the anal sphincters, as well as the extent of the penetration into the bowel wall and

adjacent lymph nodes in the perirectal fat. Therefore, with the goals of downstaging an advanced tumor

to increase resectability, and reducing local recurrence rates, preoperative radiation therapy has gained an

important role in rectal cancer. The major trial that first suggested the potential for preoperative

radiotherapy was the Swedish rectal cancer trial in 1997(13), which was followed in 2004 with the

definitive German Rectal Cancer Study Group trial (14).

There is an important difference to note in the recommendations for adjuvant chemotherapy between

colon and rectal cancer. In contrast to colon cancer, where all stage III and some stage II cancers are

recommended adjuvant chemotherapy, all stage II and stage III rectal cancers are recommended adjuvant

chemotherapy (10, 15). This is due to the aforementioned anatomic considerations and resultant increase

in risk of disease relapse.

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Colon cancer relapse and management

Despite the fact that approximately two thirds of CRC patients present with non metastatic (stage I-III)

disease, it is estimated that up to half of these patients will develop disease recurrence (16-20). The liver

is by far the most common intra-abdominal site of recurrent disease, likely via hematogenous spread

through the portal system. It has been estimated that the liver may be involved in up to 71% of patients

with disease recurrence (21) and is most frequently the first site of recurrence (20). The most common

extrabdominal site for disease relapse is the lung (20, 21). Other commonly observed sites of recurrence

include locoregional recurrence (anastomotic, mesenteric, or a second colorectal primary) (20-24),

peritoneal, bone, CNS, or adrenal (21).

Chemotherapy for CRC relapse

The most widely used chemotherapeutic agent for CRC is 5FU, and this also holds true for relapsed (or

advanced) disease (25, 26). Combined with the modulating effects of leukovorin, and optimized dosing

schedules, response rates of up to 23% and median survivals from 11 to 13 months have been reported for

patients with advanced disease (27, 28). Beginning in the mid 1990’s, irinotecan and oxaliplatin were

found to have activity against advanced CRC. The impact of irinotecan as a second line therapy was

demonstrated in two large randomized phase III studies, including patients who failed initial treatment

with 5FU/LV (29, 30). In 1998, Cunningham et al. (29) randomly assigned metastatic CRC patients, who

had progression of their disease after 6 months of 5FU treatment, to a course of 300-350mg/m2 irinotecan

every three weeks along with supportive therapy or supportive care alone, in a 2:1 ratio. The irinotecan

arm had 189 patients while the supportive care only arm had 90 patients. After a median follow-up of 13

months, the irinotecan arm had a significantly higher one year survival (36.2% vs. 13.8%), as well as

significantly better quality of life scores. Also in 1998, Rougier et al. (30) randomized 267 metastatic

CRC patients who failed first line 5FU treatment to receive either irinotecan (300-350 mg/m2 every three

weeks) versus continuous 5FU infusion. Median survival favored the irinotecan arm (10.8 months vs. 8.5

months). The efficacy of irinotecan or oxaliplatin combined with standard 5FU as first-line therapy for

advanced disease has also been assessed in several phase III trials, where median survivals of 14.8 to 21.5

months have been reported (27, 31-35).

In addition to new chemotherapeutic agents, the efficacy of using targeted therapy for advanced CRC is

being explored. Cetuximab is an antibody targeted to epidermal growth factor receptor (EGFR), which is

upregulated in 60-80% of colorectal cancers. Saltz et al. (36) reported a 10% tumour shrinkage was

observed when 60 patients were treated with antibody monotherapy. The synergistic relationship between

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cetuximab and irinotecan was confirmed by Cunningham et al (37), where 329 patients with advanced

CRC refractory to irinotecan/5FU were treated with cetuximab alone or in combination with

irinotecan/5FU/LV (IFL). Median survival improved from 6.9 to 8.6 months with the combination

therapy, when compared to antibody monotherapy. Bevacizumab is an antibody against vascular

endothelial growth factor (VEGF), thus inhibiting the angiogenesis and vascularity of tumors, potentially

improving the delivery of chemotherapy. In combination with IFL, bevacizumab improved median

survival from 15.6 to 20.3 months (38).

However, despite the improvements in survival from both new chemotherapy agents and targeted agents,

the prognosis for all patients with advanced CRC treated with only these therapies remains poor; five-year

survivors are seldomly reported.

Hepatic resection for CRC metastases

Among patients who experience disease relapse, it is estimated that up to half of these patients have the

liver as the only site of relapse (39). Of the patients who develop CRC liver metastases, it is estimated

that 10-30% may be suitable for hepatic resection (39-42). Over the past 3 decades, a body of research

has assessed the survival benefit of hepatic resection for isolated CRC metastases. Historically, until the

1980s, CRC metastases to the liver were often left untreated. Data from this time period demonstrated the

poor survival associated with this disease stage, with median survivals of five to ten months (42, 43).

Five-year survivors were extremely rare (39, 42). Even in studies examining patients with limited liver

metastases who could have potentially been candidates for liver resection, five year survival rates of 2%

to 8% were observed (42, 43). Early reports on the success of hepatic resection were met with skepticism

(44). In the past, liver resections were also perceived to be associated with a high degree of morbidity

and mortality, and the potential benefit for resection of metastatic disease was reserved for carefully

selected patients (45). In addition, it was argued that the benefits of resection were biased as there were

no adequate controls for comparison (44). However, in the following years, three major factors have

improved the outcomes of resection of hepatic metastases. Patient selection has improved through

advances in medical imaging. Perioperative and anaesthetic care has also improved through better

understanding of physiology, and finally, surgical technique has improved through better understanding

of hepatic anatomy (42).

It is now recognized that CRC liver metastases are not only potentially curable, but are also optimally

managed in a multidisciplinary setting including liver surgeons, medical oncologists, radiologists and

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interventional radiologists. As a result, reported 5 year survival following hepatic resection for CRC

metastases have slightly risen from 25-37% in the 1990’s (46-50) to 40% and above since 2002 (41, 51).

A 10-year survival rate of about 20% has also been reported for these patients in at least four series with

long-term follow-up (41, 46-48), as compared to a negligible 10-year survival rate in patients with liver

metastases not treated with resection. The eligibility for patients to potentially receive a hepatic resection

for CRC metastases is also increasing, as more aggressive approaches are adopted, such as two stage

hepatectomies (52-55) and repeat hepatectomies (39, 56-58). Although there has not been a randomized

trial examining the benefit liver resection for CRC metastases, these recent results are clearly superior

compared with historical controls, and those with no treatment or received systemic chemotherapy only.

Furthermore, it is highly unlikely that a trial comparing surgery versus chemotherapy versus no treatment

would ever be conducted, due to lack of clinical equipoise.

Recently, the 10 year experience at the University of Toronto for hepatic resection of CRC metastases

was reported (41). All patients undergoing liver resection for metastatic CRC were identified over a 10

year period starting in 1992. A total of 423 hepatectomies were performed in 395 patients. The primary

outcome was overall survival, while the secondary outcomes were disease free survival, perioperative

morbidity and mortality. The various hepatic resections ranged from wedge (non-anatomic) resections, to

major resections of greater than 4 anatomic segments. Nearly one-third (32%) of patients presented with

stage IV disease. Notable results included a median OS of 53 months, along with 1, 5, and 10 year OS of

93%, 47% and 28%, respectively. The median DFS was 19 months, with a 1, 5, and 10 year DFS of 64%,

27% and 22%, respectively. Factors identified as having a poor prognosis included advanced age (>60

years), multiple metastases, lesions greater than 5cm, and a positive margin after hepatic resection. These

data were in agreement with other single institution data, and also demonstrates a substantial

improvement in survival as compared to a report from an earlier period (1977-1992) at the University of

Toronto, where the 5 year OS was 34% (59). A number of factors may explain the improved survival

rates, including improvements in surgical technique, critical care, the recognition of other adjunctive

modalities such as radiofrequency ablation (60, 61) and peri-operative chemotherapy which may provide

an additional survival benefit (62). Recently, the EORTC Intergroup randomized phase II study 40983

(EPOC) evaluated the benefit of peri-operative oxaliplatin based chemotherapy for patients with

potentially resectable liver metastases, by randomizing 364 patients to either chemotherapy plus surgery

or surgery alone. It was reported that peri-operative chemotherapy and surgery for patients with

resectable liver metastases confers a statistically significant 7.1% absolute increase in three year

progression-free survival (63).

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Since only 10-30% of CRC metastases to the liver may be initially resectable, attention had turned to

chemotherapy regimens to improve resectability rates. With recent flurouracil, oxaliplatin, or irinotecan

based chemotherapy regimens, previously unresectable hepatic metastases have been successfully

downstaged to allow resection (64-68). The survival benefit of such resections have shown to be superior

to chemotherapy alone, with 5 year overall survivals of 35-40% (65, 66). With the increasing use of

targeted therapies such as cetuximab and bevacizumab, resectability rates are continuing to rise along

with a larger proportion of patients eligible to receive potentially curative surgical therapy.

Pulmonary resection for CRC metastases

Despite being involved in up to 20% of CRC relapses (20, 69), pulmonary relapses are often

asymptomatic. The most frequent symptoms of cough and hemoptysis occur in 15-20% of patients, and

are usually secondary to the proximity of the lesion to major airways. Other symptoms may also include

pneumonia, discomfort, neoplasia or paraneoplastic symptoms (69). Therefore, most pulmonary relapses

are detected incidentally on chest imaging. An important consideration is that the differential diagnosis

for lung nodule in a patient with a history of CRC may also include a benign neoplasm, granuloma,

hamartoma, or even a primary lung cancer (69). Thus, a tissue diagnosis via biopsy is required prior to

treatment. This is in contrast to liver relapses, where characteristic CT and ultrasound findings, along

with serial imaging, can establish a high index of suspicion for diagnosis.

Historically, it has been estimated that a small proportion (1-2%) of CRC relapses are both isolated to the

lung and are amenable to surgical resection. The first reports suggesting pulmonary resection for

metastatic disease were dated as far as 1927 and 1939 (70, 71). The first reported resection of the lung for

CRC metastasis was in 1944 by Blalock (72). As in the case with isolated liver metastases, there have not

been any prospectively randomized studies comparing surgical resection to medical management,

however there is a growing body of evidence supporting a survival benefit for surgical resection of

isolated lung recurrences (73-84).

In recent years, the 5 year overall survival rates after resection of CRC lung metastases are from 30-60%

(73-77, 85-87). A recent retrospective series by Yedibela et al. (77) reviewed a single institution

experience of resecting 153 patients with pulmonary CRC metastases. The range of surgical procedures

included wedge resection, segmental resection, lobectomy, bilobectomy, or pneumonectomy. The 5-year

overall survival was 37%, with a median survival time of 39 months. When the analysis was performed

on patients with a curative operation (R0, microscopically free of residual disease), the 5-year overall

survival was 39% with a median survival time of 43 months. Although not universally agreed upon, poor

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prognostic factors associated with pulmonary CRC relapse resection may include multiple lesions, a

rising CEA, higher stage of the primary tumor, and lymphatic involvement of the relapsed lesion (76-78,

82, 85).

There have also been several small series examining the survival following the resection of both hepatic

and pulmonary CRC relapses in selected patients (88-91). Similarly, in these patients, it has been shown

that resections of both organs are safe, and confer a potential survival benefit. In a recent report

documenting the experience at the University of Toronto (89), 39 patients underwent both lung and liver

resections for metastatic CRC from 1992 to 2002. Eleven of these patients had synchronously identified

metastases and underwent staged resections of the primary CRC and metastases. The remainder

underwent sequential resections of the colon, lung and liver. The median survival following the final

resection of metastasis (either in the liver or the lung) was 42.2 months. Furthermore, it was observed

that the median overall survival from the initial diagnosis of colon cancer was nearly ten years (117

months). This was a relatively small series of patients, however the results are in agreement with other

studies; 5 year overall survival following resection of both lung and liver recurrences ranged from 30-

60%, with median survivals from the time of the last resection of metastasis of 16-41 months (88-91).

Post-resectional surveillance for Colorectal Cancer

Due to the advent of newer chemotherapy such as oxaliplatin or irinotecan-based regimens, targeted

molecular therapies such as cetuximab and bevacizumab and the availability of potentially curative

surgery in the treatment of disease relapse, effort has been directed to establish the role surveillance after

resection of the primary tumour. The goal of surveillance is three-fold: to monitor for the development of

second primary tumors of the colon and rectum, to detect tumor recurrence at a stage where potentially

curative surgical therapy may be used, and to provide psychosocial support to the patient (19). As

approximately 80% of disease relapse occurs within the first 3 years after the primary CRC resection, and

over 90% within 5 years (92, 93), surveillance during this period is particularly important.

However, randomized trials of surveillance strategies have had conflicting results likely due to the

heterogeneity of follow-up strategies employed by the trials, and there is controversy as to the optimum

strategy to follow. As a result, there have been conflicting recommendations on how follow-up should be

carried out (16, 94-98). In addition, practice patterns and physician attitudes towards CRC follow-up are

also variable (19). These variations may stem from the fact that many relapses are first manifested by new

symptoms by patients (99), and perhaps the yield of any extra surveillance tests are low for finding

additional treatable recurrences. Modalities for surveillance commonly include periodic history taking

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and physical examinations via physician follow-up visits, combinations of laboratory tests (eg. CEA, liver

function, complete blood counts, fecal occult blood), diagnostic imaging (ultrasound, computed

tomography, magnetic resonance imaging), or endoscopic surveillance (colonoscopy, sigmoidoscopy).

Since 1990, there have been at least seven studies comparing different high intensity versus low intensity

surveillance strategies following curative CRC resection (99-105). The findings from these studies are

summarized in Table C.

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Table C. Summary of seven randomized trials comparing surveillance strategies after CRC resection. Trial Patients/Intervention Summary

Kjeldsen et al.

(101)

Control (n=307):

Clinical assessment, Hb, ESR, LFTs, CXR, FOB,

colonoscopy +/- DCBE at 5,10,15 years

Intervention (n=290):

Same tests as control, except q6mo x 3 years, then at

4, 5, 7.5, 10,12.5, 15 years

Recurrence rates equal among both arms (26%), but those in

intervention arm were more frequently asymptomatic,

diagnosed 9 months earlier, with more having surgery for

curative intent. However, overall and disease specific survival

was similar in both arms.

Makela et al.

(102)

Control (n=54):

Clinical assessment q3mo x 2 years, then q6mo x 3

years, including CBC, FOBT, CEA, CXR. Rigid

sigmoidoscopy for rectal/sigmoid patients, barium

enema q12 mo.


Same frequency and testing as control arm, except

q12 mo colonoscopy, flex sig. for rectal/sigmoid

patients q3mo, liver US q6 mo, abdominal CT q12mo

Recurrence rates equal among both arms (41% overall).

Intensively followed patients were diagnosed with recurrence 5

months earlier. Endoscopy and US were beneficial but CT

failed to improve diagnostic rate. However, cumulative 5 year

survival was similar between both arms.

Ohlsson et al.

(99)

Control (n=54):

FOB q3mo x 3 yrs then q12 mo; clinical assessment

when symptoms arise.


Clinical assessment, rigid sigmoidoscopy, CEA,

LFTs, FOBT, CXR q3mo x 2 years, then q6 mo

Endoscopy assessment of anastomosis (flex sig,

colonoscopy) at 9, 21, 42 mo

Complete colonoscopy at 3, 15, 30, 60mo

CT pelvis at 3, 6, 15,18, 24 mo (if APR)

Recurrence rates equal among both arms (32-33%). No patient

underwent surgery for distant metastases. Cumulative 5 year

survival rates for the control arm was 67% and the intervention

arm 75%, which was not statistically significant.

Pietra et al.

(105)

Control (n=103):

Clinical assessment, CEA, liver US q6 mo x 1 yr,

then q12 mo. CXR and colonoscopy q12 mo.


Clinical assessment, CEA, liver US q3mo x 2 yr then

q6 mo x 3 yr, then q12mo. CXR, abdominal CT,

colonoscopy q12mo.

Recurrence detection rates in both arms were not statistically

different (20% and 26%). Distant metastases were resected at

similar rates in both arms. 5 year cumulative (53.3% vs 73.1%)

and disease free survival (53.3% vs. 68.2%) was statistically

different among both arms. Overall, the data supported an

intense follow-up regimen, at least for rectal cancer patients

due to the higher rates of local recurrence.

Rodriguez et al.

(103)

Control (n=132):

Clinical assessment, CBC, LFTs, CEA q3mo x 2 yr

then q6mo x 3 yr


Clinical assessment, and lab tests as control arm

Abdominal CT or US q6mo x2yr, then q12mo

CXR q12 mo, colonoscopy q12 mo

There was no statistical difference in the rate of tumor

recurrence in either arm, time to relapse, or type of recurrence.

There was a higher proportion of resectable tumor recurrence in

the intervention arm, and remained significant after adjusting

for potential confounders. Overall, there was no difference in

overall survival, but a survival benefit was observed for those

with stage II disease and rectal tumors.

Secco et al. (104) Control (n=145):

Assessment by telephone q6mo. Clinical assessment

by family physician q12 mo or when symptoms arise.


High risk pts: Clinical assessment and CEA q3mo x 2

yrs, q4 mo x 1 yr, then q6 mo x 2 yr

Abdominal and pelvic US q6mo x 3 yr then q12 mo

x2 yr. Rigid sigmoidoscopy and CXR q12 mo for

rectal pts.

Low risk pts: Clinical assessment and CEA q6mo x 2

yrs, then q12mo x 3 yrs. Abdominal and pelvic US

q6mo x 2 yr then q12 mo x 3yr. Rigid sigmoidoscopy

q12mo x 2 yr then q2yr and CXR q12mo for rectal

pts.

Recurrence rates were similar among both arms (52.6%,

57.2%). Patients in the intervention arm at high risk had a

significantly higher number of curative reoperations. Actuarial

5 year survival of all patients in intervention arm was

significantly better than those in the control arm

Schoemaker et al.

(100)

Control (n=158):

Clinical assessment, CBC, LFTS, CEA, FOBT q3mo

x 2 yrs, q6mo x 5 yrs


Clinical assessment and lab tests as per control arm,

plus CXR q12mo, CT liver q12 mo, colonoscopy

q12mo.

There was no statistically significant difference in mortality

rates between the two follow-up schedules, overall, by stage, or

by tumor location. Although more patients had asymptomatic

liver recurrences detected with intense surveillance, a similar

number of patients in both arms received a liver resection.

12

Recently, six (99-103, 105) of the aforementioned seven trials were analyzed in a meta-analysis (92).

Although limited by the heterogeneity of the included trials, their inclusion provided improved power to

detect statistical differences among different CRC surveillance modalities. This analysis observed an

overall survival benefit at 5 years for more intensive follow-up (OR 0.73, 95%CI 0.59-0.91), although as

expected, the number of recurrences in both arms were similar (OR 0.91, 95%CI 0.75-1.10). There was a

mortality benefit for performing more tests compared to fewer tests (OR 0.64, 95%CI 0.49-0.85), and

liver imaging (OR 0.64, 95%CI 0.49-0.85). In the more intensively followed arm, there was also a

significantly higher proportion of patients who had curative surgical procedures attempted (OR 2.41,

95%CI 1.63-3.54). The weighted mean differences for the time to recurrence was also significantly

smaller in the intensive surveillance arm, with an observed reduction of -6.75 months (95%CI -11.06 - -

2.44). However the conclusion of this meta-analysis emphasized that it was not possible to determine

from the data the best combination or frequency of physician visits and surveillance test that would yield

the optimum follow-up strategy, nor was it possible to evaluate costs or potential harms of intensifying

follow-up. Despite these limitations, in the context of the controversy surrounding whether there is any

clinical benefit in intensifying CRC surveillance, this is among the best evidence to date in support of

intensifying follow-up.

The current guidelines issued by Cancer Care Ontario (94, 106) are also based on a meta-analysis of

similar studies as the Cochrane review (99-102, 104, 105). The findings of this study were similar: there

was a significant improvement in survival with more intensive follow-up strategies (relative risk ratio

0.80, 95%CI 0.70-0.91), and despite a similar number of recurrences in both arms, asymptomatic

recurrences and reoperations for cure of recurrences were more common in the more intensively followed

arm. At the conclusion of the study, it was recommended that for patients at high risk of disease

recurrence (stage IIb, III), clinical assessment should be performed at least every 6 months (or when

symptoms occur) for the first 3 years of follow-up. At the time of these physician visits, patients may

have blood CEA, liver imaging, or chest radiography. For patients at lower risk of recurrence (stage I,

IIa), or with comorbidities that preclude surgery for metastatic disease, physician visits should be

performed at least yearly, or when symptoms occur. With regards to colonoscopy, all patients should

receive a follow-up colonoscopy within 6 months of curative resection (if a preoperative colonoscopy was

not performed), or else repeated every 3-5 years if no adenomas are found. It is noted that these

guidelines do not mandate liver imaging, but suggest that they may be a part of the follow-up regimen. In

contrast, follow-up guidelines from the American Society of Clinical Oncology [ASCO] (96) mandate an

annual CT scan for the first three years following primary CRC resection.

13

There has also been one randomized controlled trial comparing general practice versus surgical-based

follow-up for patients with colon cancer (107). A total of 203 patients were randomized to either a general

practitioner or surgeon-led follow-up, with identical guidelines given to both groups. It was

acknowledged that clinicians in either setting were not compelled to adhere to the guideline, and

crossover between the two arms was allowed. The recommended follow-up regimen included 3 monthly

visits for the first 2 years, followed by visits 6 monthly. In addition to history and physical examination,

diagnostic tests included annual FOBT and colonoscopy every 3 years. Primary outcomes were quality of

life, depression and anxiety, and satisfaction. Secondary outcomes were the number and type of

investigations, number and time to detection of recurrences, and deaths from all causes after 2 years into

the study. There was no significant difference in quality of life, depression or anxiety, or satisfaction

between the two arms. However, patients in the GP-led arm were more likely to have FOBT, while those

in the surgeon arm were significantly more likely to have more imaging (ultrasound) or endoscopic

(colonoscopy) surveillance. The study was not powered to detect differences in death or recurrence rates,

and despite a lower time to recurrence and death rate in the surgeon led group, there was no statistically

significant difference between the two arms.

Variation in care after colorectal cancer resection

With respect to surveillance following curative colorectal resection, variations and disparities have been

identified. Rolnick et al. (108) examined a cohort of 881 non-metastatic resected CRC patients in the

United States, and showed that African-American and elderly patients were less likely to receive colonic

endoscopy modalities at 1, 3 and 5 years following primary CRC resection. Similar results were found in

a study of SEER-Medicare patients, where elderly African Americans were less likely to receive colonic

surveillance after primary CRC resection, despite adjusting for sociodemographical, hospital, and clinical

characteristics. Cooper et al. (109) examined the patterns of postoperative endoscopic follow-up among

SEER-Medicare patients, and showed that only 51% of patients received an endoscopic exam in the

follow-up period, along with geographic variations in practice patterns. In another study by Cooper

(110), further tests were examined among SEER-Medicare CRC patients, including liver enzymes, chest

x-rays, and CT scans. It was observed that rates of testing were lower with increasing age, less

comorbidities, and there was significantly variability among different SEER regions in the use of these

tests, ranging from 1.5 to 3.6-fold.

Attitudes towards CRC follow-up among Ontario physicians were examined in a recent survey by Earle et

al (19). In this study, all Canadian radiation oncologists, medical oncologists and surgeons specializing in

CRC were assessed for their follow-up recommendations for a hypothetical patient (a 50 year old healthy

14

man with stage III disease after a curative CRC resection). Out of the 160 physicians who completed the

survey, the majority recommended clinical assessment every three to four months for the first two follow-

up years. The recommended follow-up frequency decreased with each year until year 5, where 45%

recommended 6 monthly and 45% recommended yearly visits. Beyond 5 years of follow-up the majority

recommended no follow-up visits. Less than one third of the physicians recommended body surveillance

by ultrasound imaging for any follow-up year, and less than 10% recommending abdominal CT in any

follow-up year (including year 1). In contrast, about 90% of physicians recommended bowel surveillance

with colonoscopy in follow-up year one, decreasing to 65% of physicians recommending it in year 5.

There were other notable results from this study. The majority of physicians surveyed (64%) stated that

they routinely discharged patients to their primary care physician for follow-up, although a similar

proportion (66%) agreed that alternating follow-up between primary care physician and specialists was

appropriate. Regarding attitudes towards follow-up, 65% thought that finding local recurrences improved

survival, while 50% felt that specialists were more efficient (eg. less likely to order unnecessary tests) at

providing follow-up care than primary care physicians.

Population-based studies on CRC relapse and management

By examining population based data, one may be able to examine treatments and outcomes in the absence

of the bias introduced by single center series. In addition, examination of a large number of patients in a

population allows examination of non-clinical, health services related variables which may have an effect

on treatment and outcome. These variables may include geographic region, socioeconomic status, ethnic

origin, proximity to academic center, or urban versus rural place of residence. Although clinical details

are often not available because such studies often examine administrative data, population-based studies

can be a rich source of descriptive information for a population of interest, and can generate numerous

hypotheses to base future studies upon.

Several groups have attempted to describe CRC relapse, and its management on a population level,

especially with respect to the use of hepatic resection. Leporrier et al (111) examined patients with CRC

from the Digestive Cancer Registry of Calvados, France, from 1994 through 1999. Of 1,315 patients

examined, 358 developed hepatic metastases, where 17.3% received a surgical resection, 40.2% were

treated with palliative chemotherapy, while the remaining 42.5% were treated symptomatically. For the

overall group, median survival was 10.7 months, while the 5 year OS was 14%. When analyzed

separately, the group with hepatic metastases who were surgically resected had a median survival of 44.7

15

months, those treated with palliative chemotherapy had a median survival of 13.5 months, and those

treated symptomatically had a median survival of 4.5 months. A logistic regression analysis was

performed to attempt to identify factors associated with the use of surgical resection for hepatic

metastases. Significant clinical parameters negatively associated with hepatic resection included age

greater than 75 (OR 0.14, 95%CI 0.04-0.45), 2-3 hepatic metastases (OR 0.28, 95%CI 0.14-0.57) or >3

hepatic metastases (OR 0.02, 95%CI 0.01-0.07), or size of largest hepatic metastasis > 50mm (OR 0.47,

95%CI 0.23-0.96). Non-clinical parameters evaluated included the place of treatment (academic vs non-

academic center), place of residence (urban vs rural) and diagnosis period (1994-1997 vs 1998-2002),

however the only significant factor with a positive association with hepatic resection was recent period of

diagnosis (OR 2.03, 95%CI 1.16-3.56), likely reflecting the increasing recognition of its potential survival

benefit. Other non-clinical, population level factors such as socioeconomic status and geographic region

were not assessed.

Manfredi et al. (112) also examined a population-based cancer registry in France from 1976 to 2000,

examining the incidence, treatment and prognosis of CRC liver metastases. Of the 13,463 patients with

CRC, 14.5% had hepatic metastases discovered during diagnostic workup or during the course of

treatment, with 76.8% confined to the liver. Resection for cure was performed in 6.3% of these patients.

For 3,655 patients with follow-up data, 12.8% developed liver metastases over the 5 years following

diagnosis, and 16.9% of patients were resected for cure. The proportion of patients treated with palliative

chemotherapy increased with time, while those treated symptomatically decreased. Multivariable

analyses to determine factors associated with resection for cure or survival did not include any non-

clinical factors such as geographic region, socioeconomic status, or treatment at academic center.

There has been one population based study that suggests the potential role for imaging, follow-up routines

and multidisciplinary management to improve outcome in patients with CRC hepatic metastases. Sjovall

et al (113) examined 2,280 CRC patients in Sweden from 1996 through 1999 for their treatment and

outcome, and also analyzed their imaging to evaluate resectability. Hepatic metastases were discovered

in 537 patients (24%), where 266 patients had disease isolated to the liver. However, a hepatic resection

was performed in only 21 patients (4% of those with liver metastases). By re-evaluation of liver imaging

of these patients, it was determined that less than 50% of immediately potentially resectable patients

received a resection. By using reported rates of salvageability with chemotherapy for non-resectable

patients combined with eligible patients who did not receive resection, it was estimated that up to 17% of

those with liver metastases could have been treated with potentially curative surgery. This finding

suggests that in addition to the clinical factors associated with surgical resection that were explored in

16

other series, there may also be other non clinical health services related factors that may be associated

with the use of surgery in the management of relapsed disease.

17

Rationale

For the population of Ontario, the processes of care and outcomes of patients who have received curative

resection for CRC have not been previously described. These data are important in order to establish the

current practice patterns in Ontario, as well as the outcomes that result from them. Such a description

may reveal potentially modifiable or addressable processes of care that a patient receives following CRC

surgery. For example, there may be variations among different Ontario regions, or patients in different

socioeconomic groups for receiving potentially curative surgery for disease relapse, but there is no data

existing to determine whether or not such variation may be appropriate (eg. if a LHIN had an unusually

large proportion of high risk patients, that LHIN may appropriately have a higher rate of potentially

curative surgery). As Ontario has recently regionalized health care into Local Health Integration

Networks (114), it is particularly important that individual needs or deficiencies in regions are identified

such that further research may be performed to elucidate the details of the cause and what is needed to

address them. An initial but detailed descriptive study of the Ontario population would help establish

future research priorities for processes of care in CRC follow-up.

A detailed descriptive study may also provide information about the potential denominator of patients

who may be eligible for surgical treatment of relapse. By comparing the proportion of patients receiving

surgery to expected proportions from the literature, potential differences can be identified and

investigated. Previous population-based studies have not attempted to examine the relationship between

processes of care following primary CRC resection and the treatment of relapse. Preliminary analytical

models may be constructed from descriptive data that may provide further evidence to support guidelines

for surveillance, and generate further hypotheses to explore. Finally, there is a need to develop a

validated method for identifying CRC relapse in administrative data. As administrative data in Ontario is

readily available and population based, the potential for using this algorithm in future studies is

substantial. This may include future studies that evaluate measures of quality, or that assess population

health effects from knowledge translation initiatives.

18

Objectives

Primary objectives

1) To describe the processes of care that patients receive in the follow-up period, including MD

visits and surveillance tests

2) To describe the proportion of patients that had evidence of disease relapse, who receive surgical

treatment in the management of relapse, with stratification by LHIN and income quintile

Secondary objectives

1) To explore potential factors associated with the receipt of body imaging or endoscopy in the

follow-up period after CRC resection

2) To explore potential factors associated with the use of surgery in the management of relapsed

disease

3) To assess the sensitivity and specificity of classification of disease relapse and high risk disease

in the study cohort by using a primary chart reviewed cohort of CRC patients

Hypotheses

It is hypothesized that greater than 80% of Ontario CRC patients will receive surveillance colonoscopy at

least once in their 5 year follow-up period, as well as at least one body imaging modality. Most patients

will receive follow-up from their general surgeons on average once per year.

For disease relapse, it is hypothesized that there will be no significant association between LHIN or

income quintile and the rate of relapse. However, there will be statistically significant differences in the

proportion of patients who receive surgical treatment for relapse, across LHINs and income quintiles.

Among the exploratory analyses, it is hypothesized that income quintile will be a determinant for the

receipt of both body imaging and endoscopy. The main predictors for the use of surgery will be age and

comorbidity, as well as the frequency of body imaging that the patient received in follow-up.

It is hypothesized that the classification of relapse used in the study will yield both a specificity and

sensitivity rate of greater than 80%. Furthermore, the classification of high risk disease will capture

greater than 90% of stage III patients and 30% of stage II patients.

19

Methods

A retrospective cohort study was performed at the Institute for Clinical Evaluative Sciences (ICES). The

sources information included the Ontario Cancer Registry (OCR) and the following linked administrative

databases: the Canadian Institutes of Health Information Discharge Abstract Database (CIHI-DAD), the

Ontario Health Insurance Plan (OHIP), the ICES physician database (IPDB), the Registered Persons

Database (RPDB). Research ethics board (REB) approval for this study was obtained from the

Sunnybrook Health Sciences Center and the University of Toronto. For secondary analysis of the

externally collected, chart reviewed cohort of CRC patients from Princess Margaret Hospital and Credit

Valley Hospital, REB approval was obtained from the University Health Network and Credit Valley

Hospital and permission of Dr. Lillian Siu.

Data sources

The Ontario Cancer Registry

The OCR collects information on all incident cancers in Ontario. The OCR is operated by the Ontario

Cancer Treatment and Research Foundation (OCTRF), which was established in 1943 by the Cancer Act.

Via subsequent amendments to the Cancer Act, hospitals are required by law to report incident diagnoses

of cancer to this registry, where information such as tumor characteristics and some patient demographics

are recorded (115, 116). There are four major data sources from which the OCR abstracts information

(115, 116). The first source is by hospital discharge abstract summaries with a diagnosis of cancer. These

hospital abstracts are summarized, forwarded and recorded into CIHI-DAD via the Ministry of Health.

From this point the record is forwarded to the OCR. These hospital abstracts may contain up to 16

diagnoses, from which one may be that of cancer. The second source of information is via pathology

reports. Starting in 1973, all pathology laboratories in Ontario were required to submit reports where

cancer was mentioned, and compliance reached 100% in 1980. These reports are submitted directly to the

OCR, where the data is coded and abstracted. The third major source of data is death certificate

information. This is achieved via special arrangement with the Office of the Registrar General of Ontario,

where all deaths are reported and the underlying cause of death is determined. When the underlying

cause is determined to be cancer, the case is reported to the OCR. Additional information may be sought

by the OCR (data requested from health institutions, etc) to complete the record, if corresponding cancer

information cannot be found in any of the other data sources (ie. the case is a death-certificate-only

(DCO) case). The fourth major source of data is direct reporting from regional cancer centers (RCC’s)

and the Princess Margaret Hospital (PMH). These cancer centers record tumor registry data and forward

20

them directly to the OCR for data abstraction. The records in OCR are indexed by an encrypted OHIP

number (IKN, ICES key number), each representing an individual patient.

Administrative databases

The CIHI-DAD is an administrative database consisting of discharge abstracts of each hospital stay for

every patient in Ontario, regardless of disposition (patient went home, died, transferred to another

hospital). The main data elements include patient demographics (eg. sex, date of birth, postal code,

county and residence code), clinical data (eg. diagnoses, procedures performed), and administrative data

(eg. institution number, admission category, length of stay, disposition). The OHIP database consists of

all physician billings submitted to OHIP. Information in an OHIP record includes the date of service, fee

code (as per the OHIP Schedule of Benefits), and the billing physician’s number (corresponding to the

IPDB). The IPDB is a database updated yearly, consisting of a unique number for every physician in

Ontario. Each IPDB record also contains the physician’s self-reported main specialty. Finally, the RPDB

consists of basic demographic information about anyone who has ever received an Ontario health card

number. This data is supplied by the Ministry of Health and is enriched with other in-house data at ICES.

There is one record for each health card number issued, and consists of date of birth, sex, geographic

information on the place of residence, and if applicable, the date of death. All databases are indexed by

an ICES key number (IKN), a unique, encrypted identifier for individual patient records that allows for

linkage across the various data sources.

Validity

The use of administrative databases results in a large sample size, and often provides statistical power

where single institution series cannot. Furthermore, the bias introduced by selection of patients by single

centers is reduced. However, prior to using the data, it must first be ascertained whether these

administrative databases are dependably and accurately coded. By confirming the validity of the data

used, a higher degree of validity may be conferred to any conclusions drawn from the study of this data.

The completeness of detection of cancer, or case ascertainment, of the OCR has been evaluated as

described by Robles et al. (117). Two methods were used to estimate completeness of registration:

mathematical modeling using three data sources, and using two data sources with capture-recapture

methods. It was found that the two methods were similar in their estimates of case ascertainment, where

at most there was a 7% difference in estimate by cancer site. Overall, case ascertainment was greater than

90% for each of the 16 cancer sites.

21

Notably, variables describing the tumor stage (primary tumor size, extent, nodal status, and metastasis)

are not directly recorded into the OCR database. Staging of a tumor is very important clinically, as this is

what guides subsequent treatment of the tumor, and is used for prognostication. These parameters are

also important from a health services perspective, in order to aid researchers in determining whether or

not the patient received appropriate treatment. Although these data are potentially available, they can

only be accessed from the individual archived pathology reports that were submitted on cancer diagnosis.

With respect to CIHI-DAD, the validity of this database has been assessed in a recent reabstraction study

(118) as well as a previous inventory of seven reabstraction studies (119). Overall, less than three percent

of Ontario health records are missing demographic data. The agreement between the database and the

hospital chart for admission and discharge date, sex, birth date, admission source, and discharge

destination is greater than 97%. For principal procedure code there is 88%-96% agreement, and 100% for

death. However, there is less agreement when examining diagnoses, with 81% agreement for “most

responsible diagnosis”, and a greater than 60% false negative rate for the coding of specific comorbid

conditions and complications. These figures suggest that using these data will allow a high sensitivity

and specificity for detecting principal procedures such as surgical resection. However, with a high false

negative rate for coding specific comorbid conditions, there is a risk of under-detection of diagnoses such

as metastatic cancer. To the knowledge of the author, there are no validation studies of the other

administrative databases used.

Selection Criteria

Patients aged 18 to 80 years, with an ICD-9 diagnosis of colon or rectal cancer (153.0-153.4, 153.6-153.9,

154.0, 154.1), and an ICD-0-2 histology code of adenocarcinoma (8140, 8141, 8143, 8144, 8145, 8147,

8210, 8211, 8220, 8221, 8260, 8261, 8262, 8263, 8430, 8440, 8480, 8481, 8490, 8510, 8550, 8551, 8560,

8562, 8570, 8571, 8572, 8573, 8574, 8575, 8576) were identified from the OCR from January 1, 1996

through November 30, 2001. Patients with a diagnosis of any other neoplasm at any time based on OCR

records were excluded in order to remove the confounding effect of receipt of surgery or chemotherapy

for any tumors other than the colon cancer. Patients who had colorectal resectional surgery were

identified by searching for linked OHIP billings and CIHI-DAD procedures (Appendix Tables A.1, A.2),

starting from 14 days prior to the diagnosis date. This 14 day window allowed the identification of the

index colorectal resection for patients who did not have a preoperative diagnosis of CRC (eg. those who

presented with an obstruction, perforation). The service date for the OHIP claim for resection took

precedence for the CIHI admission date, in the case where both an OHIP claim and CIHI record for

resection was found. Either one OHIP claim or one CIHI code for CRC resection was considered

22

sufficient for classifying a patient as having received a primary CRC resection. Patients who did not

receive a colorectal resection, or who received a colorectal resection greater than 120 days following

diagnosis were excluded. These two exclusions were applied because the population of interest was those

who received a potentially curative colorectal resection for CRC; patients undergoing resection more than

4 months from diagnosis were not likely for curative intent. As the 90th percentile for Ontario wait times

in those patients with gastrointestinal cancer (including colorectal cancer) was less than 70 days (120),

this 120 day cutoff was conservative.

In order to identify a cohort of patients likely resected for cure and potentially disease-free following

primary colorectal resection, a series of exclusion criteria were applied based on data over the first year

after resection. This one year interval from the CRC resection permitted patients to complete

multidisciplinary treatment for the primary tumor (ie. the administration of a course of adjuvant

chemotherapy). Therefore, patients who had evidence of relapse in the first year were also excluded

based on these criteria.

The exclusion criteria applied during the first year following CRC resection were:

Death within the first year after colon resection

A diagnosis of advanced (secondary) disease code (Table A.3) within CIHI diagnosis codes in

hospital admissions

Evidence of early relapse of disease via lung or liver procedure (resection, destruction or biopsy)

(Table A.4)

A palliative care consult (OHIP fee codes A945, C945, W982, C982, W882, C882, W872, W972,

K023, K998, K996)

First claim for chemotherapy (Table A.5) greater than 120 days following primary colon resection

– in unpublished data (M. Kryzanowska, verbal comm.), over 90% of patients will initiate a

course of adjuvant chemotherapy within 4 months of the primary colon resection. Initiation of

chemotherapy later than this (but within the first year) is atypical and suggests treatment of early

disease relapse

Days between first and last chemotherapy claim exceeding 270 days, between days 0 and 395

after CRC resection. The usual duration of a course of adjuvant chemotherapy is 6 months.

Allowing time for breaks in treatment due to side effects or delays, a duration of chemotherapy

greater than 270 days likely represents ongoing treatment for metastatic or relapse of disease. For

23

this exclusion criterion, the first month of the second follow-up year was examined to

accommodate the definitions of late start and prolonged duration.

Finally, patients with missing LHIN of residence, or income quintile were excluded. Those patients

residing in Southeast LHIN were also excluded due to the alternate funding plan employed by this LHIN,

which affected the completeness of OHIP billings.

Demographic and patient related variables

Patient variables collected included sex, age at diagnosis of CRC and comorbidities at the time of CRC

resection. The comorbidity of a patient was expressed as a Charlson score (121), with the Deyo

modification (122) for use with ICD-9-CM diagnosis codes. The Charlson score is a weighted score

based on 16 diagnostic categories, and was designed to predict 1 year mortality. Although originally

designed based on a cohort of breast cancer patients, the Charlson score has been validated for CRC

patients as well (123) as a predictor for mortality. The Charlson comorbidity was calculated excluding

the index admission for CRC resection. Hospital admissions for two years prior to the index admission

were examined for primary and secondary diagnosis codes. The overall Charlson score was classified as

indicating low (0 to 1), medium (2) and high (greater than 2) comorbidity. Since every patient in this

study had cancer, the two diagnostic categories referring to neoplasm or metastatic disease were not

included in the calculation of the Charlson score. Patients who relapsed also had a Charlson score

calculated from the date of relapse (minus the index date for relapse, with a look-back period of two

years). Patients were classified as having received a total colectomy if their original CRC resection was

associated with CCP code 57.6, or OHIP fee codes S169, S170, S172-S174.

Demographic variables collected included the LHIN of the patient’s residence, as determined through the

RPDB, and the LHIN of the institution performing the colon resection. The mean neighborhood income

quintile was derived from the RPDB, postal codes and census tract information (census year 2001).

Rural status was based on the StatsCan definition, defined as residence in a community size of less than

10,000, based on the 2001 census.

Definition of high risk for recurrence

The receipt of adjuvant chemotherapy (at least one claim within 120 days of CRC resection) was used to

represent disease that was at high risk for relapse. The risk for relapse is usually represented by disease

stage, where higher disease stage was associated with a higher likelihood of disease relapse. However,

there was no variable representing tumor stage within OCR for the time period of this study. Since

24

adjuvant chemotherapy is recommended for stage III and selected stage II patients, this was chosen as a

proxy for stage in the absence of this variable in the administrative data.

Definition of disease relapse

As there was not an explicit variable within the administrative databases that represents disease relapse,

the event of disease relapse was represented by several variables: the appearance of a diagnosis code for

advanced disease (Table A.3), a liver or lung procedure (resection, destruction or biopsy) (Table A.2), the

new administration of chemotherapy (A.5), or new consultation to palliative care (OHIP fee codes A945,

C945, W982, C982, W882, C882, W872, W972, K023, K998, K996) (Figure 1). Lung or liver

destruction that were not clearly definitive resections or that were biopsies were classified as “other

procedure”. The date of relapse was defined as the earliest date of any of the aforementioned events.

Surgical resection for relapse was defined as a formal lung or liver resection for disease relapse (Table

A.4). Patients who died with a cancer related cause of death code (ICD-9 140.0 -199.1) from the OCR

were classified as having disease relapse, but with an unknown date of relapse.

Figure 1. Algorithm for classification of disease relapse

Descriptive statistics

Prior to applying exclusion criteria, the type of CRC of each patient in the inception cohort was described

via ICD-9 code. Descriptive statistics were generated for the excluded cohort and the final study cohort.

Continuous data were expressed as means and standard deviations, while categorical variables were

expressed as counts and percentages. When applicable, continuous data were compared using the

25

Student’s t-test, while categorical data were compared using the chi-square test. To better understand

why patients were excluded in their first year, counts of patients having at least two exclusion criteria

were summarized in a table of pair-wise combinations of exclusion criteria. The exclusion rates by LHIN

were also examined by direct standardization against the 1996 Ontario population by age (18-50, 51-60,

61-70, 71-80) and sex. Univariate descriptive statistics included patient demographics (age, sex), primary

cancer type (colon or rectum), high or low risk primary (represented by adjuvant chemotherapy),

Charlson comorbidity classification, LHIN, income quintile, and the time period of the study (1996-1998,

1999-2001).

The study cohort was divided into four groups: 1) those who were alive and had no evidence of relapse at

the end of the follow-up period, 2) those who had evidence of relapse within the follow-up period, 3)

those who had no evidence of relapse but died within the follow-up period, and 4) those whose only

evidence of relapse was a cancer related cause of death (ie. classified as relapse but the date of relapse is

unknown). Only the former two groups were used in the analysis of visits and tests, because patients in

the latter two groups either had an incomplete disease-free follow-up time, or an unknown date of relapse.

Preliminary analyses

Following the application of the patient selection criteria, the final study cohort of patients were likely

disease free and eligible for post operative follow-up in years two through five (the “follow-up period”).

A series of preliminary analyses were performed to establish data consistency. For all colon, liver and

lung resections, dates between OHIP claims and CIHI procedures were assessed for agreement. When the

documentation of a resection was from an OHIP claim only, all CIHI admissions 7 days prior and 7 days

following the claim was searched to possibly document the setting in which the OHIP claim was made.

Likewise, when the only documentation of the procedure was via CIHI procedure code, all OHIP claims

within 7 days of the admission were examined to document the activity surrounding the admission. The

diagnosis codes for all hospital admissions with lung and liver resections were also evaluated to

determine whether the resection was performed for metastatic disease.

For patients who received adjuvant chemotherapy, the mode, median and interquartile range of the

interval from the date CRC resection to the date of the first dose of chemotherapy was reported. The

mode and median number of chemotherapy doses were reported, with each dose identified as an OHIP

claim for chemotherapy on a different date. The mode and median duration of chemotherapy was

26

reported, with duration defined as the interval between the first and last dates of chemotherapy OHIP

claims.

Objective #1: Visits and tests

For physician visits, the specialty of the physician was determined by the specific consultation code that

was billed (general practitioner, general surgery, radiation oncologist, Table A.6). Medical oncologists

bill consultations using internal medicine fee codes, and thus could not be readily identified due to the

non-specificity of this designation. Instead, those physicians who had both a history of billing for

chemotherapy in the data set (January 1996 through March 2007), had a designation of “Medical

Oncology”, “Hematology”, or “GP/FP” in the IPDB and billed using internal medicine, GP/FP or

hematology consult codes were classified as medical oncologists (Table A.6).

For group #1 (who were alive and had no evidence of relapse in the follow-up period), the count of MD

visits (general practitioner, general surgeon, medical oncologist, radiation oncologist, see Table A.6) was

categorized (None, 1, 2, 3-5, >5). Endoscopy testing (sigmoidoscopy, colonoscopy, Table A.7), body

imaging modalities (CT abdomen/pelvis, ultrasound abdomen/pelvis, Table A.7), CT thorax, and MRI

abdomen/pelvis was similarly categorized. When reporting the number of patients having >5 visits or

tests, the median and range of the number of visits or tests for that group was also reported. The counts of

endoscopic modalities included those performed within the first year of follow-up, as adherence to current

guidelines may result in only one colonoscopy in the five year follow-up period. Patients who received a

total colectomy were excluded from endoscopy counts.

The polypectomy rate per endoscopy was calculated by taking the quotient of the total number of

polypectomy fee codes (Z570, Z571) by the total number of endoscopy, among patients alive with no

evidence of relapse at 5 years (group #1), who did not receive a total colectomy. This rate represents

endoscopies with >=1 polypectomy, as additional polypectomies are billed under different fee codes. For

the same group of patients, the rate of complete colonoscopy was determined by searching for a

colonoscopy code (Z555) accompanied by an additional code representing assessment of the caecum

(E747) or terminal ileum (E705).

Due to the varying amounts of time in follow-up for patients that relapsed within the follow-up period

(group #2), visits and tests were expressed as rates, per 6 months of follow-up time. A censoring period

(figure 2) was used to exclude any increased activity prior to the relapse event which may artificially

27

inflate the frequency of tests. Due to the possibility of an increase in testing or MD visits prior to relapse

(for example, multiple MD visits and CT scans prior to a liver resection), the analyses were performed

using a 60 or 90 day censoring period. Since endoscopy counts included the first 12 months after CRC

resection, the denominator in endoscopy rates included this time interval.

For either denominator of follow-up time, the frequency or rate of general surgeon visit and endoscopy

was stratified by colon or rectal primary, and the frequency or rate of radiation oncologist visit was

expressed for rectal primary (there is almost no role for radiation in the treatment of colonic primaries).

All categories were also stratified by high or low risk primary tumour.

Exploratory analyses for visits and tests (Secondary objective #1)

To examine potential factors associated with the increased likelihood of receiving at least one endoscopy

modality in follow-up years 1 through 5, a multivariable logistic regression model was constructed

(Model #1). The population for this analysis was group #1 (those who were alive and had no evidence of

relapse at the end of the follow-up period), but did not receive a total colectomy. The dependent variable

was the binary variable of receiving 1 or more endoscopies in the follow-up period (including year 1),

versus none. Covariates used included age at CRC diagnosis (continuous variable), sex, mean

neighborhood income quintile, colon versus rectal primary, rural or urban, Charlson comorbidity

classification, and period of diagnosis (1996-1998 vs 1999-2001).

Similarly, factors associated with the increased likelihood of receiving one or more body imaging

modalities was assessed using multivariable logistic regression (Model #2). This analysis was performed

on group #1. The dependent variable was the binary outcome of receiving one or more body imaging

modalities (CT, ultrasound) versus none. Covariates included age at diagnosis (continuous), sex, mean

neighborhood income quintile, Charlson comorbidity classification, colon versus rectal primary, rural or

urban, colon versus rectal primary, period of diagnosis, medical oncologist and general surgeon follow-

up. The latter two variables were classified as zero follow-up versus one or more visits in years 2-5.

Interactions between high/low risk primary tumour and general surgery or medical oncology follow-up

was assessed. If any of these interactions were significant, the model would be run with stratification by

high or low risk primary tumor. If not significant, the final model was run excluding these interaction

terms.

28

Objective #2: Treatment for disease relapse

To describe group #2 (relapsed during the follow-up period), the count of patients who relapsed by

follow-up year stratified by colon/rectum and high/low risk primary tumour was summarized. Secondly,

while stratifying by year of relapse, relapse events among this group over the follow-up period was

reported as counts and proportions. The counts and proportion of relapsed patients who received either

palliative (chemotherapy) or potentially curative (lung or liver resection) treatment was then summarized

by stratifying by LHIN or mean neighborhood income quintile. As a measure of difference between

highest and lowest LHIN or income quintile, the extremal quotient (EQ) was used. The EQ calculated by

taking the quotient of the highest to the lowest proportion. Differences between LHINs and income

quintiles were also assessed using the chi-square test. The two-sided Cochran-Armitage trend test was

used to assess for increasing or decreasing trends among income quintiles due to the ordinal classification

of this variable.

To characterize possible regionalization of lung and liver resections, the institution number associated

with the lung or liver resection was obtained from either the CIHI-DAD or OHIP record of the procedure,

and linked with its LHIN. The LHINs where all patients with either lung or liver resection received their

procedure were summarized by counts and proportions.

For survival, the vital status and date of death was obtained from the RPDB. Overall survival (OS) was

calculated from the date of liver or lung resection, or from the date of relapse until their date of death or

end of the available dataset (March 31, 2007). Survival was modeled using the Kaplan-Meier method

(124), reporting median and 5 year OS. Differences in survival between groups were assessed using the

log-rank test (125). Survival was assessed among those with evidence of CRC relapse in the 5 year

follow-up period, for those patients receiving liver resection versus none, lung resection versus none, and

receipt of chemotherapy versus none.

Exploratory analysis for relapse treatment (Secondary objective #2)

The primary outcome of surgical treatment of relapse (lung or liver resection) was examined using

multivariable logistic regression (Model #3). This analysis was performed on group #2 (evidence of

relapse in the follow-up period). Covariates in this analysis included age at relapse (continuous), sex,

Charlson comorbidity classification at the time of relapse, income quintile, rural or urban, colon or rectal

primary, high or low risk primary, period of diagnosis, general surgery visit frequency, medical oncology

29

visit frequency, and body imaging frequency. The latter three variables were expressed as frequencies per

6 months of follow-up, as patients who relapsed had varying follow-up times. As described above, there

was a potential for an increased frequency in tests and MD visits in the period prior to the first evidence

of relapse. Therefore the initial analysis was performed only examining events up to 60 days prior to

relapse. To assess sensitivity of results to the length of the censoring period, the analysis was repeated

censoring up to 0, 30, 90, and 120 days prior to the relapse date (Figure 2).

Figure 2. Schematic timeline representing censoring period for measuring test and MD visit frequency in

relapsed patients

In all logistic regressions, multicollinearity among covariates was assessed. A statistically significant

correlation coefficient greater than or equal to 0.8 was considered to indicate the presence of

multicollinearity, and in such cases only one member of a correlated set was retained for the multivariable

analysis.

Secondary Objective: Comparison with primary chart reviewed cohort

To determine the accuracy of the algorithm used to identify disease relapse in administrative data, a

cohort of patients reviewed by primary chart extraction was acquired (with permission from Dr. Lillian

Siu). This cohort consisted of stage II and III CRC patients treated during the time period of our study

(from 1999 through 2001) who were followed up at either an academic hospital (Princess Margaret

Hospital) or in a community setting (Credit Valley Hospital). Probabilistic linkage of individual level

data to the administrative databases occurred through a multi-step sequential process using patient name,

30

date of birth and diagnosis date of CRC if available. Of 529 patients, there were 6 duplicates and 9 non-

matches to the administrative data, and one invalid IKN. A total of 513 (333 eligible for follow-up, 180

ineligible due to progressive or recurrent disease on restaging at less than one year of follow-up) patients

were matched to a corresponding valid, unique encrypted identifier in the administrative data. These

patients were then matched with their corresponding records among the study cohort of patients, prior to

applying year-one exclusions. Variables used included date of diagnosis, clinical stage, pathologic stage,

relapse status (yes/no), location of relapse, and treatment for relapse. Sensitivity was calculated as the

quotient of true positives by the sum of true positives and false negatives. Specificity was calculated as

the quotient of true negatives by the sum of true negatives and false positives. Positive predictive value

was calculated as the quotient of true positives by the sum of true positives and false positives. Negative

predictive value was calculated as the quotient of true negatives by the sum of true negatives and false

negatives. The sensitivity, specificity, positive predictive value and negative predictive value of

classifying patients as eligible for follow-up was calculated by a 2x2 table summary. For any false

positives (those patients who actually relapsed in their first year, but misclassified as being eligible for

follow-up), it was determined whether or not they were eventually classified as having relapsed. In

addition, the interval from the date of resection to the date of relapse detection was described by the range

and median value. For the false negatives (patients eligible for follow-up by chart review but classified as

ineligible by the present study), exclusion criteria were examined for the cause of misclassification.

The group of patients who were appropriately classified as eligible for follow-up by the administrative

data was then examined for the sensitivity, specificity, positive predictive value and negative predictive

value of detecting disease relapse in the follow-up period, by a 2x2 table summary. For false positives

(classified as relapsed but did not by primary chart review) relapse criteria were examined for the cause of

misclassification. For false negatives (recorded as relapsed in the primary chart review but not by the

present study), the year of relapse, location of relapse, and where or not the relapse was surgically

resected was reported.

The overall group of patients (the group of patients excluded due to first year events, as well as those

deemed eligible for follow-up at year 2) was then summarized by a 2x2 summary table for the accuracy of

detecting disease relapse in the follow-up years 1-5. The sensitivity, specificity, positive predictive value

and negative predictive value was calculated.

Finally, the accuracy of using adjuvant chemotherapy as a proxy for high risk disease was evaluated by

stratifying the cohort by colon or rectal primary, then comparing receipt of adjuvant chemotherapy to the

pathologic stage recorded in the chart reviewed data. If pathologic stage was not available, clinical stage

31

was used. This stratification was used to reflect clinical practice guidelines (10) where both stage II and

III rectal cancers are recommended to receive adjuvant chemotherapy.

Data analysis

All programming and statistics was performed using SAS 9.1.3 for Unix (Cary, NC). All odds ratios

were reported with 95% confidence intervals. P-values of less than 0.05 were considered to be

statistically significant. All tests were two-sided.

32

Results

Inception cohort

A total of 23,914 patients were identified from the OCR from January 1, 1996 through November 30,

2001. These patients had a diagnosis of colorectal cancer with a histology of adenocarcinoma, aged 18-

80, and had no other primary cancers recorded in the OCR. After examination of linked data from CIHI

procedure codes and OHIP billing codes, 20,635 patients received a colorectal cancer resection from 14

days prior, to 120 days after the OCR diagnosis date. Of the different types of CRC, classified by ICD-9

diagnosis code, cancers of the rectosigmoid junction and rectum comprised of 29.3% of these patients.

For the colonic primaries, the most common ICD-9 diagnosis codes were for tumors of the sigmoid colon

(20.9%), cecum (13.0%), ascending colon (12.5%), and not otherwise specified (11.3%) (Table 1).

Table 1: Types of CRC by ICD9 diagnosis code

ICD9 code Definition N %

153.0 Hepatic flexure 400 1.9%

153.1 Transverse colon 944 4.6%

153.2 Descending colon 895 4.3%

153.3 Sigmoid colon 4306 20.9%

153.4 Cecum 2677 13.0%

153.6 Ascending colon 2578 12.5%

153.7 Splenic flexure 405 2.0%

153.8 NEC 62 0.3%

153.9 Not otherwise specified 2326 11.3%

154.0 Rectosigmoid junction 2028 9.8%

154.1 Rectum 4014 19.5%

Exclusions

To create the inception cohort of patients eligible for postoperative surveillance, patients were excluded

based on events at presentation or in the first year following primary CRC resection suggesting advanced

(metastatic) disease. These exclusions are summarized in Table 2 (numbers are not mutually exclusive).

The most common reason for exclusion was diagnosis of advanced disease (4609, 58.9%), followed by

death (3055, 39.3%), prolonged chemotherapy (1013, 22.7%), palliative care consult (1646, 21.0%), liver

procedure (1590, 20.3%), and late start of chemotherapy (804, 18.0%). Lung procedures accounted for a

minority of exclusions (113, 1.4%).

To understand the proportion of patients who were excluded based on fulfilling at least two exclusion

criteria, counts of patients by pair-wise combinations of exclusion criteria were tabulated (Table 3). For

33

each of the criteria, with the exception lung procedures (42%), more than 50% of patients with any

exclusion criteria also had a diagnosis of advanced disease in the first year.

The proportion of excluded patients from each LHIN from the denominator of resected CRC patients was

evaluated, standardizing each LHIN proportion by age and sex against the reference population of Ontario

1996. With the exception of the Southeast LHIN where 100% of patients were excluded (due to alternate

funding plan, see Methods, page 21), the overall crude exclusion rate was 34.9%, with crude rates from

each LHIN ranging from 31.0% to 37.9%. Following adjustment by age and sex, the overall direct-

standardized rates of exclusion was 34.7%, with LHIN rates ranging from 29.9 to 38.2. Excluding the

Southeast LHIN, no LHIN had a significantly different rate of exclusion than others (Table 4).

Baseline characteristics - excluded cohort

Baseline characteristics were also described for the excluded group of patients in Table 5. For the

excluded patients, the mean age at CRC diagnosis was 65.4 years. The group was predominantly male

(57%). Over 75% of these excluded patients had a medium or high Charlson comorbidity classification.

The distribution of patients ranged from 18.5%-21.8% among the five income quintiles. A small number

of patients had missing income quintile (306) or missing LHIN (4) and these patients were eliminated

from future analyses.

Following application of the exclusion criteria, 7,831 patients were eliminated while 12,804 patients were

deemed likely disease-free at the start of the follow-up period (post primary CRC resection year 2 through

year 5), and eligible for postoperative surveillance.

Baseline characteristics – study cohort

There were 12,804 patients in the study cohort, eligible for follow-up at the start of the follow-up period,

and baseline characteristics are described in Table 6. The mean age of the inception cohort was 65.3

years, with 7110 (55.5%) male patients. This cohort consisted of four groups of patients. Group #1 (alive

and had no evidence of disease at the end of the follow-up period) consisted of the majority of patients

(8804, 68.8%). The next largest was group #2 (who had evidence of CRC relapse in the follow-up period,

3316, 25.9%). The final two groups comprised of those who died within the 5 year follow-up period yet

had no evidence of relapse or those whose only evidence of relapse was a cancer-related cause of death in

34

the follow-up period. More than one-third of the entire cohort (5203, 40.6%) had a primary CRC that was

high risk for recurrence (as defined in Methods). The majority of these patients had a low to medium

Charlson comorbidity classification prior to primary CRC resection (79%). Distribution across income

quintiles ranged from 17.9% to 21.5%. Slightly more patients were diagnosed in 1999 to 2001 than 1996

to 1998 (53% vs. 47%).

Table 2: Number of patients meeting each exclusion criteria

Table 3: Pair-wise summary of first year exclusion criteria*

Died

In 1st

yr

Pall.

care

Long

chemo

Late

chemo

Lung

procedure

Liver

procedure

Advanced

disease

Advanced

disease

(n=4609)

2067 1110 535 505 48 936

Liver procedure

(n=1590)

328 199 134 183 7

Lung procedure

(n=113)

9 10 7 13

Late start of

Chemotherapy

(n=804)

148 135 0

Long course of

Chemotherapy

(n=1013)

15 101

Palliative care

consult

(n=1646)

948

Died in first year

(n=3055)

*represents the number of excluded patients having both criteria from row/column; numbers are not

mutually exclusive

N = 7,831 N %

Advanced disease in year 1 4609 58.9%

Liver procedure (incl. biopsy) in year 1 1590 20.3%

Lung procedure (incl.biopsy) in year 1 113 1.4%

Late start of chemotherapy (>120d) 804 18.0%

Prolonged course of chemotherapy (>270d) 1013 22.7%

Palliative care consult 1646 21.0%

Died in year 1 3055 39.3%

35

Table 4. Excluded patients – Direct age-sex standardization to Ontario population 1996

LHIN Excluded All CRC

patients

Crude Rate

(%)

Standardized

rate (%)

95%CI

Erie St. Clair 427 1224 34.9 35.7 28.0-44.7

South West 584 1780 32.8 32.4 26.4-39.3

Waterloo Wellington 343 1076 31.9 31.8 24.6-40.3

Hamilton Niagara

Haldimand Brant

976 2619 37.3 38.0 32.6-44.1

Central West 284 794 35.8 33.9 26.4-42.9

Mississauga Halton 460 1321 34.8 36.3 30.0-43.5

Toronto Central 636 1762 36.1 37.9 31.9-44.8

Central 731 270 33.7 32.1 27.7-37.0

Central East 878 2318 37.9 38.2 32.8-44.1

Champlain 614 1869 32.9 29.9 24.7-35.8

North Simcoe Muskoka 278 764 36.4 35.8 26.1-47.8

North East 454 1465 31.0 32.1 25.6-39.6

North West 165 472 35.0 36.7 25.4-51.4

Overall 6830 19634 34.8 34.7 32.9-36.5

Southeast* 997 997 100.0 100.0

Total** 7827 20631

* patients from Southeast LHIN excluded from standardization

**patients with missing LHIN information excluded from standardization

36

Table 5: Baseline characteristics of excluded cohort

N = 7,831 N %

Age at CRC diagnosis 65.4

(mean)

10.5

(std. dev.)

Male

Female

4460

3371

57.0%

43.0%

Charlson score

Low (0-1)

Medium (2)

High (>2)

1674

2864

3293

21.4%

36.6%

42.1%

Income quintile

1 (poorest)

2

3

4

5 (richest)

Missing

1489

1637

1597

1410

1392

306

19.8%

21.8%

21.2%

18.7%

18.5%

4%

Local Health Integration Network

Erie St. Clair

South West

Waterloo Wellington

Hamilton Niagara Haldimand Brant

Central West

Mississauga Halton

Toronto Central

Central

Central East

Southeast

Champlain

North Simcoe Muskoka

North east

North West

Missing

427

584

343

976

284

460

636

731

878

997

614

278

454

165

4

5.5%

7.5%

4.4%

12.5%

3.6%

5.9%

8.1%

9.3%

11.2%

12.7%

7.8%

3.6%

5.8%

2.1%

0.06%

37

Table 6: Characteristics of study cohort, eligible for postoperative surveillance

N= 12,804 N %

Age at CRC diagnosis 65.3 (mean) 10.5 (std. dev.)

Male

Female

7110

5694

55.5%

44.5%

Colon – high risk

Colon – low risk

Rectum – high risk

Rectum –low risk

3185

5579

2018

2022

24.9%

43.6%

15.8%

15.8%

Alive and no evidence of relapse at 5 years

Evidence of relapse in 5 years

Died but no evidence of relapse at 5 years

Cancer related cause of death only

8804

3316

546

138

68.8%

25.9%

4.3%

1.1%

Charlson score

Low (0-1)

Medium (2)

High (>2)

2771

7353

2680

21.6%

57.4%

20.9%

Local Health Integration Network

Erie St. Clair

South West

Waterloo Wellington

Hamilton Niagara Haldimand Brant

Central West

Mississauga Halton

Toronto Central

Central

Central East

Champlain

North Simcoe Muskoka

Northeast

Northwest

797

1196

733

1643

510

861

1126

1439

1440

1255

486

1011

307

6.2%

9.3%

5.7%

12.8%

4.0%

6.7%

8.8%

11.2%

11.3%

9.8%

3.8%

7.9%

2.4%

Income quintile

1 (poorest)

2

3

4

5 (richest)

2298

2756

2596

2478

2676

17.9%

21.5%

20.3%

19.4%

20.9%

Period of diagnosis

1996-1998

1999-2001

6024

6780

47.1%

52.9%

38

Preliminary analyses

The OHIP billings and CIHI procedure codes for colon resection, liver resection, and lung resection were

examined for agreement in procedure dates. Among primary CRC resections, there was an 85%

agreement between dates of OHIP claims and CIHI procedure codes. For the study cohort, there was a

90% agreement in dates for liver resections, and 86% for lung resections.

Furthermore, the primary diagnosis code was examined in all patient CIHI admissions where a liver or

lung resection was documented, at any point following the primary CRC resection. For all admissions

documenting a procedure of liver resection or destruction from the time of primary CRC resection to five

years afterward, 95% of the ICD-9 or ICD-10 codes for primary diagnosis corresponded to either CRC

(153.x, 154.0, 154.1, C18.0, C18.2-C19.0, C20.0), or secondary neoplasm to the liver (197.7, C787). For

admissions documenting a lung resection or destruction in the same time frame, 92% of all ICD-9 or ICD-

10 primary diagnosis codes corresponded to CRC, secondary neoplasm to the lung (197.0, C780) or

malignant neoplasm of the lung (162.X, C343-C349).

The receipt of adjuvant chemotherapy was characterized for the inception cohort. The most common

interval to the first course of adjuvant chemotherapy was 41 days, with a median of 47 days and an

interquartile range of 38 – 62 days. For the number of doses of chemotherapy, the mode was 30, with a

median of 25 doses. For duration of chemotherapy, the mode was 144 days, with a median of147 days.

39

Objective #1 – Visits and tests

To describe the processes of care that patients receive in the follow-up period, including MD visits and

surveillance tests

Physician visits and tests – Group #1

In the cohort of patients who were both alive and had no evidence of relapse at the end of the follow-up

period (Group #1, n=8,804), the frequency of physician visits, imaging, and endoscopy was examined

over the entire follow-up period. The overall summaries of visit and tests are listed in Table 7. A

minority of patients (3.8%) did not see their general practitioner in the entire follow-up period and the

vast majority visited their general practitioner greater than 5 times in this period (87.3%, median 21,

range 6-213). For medical oncology follow-up, a marked difference was observed for patients with a high

risk versus low risk primary tumour. For low risk patients, the majority (71.3%) did not see a medical

oncologist in follow-up, but most high risk patients saw their medical oncologist greater than 5 times

(55.1%, median 8, range 6-86) (Figure 3).

The patterns of follow-up for general surgeon visits were similar among patients with a rectal or colonic

primary, where a slightly higher frequency of follow-up visits was observed in those patients who had

high risk primary tumours. In colon cancer patients, 39.2% of high risk patients (median 8 visits, range 6-

27) compared with 33.3% of low risk patients (median 8, range 6-38) had greater than 5 physician visits.

In rectal cancer patients, 42.3% of high risk patients (median 8, range 6-53) and 38.2% of low risk

patients (median 8, range 6-47) had greater than 5 visits (Figure 4). Radiation oncology follow-up of

rectal patients appeared to be higher in frequency among those with a high risk primary tumour, where

more than 35% of high patients had 3 or more visits over the follow-up period, while 88.1% of low risk

patients did not see a radiation oncologist at all.

The number of patients in the subgroup who did not undergo a total colectomy was 8,486. In both

patients who had rectal or colonic primaries, more than two thirds of patients received between 2 and 5

endoscopic examinations over all five years after primary CRC resection. A small number in each group

(416 or 7.1% of colon patients, 172 or 6.5% of rectal patients) did not receive any endoscopic evaluation

at all (Figure 5a). A summary of the counts of complete colonoscopies over follow-up years 1-5 in this

population is summarized in Table 5b.

The frequency of body imaging modalities appeared to be different among patients with high risk and low

risk primary tumours. More than one third (38.7%) of the low-risk cohort did not undergo CT imaging or

40

ultrasound in the follow-up period. In contrast, more than half of the high risk group (51.2%) received at

least 3 imaging tests over this time period (Figure 6). The imaging modalities of thorax CT and MR of

the abdomen or pelvis were rarely used, where for each modality greater than 89% of patients had zero

tests over follow-up years 2-5.

41

Table 7: Total visits and tests over follow-up years 2-5 in patients alive at 5 years without evidence of disease relapse

N=8804 None 1 2 3-5 >5

MD Visits

General Practitioner

High risk (N=3293)

Low risk (N=5511)

336 (3.8%) 104 (3.2%) 232 (4.2%)

152 (1.7%) 54 (1.6%) 98 (1.8%)

144 (1.6%) 61 (1.9%) 83 (1.5%)

487 (5.5%) 218 (6.6%) 269 (4.9%)

7685 (87.3%) 2856 (86.7%) 4829 (87.6%)

Medical Oncologist

High risk

Low risk

4464 (50.7%) 536 (16.3%) 3928 (71.3%)

518 (5.9%) 174 (5.3%) 344 (6.2%)

304 (3.5%) 140 (4.3%) 164 (3.0%)

1010 (11.5%) 627 (19.0%) 383 (6.9%)

2508 (28.5%) 1816 (55.1%) 692 (12.6%)

General Surgeon (colon, N = 6107)

High risk (N=2034)

Low risk (N=4073)

1197 (19.6%) 360 (17.7%) 837 (20.5%)

575 (9.4%) 181 (8.9%) 394 (9.7%)

597 (9.8%) 177 (8.7%) 420 (10.3%)

1583 (25.9%) 519 (25.5%) 1064 (26.1%)

2155 (35.3%) 797 (39.2%) 1358 (33.3%)

General Surgeon (rectal, N=2697)

High risk (N = 1259)

Low risk (N = 1438)

446 (16.5%) 190 (15.1%) 256 (17.8%)

235 (8.7%) 114 (9.1%) 121 (8.4%)

243 (9.0%) 103 (8.2%) 140 (9.7%)

692 (25.7%) 320 (25.4%) 372 (25.9%)

1081 (40.1%) 532 (42.3%) 549 (38.2%)

Radiation Oncologist

(rectal only, N=2697)

High risk (1259)

Low risk (N=1438)

1925 (71.4%)

658 (52.3%) 1267 (88.1%)

115 (4.2%)

85 (6.8%) 30 (2.1%)

83 (3.1%)

65 (5.2%) 18 (1.3%)

290 (10.8%)

234 (18.6%) 56 (3.9%)

284 (10.5%)

217 (17.2%) 67 (4.7%)

Test

Endoscopy * (colon, N = 5833)

High risk (N=1926)

Low risk (N=3907)

416 (7.1%) 53 (2.8%) 363 (9.3%)

725 (12.4%) 177 (9.2%) 548 (13.9%)

1528 (26.2%) 539 (28.0%) 989 (25.3%)

2783 (47.7%) 1017 (52.8%) 1766 (45.2%)

381 (6.5%) 140 (7.3%) 241 (6.2%)

Endoscopy * (rectum, N = 2653)

High risk (N=1242)

Low risk (N=1411)

172 (6.5%) 56 (4.5%)

116 (8.2%)

324 (12.2%) 145 (11.7%)

179 (12.7%)

574 (21.6%) 290 (23.3%)

284 (20.1%)

1210 (45.6%) 593 (47.7%)

617 (43.7%)

373 (14.1%) 158 (12.7%)

215 (15.2%)

Body imaging ** (N=8804)

High risk

Low risk

2760 (31.3%) 625 (19.0%) 2135 (38.7%)

1693 (19.2%) 505 (15.3%) 1188 (21.6%)

1258 (14.3%) 479 (14.5%) 779 (14.1%)

2211 (25.1%) 1105 (33.6%) 1106 (20.1%)

882 (10.0%) 579 (17.6%) 303 (5.5%)

Thorax CT (N=8804)

High risk

Low risk

7892 (89.6%) 2816 (85.5%) 5076 (92.1%)

598 (6.8%) 295 (9.0%) 303 (5.5%)

171 (1.9%) 94 (2.9%) 77 (1.4%)

134 (1.5%) 80 (2.4%) 54 (1.0%)

<13 (<0.3%) 8 (0.2%) <5 (<0.1%)

Body MR (N=8804)

High risk

Low risk

8544 (97.0%) 3138 (95.3%)

5406 (98.1%)

<5 (<0.02%) 0 (0%)

<5 (<0.02%)

0 (0.0%) 0 (0.0%)

0 (0.0%)

252 (2.9%) 151 (4.6%)

101 (1.8%)

7 (<0.3%) <5 (<0.2%)

<5 (<0.02%)

Percentages reflect row totals

* colonoscopy, flexible and rigid sigmoidoscopy; includes year 1 of follow-up but excludes patients with total colectomy

** ultrasound abdomen, CT abdomen/pelvis

42

Figure 3. Number of medical oncology follow-up visits over follow-up years 2-5 for low and high

risk CRC patients, among those patients with no evidence of relapse at the end of the follow-up

period.

Figure 4. Number of general surgeon follow-up visits over follow-up years 2-5 for low/high risk

colon and rectal patients, among those patients with no evidence of relapse at the end of the follow-

up period.

43

Figure 5a. Number of endoscopy tests in follow-up years 1-5 among patients with no evidence of

relapse, who did not receive a total colectomy at the end of the follow-up period.

Figure 5b. Number of colonoscopies to the terminal ileum or cecum in follow-up years 1-5 among

patients with no evidence of relapse, who did not receive a total colectomy at the end of the follow-

up period.

44

Figure 6. Number of body imaging tests in follow-up years 2-5 for patient s with no evidence of

relapse at the end of the follow-up period.

Polypectomies with endoscopies and complete colonoscopies

Among patients who received an endoscopic examination in the follow-up period and did not have a total

colectomy, the rate of polypectomy per endoscopy was determined. By the end of the follow-up period,

there were a total of 25,888 endoscopic examinations in this group, where 5,412 were accompanied with a

billing claim for polypectomy, giving a polypectomy rate of 20.9%.

For the same population and follow-up period, there were 20,718 claims for colonoscopy, where 16,324

were accompanied with a claim for assessment of the cecum or terminal ileum. This represented a

complete colonoscopy rate of 78.8%.

Physician visits and tests – Group #2

The frequency of physician visits and tests were examined for group #2 (patients who had evidence of

relapse in the follow-up period). Due to the varying time intervals until the time of the first evidence of

relapse, follow-up frequencies were expressed with the denominator of 6 months of follow-up (Table 8).

While examining visits and tests up to 60 days before the first evidence of relapse, family physician visits

were the most frequent, with a similar frequency among high and low risk patients. Follow-up with

general surgery was also similar among high and low risk patients with either colonic or rectal primaries.

45

However, for medical oncology follow-up visits, high risk patients (range 0.9-1.2 visits per 6 months) had

at least twice the frequency of follow-up visits than low risk patients (0.3-0.5 visits per 6 months).

Endoscopy frequencies were similar among low risk and high risk patients, however, it was noted that for

patients that relapsed in year 2, the cumulative frequency was at least twice higher than that of patients

who relapsed in years 3-5. When only including visits and tests up to 90 days prior to the first evidence

of relapse, the observed patterns in frequencies were similar (Table 8).

Table 8. Mean number of MD visits or tests per 6 months of follow-up

60 day censoring period 90 day censoring period

Year 2

relapses

Year 3

relapses

Year4

relapses

Year 5

relapses

Year 2

relapses

Year 3

relapses

Year4

relapses

Year 5

relapses

GP

High Risk 1.8 2.7 2.7 2.8 1.2 2.4 2.5 2.7

Low Risk 2.1 3.2 3.2 2.8 1.4 2.9 3.1 2.7

GS (colon)

High Risk 0.7 0.9 0.7 0.6 0.5 0.8 0.6 0.6

Low Risk 0.8 0.7 0.7 0.6 0.5 0.7 0.7 0.6

GS (rectal)

High Risk 0.8 1 0.9 0.8 0.8 1 0.9 0.8

Low Risk 0.9 0.9 1 0.6 0.6 0.8 0.9 0.6

Med Onc

High Risk 0.9 1.2 1.2 0.9 0.6 1.1 1.1 0.9

Low Risk 0.4 0.5 0.5 0.3 0.3 0.4 0.4 0.3

Rad Onc

(rectal)

High Risk 0.2 0.5 0.4 0.3 0.2 0.4 0.4 0.3

Low Risk 0.3 0.7 0.3 0.3 0.2 0.3 0.3 0.2

Endoscopy

(colon)

High Risk 1.6 0.6 0.4 0.4 1.4 0.6 0.4 0.4

Low Risk 1.8 0.5 0.4 0.4 1.6 0.5 0.4 0.4

Endoscopy

(rectal)

High Risk 1.9 0.6 0.5 0.4 1.6 0.6 0.5 0.4

Low Risk 2.3 0.7 0.5 0.3 2.2 0.7 0.5 0.3

Body Imaging

High Risk 0.7 0.7 0.5 0.5 0.4 0.6 0.6 0.5

Low Risk 0.5 0.4 0.3 0.3 0.3 0.4 0.3 0.3

GP, general practitioner; GS, General Surgeon

46

Model #1 - Endoscopy

The first exploratory analysis was to examine factors associated with receiving at least one endoscopy in

years 1 through 5 of follow-up, among patients who did not receive a total colectomy, and were alive with

no evidence of relapse. Diagnosis from 1999 to 2001 (OR 1.36, 95%CI 1.15-1.61) was positively

associated with endoscopic examination, while increasing age at diagnosis (OR 0.95, 95%CI 0.94-0.96)

and higher Charlson comorbidity classification (OR 0.70, 95%CI 0.54-0.90) had a negative association.

Among income quintiles, it appeared that patients in the fourth (OR 1.51, 95%CI 1.14-2.00) and fifth (OR

1.50, 95%CI 1.13-1.98) highest income quintiles had a significantly higher likelihood of receiving at least

one endoscopic examination as compared to patients in the first (referent) quintile (Table 9). Non

significant factors included sex, urban or rural place of residence, and colon or rectal primary.

Table 9. Model #1. Univariate and multivariable analysis for having at least one endoscopic

examination in follow-up years 1-5, among patients alive and no evidence of relapse at 5 years, who

did not receive a total colectomy

Univariate statistics Multivariable model

N=8486 No endoscopy

(n=588)

>=1

endoscopy (n=7898)

P OR 95%CI P

Age (mean) 69.5 64.5 <0.01 0.95 0.94-0.96 <0.01

Male 308 (6.8%) 4228 (93.2%) 0.59 Referent

Female 280 (7.1%) 3670 (92.9%) 1.01 0.85-1.20 0.91

Income quintile

1 (poorest)

125 (9.5%)

1341 (91.5%)

<0.01

Referent

2 152 (9.4%) 1668 (91.6%) 1.04 0.81-1.33 0.79

3 121 (7.1%) 1596 (92.9%) 1.18 0.91-1.54 0.21

4 93 (5.5%) 1591 (94.5%) 1.51 1.14-2.00 <0.01

5 (richest) 98 (5.5%) 1701 (94.5%) 1.50 1.13-1.98 <0.01

Charlson classification

Low (0-1) 122 (6.5%)

1767 (93.5%)

<0.01

Referent

Medium (2) 319 (5.2%) 4859 (94.8%) 1.04 0.84-1.30 0.71

High (>2) 147 (10.4%) 1272 (89.6%) 0.70 0.54-0.90 <0.01

Diagnosed 1996-1998 304 (8.0%) 3502 (92%) <0.01 Referent

Diagnosed 1999-2001 284 (6.1%) 4396 (93.9%) 1.36 1.15-1.61 <0.01

Urban 492 (6.8%) 6702 (93.2%) Referent

Rural 96 (7.4%) 1196 (92.6%) 0.44 0.99 0.79-1.25 0.94

Colon primary 416 (7.1%) 5417 (92.9%) 0.28 1.06 0.79-1.25 0.56

Rectal primary 172 (6.5%) 2481 (93.5%) Referent

47

Model #2 – Body imaging

The outcome of receiving at least one body imaging modality was explored among all patients alive and

had no evidence of relapse in the follow-up period (group #1) (Table 10). Due to a significant interaction

between high/low risk tumour and both general surgery and medical oncology follow-up, this model was

stratified for high and low risk primary CRC tumours. Among low risk patients (N=5511), factors

associated with the receipt of at least one body imaging modality included visiting the general surgeon

(OR2.47, 95%CI 2.16-2.84) or medical oncologist (OR 1.69, 95%CI 1.48-1.92) at least once. The lone

factor which had a negative association with at least one body imaging modality was rural place of

residence (OR 0.8, 95%CI 0.7-0.9). All other factors had no statistical association with the outcome,

including age at diagnosis, sex, income quintile, Charlson comorbidity score, or period of diagnosis. In

the model for high risk patients (N=3293), at least one general surgeon (OR 1.83, 95%CI 1.48-2.27) or

medical oncologist (OR 1.88, 95%CI 1.52-2.34) visit was also positively associated with at least one body

imaging modality. Recent period of diagnosis (1999-2001) was also positively associated with the

outcome (OR 1.32, 95%CI 1.10-1.58), and rural place of residence was not significant (OR 0.95, 95%CI

0.74-1.22). Other covariates were non-significant in this model.

48

Table 10. Model #2. Univariate and multivariable analysis for having at least one body imaging modality in follow-up years 2-5, among

patients alive and no evidence of relapse at 5 years, stratified by high and low risk primary

Low risk N = 5511 High risk (N=3293)

Univariate statistics Multivariable model Univariate statistics Multivariable model

No body

imaging tests (N=2135)

>=1 body

imaging test (N=3376)

P OR 95%CI P No body

imaging tests (N=625)

>=1 body

imaging test (N=2668)

P OR 95%CI P

Age at diagnosis 66.4* 66.8* 0.27 1.00 0.99-1.00 0.47 61.1* 63.3* <0.01 0.98 0.97-0.99 <0.01

Male 1005 (35.1%) 1860 (64.9%) 0.27 Referent 371 (19.9%) 1493 (80.1%) 0.12 Referent

Female 1130 (42.7%) 1516 (57.3%) 1.07 0.96-1.19 0.25 254 (17.8%) 1175 (82.2%) 1.19 0.99-1.43 0.06

Income quintile

1 (poorest)

377 (37.0%)

642 (63.0%)

0.74

Referent

92 (18.3%)

411 (81.7%)

0.17

Referent

2 477 (38.6%) 759 (61.4%) 0.94 0.79-1.12 0.51 125 (19.5%) 517 (80.5%) 0.91 0.67-1.24 0.55

3 428 (39.2%) 663 (60.8%) 0.91 0.76-1.09 0.29 148 (21.4%) 542 (78.6%) 0.81 0.60-1.09 0.16

4 403 (38.9%) 632 (61.1%) 0.90 0.75-1.08 0.23 138 (19.4%) 574 (80.6%) 0.90 0.67-1.21 1.49

5 (richest) 450 (39.8%) 680 (60.2%) 0.86 0.72-1.03 0.11 122 (16.4%) 624 (83.6%) 1.14 0.84-1.55 0.39

Charlson

classification

Low (0-1)

511 (39.6%)

780 (60.4%)

0.74

Referent

134 (19.8%)

544 (80.2%)

0.66

Referent

Medium (2) 1309 (38.4%) 2103 (61.6%) 1.03 0.90-1.17 0.72 361 (18.5%) 1594 (81.5%) 1.05 0.84-1.32 0.66

High (>2) 315 (39.0%) 493 (61.0%) 1.03 0.85-1.24 0.80 130 (19.7%) 530 (80.3%) 1.12 0.85-1.48 0.43

GS: 0 visits 614 (56.2%) 479 (43.8%) <0.01 Referent 152 (27.6%) 398 (72.4%) <0.01 Referent

GS: 1 or more visits 1521 (34.4%) 2897 (65.6%) 2.47 2.16-2.84 <0.01 473 (17.2%) 2270 (82.8%) 1.83 1.48-2.27 <0.01

MO: 0 visits 1651 (42.0%) 2277 (58.0%) <0.01 Referent 153 (28.5%) 383 (71.5%) <0.01 Referent

MO: 1 or more visits 484 (30.6%) 1099 (69.4%) 1.69 1.48-1.92 <0.01 472 (17.1%) 2285 (82.9%) 1.88 1.52-2.34 <0.01

Diagnosed 1996-1988 1025 (40.6%) 1500 (59.4%) <0.01 Referent 300 (21.1%) 1120 (78.9%) <0.01 Referent

Diagnosed 1999-2001 1110 (37.2%) 1876 (62.8%) 1.11 0.99-1.24 0.07 325 (17.4%) 1548 (82.6%) 1.32 1.10-1.58 <0.01

Urban 1776 (38.2%) 2878 (61.8%) 0.04 Referent 531 (18.9%) 2285 (81.1%) 0.66 Referent

Rural 359 (41.9%) 498 (58.1%) 0.76 0.65-0.88 <0.01 94 (19.7%) 383 (80.3%) 0.95 0.74-1.22 0.70

Colon primary 1557 (38.2%) 2516 (61.8%) 0.19 1.10 0.97-1.25 0.16 404 (19.9%) 1630 (80.1%) 0.10 0.83 0.69-1.00 0.05

Rectal primary 578 (40.2%) 860 (59.8%) Referent 221 (17.6%) 1038 (82.4%) Referent

*mean age of group; GS, General Surgeon; MO, Medical oncologist

49

Objective #2 - Treatment for relapse

To describe the proportion of patients that had evidence of disease relapse, who receive surgical

treatment in the management of relapse, with stratification by LHIN and income quintile

Overall, 3316 patients had some evidence of disease relapse within the 5 year follow-up period (group

#2). These patients were summarized by both primary site and risk of the primary tumor for recurrence,

and stratifying by year of relapse (Table 11). The number of patients relapsing decreased over the follow-

up years, with 1428 (43.1%) with evidence of relapse in year 2, 954 (28.8%) in year 3, 557 (16.8%) in

year 4, and 377 (11.4%) in year 5. Overall, a slightly higher proportion of rectal patients comprised this

group as compared to baseline (35% vs 31.5%). Among patient with colonic primaries, 50% of relapses

had a high risk primary, while for rectal patients, 61% of relapses had high risk primaries. More relapsed

colon cancer patients in years 3-5 were classified as having a low risk primary (51-61%), however for

rectal patients, the majority of relapsed patients in each follow-up year were classified as having a high

risk primary.

Table 11. Relapse based on site and high/low risk status of primary, by year of relapse

Year 2

relapses

Year 3

relapses

Year 4

relapses

Year 5

relapses

Total

# relapsed in year 1428 954 557 377 3316

Colon primary (n, % of year) 925 (65%) 624 (65%) 358 (64%) 246 (65%) 2153 (65%)

High risk (n, % colon) 526 (57%) 306 (49%) 139 (39%) 100 (43%) 1071 (50%)

Low Risk (n, % colon) 399 (43%) 318 (51%) 219 (61%) 146 (57%) 1082 (50%)

Rectal primary (n, % of year) 503 (35%) 330 (35%) 199 (36%) 131 (35%) 1163 (35%)

High risk (n, % rectum) 307 (61%) 212 (64%) 120(60%) 70 (53%) 709 (61%)

Low risk (n, %rectum) 196 (39%) 118 (36%) 79 (40%) 61 (47%) 454 (39%)

Treatment of disease relapse – Income quintiles

When the cohort was stratified by income quintiles (Table 12), the proportion of relapsed patients were

not statistically different (p=0.50), ranging from 25.0% in quintile 5 to 26.8% in quintile 1. There

appeared to be a decreasing proportion of relapsed patients with higher income quintiles, however, this

trend was not statistically significant (p=0.10, two-sided test). When considering surgical treatment as a

whole (lung and liver resection), there was a significant difference between income quintiles (p<0.01) and

a significant trend (p<0.01) for increasing proportions of relapse surgery with higher income quintile. For

the proportions treated by liver resections only, there was no statistical difference (p=0.07) or trend

(p=0.13) among income quintiles. Regarding lung resections for disease relapse, there was a statistically

50

significant difference between income quintiles (p<0.01), with a significant trend for increasing

proportion of patients to receive a potentially curative lung resection with each higher quintile (p<0.01).

The proportions ranged from 2.3% in quintile 1 to 6.9% in quintile 5 (EQ 3.0). However, there was no

statistical difference in those receiving chemotherapy (p=0.46), ranging from 40.9% to 49.9% (EQ 1.2)

with a non significant trend test (p=0.13).

Treatment of disease relapse – LHINs

The analysis was stratified by individual LHIN to both determine the proportion of patients who had

disease relapse, and also who received medical (chemotherapy) or surgical (lung or liver resection)

treatment (Table 13). There were no statistical differences in the proportion of patients who experienced

disease relapse in the follow-up period among the different LHINs (range 24.2% to 28.9%, p=0.34).

When examining individual treatment modalities, there also was no overall statistical difference for the

proportion of relapsed patients who received a liver (p=0.63) or lung (p=0.61) resection, or chemotherapy

(p=0.09) among LHINs. Excluding LHINs with cell counts of less than 5, the range of proportions

among LHINs to receive a liver resection was from 5.2% to 8.8% (EQ 1.7), for lung resection 3.1% to

6.2% (EQ 2.0) and for chemotherapy 35.5% to 55.5% (EQ 1.6).

LHINs performing liver and lung resections

A further analysis was performed examining the LHIN where the patient resided, and the LHIN where the

patient received a potentially curative surgical resection. The LHINs with the highest volume of liver

resections were Toronto Central (124, 53.0% of all liver resections), Southwest (40, 17.1%), Hamilton

Niagara (35, 15.0%) and Champlain (17, 7.3%). The same LHINs also provided the highest volume of

lung resections; Toronto Central (54, 37.9% of all lung resections), Hamilton Niagara (27, 18.6%),

Southwest (15, 10.3%), and Champlain (10, 6.9%) (Table 14).

Treatment of disease relapse – Survival

Univariate survival analyses were performed among different groups of patients with evidence of relapse.

For those who received a liver resection, the 5 year OS was 45% with a median survival of 52.5 months ,

compared to those not receiving a liver resection who had a 5 year OS 15% and median survival 10

51

months (p<0.01). Patient who received a lung resection (5 year OS 48%, median survival 58 months)

also had a significantly longer survival than those without a lung resection (5 year OS 15%, median

survival 11 months) (p<0.01). Comparing patients who had evidence of relapse but did not receive lung

or liver resection, those who received palliative chemotherapy had a significantly longer median survival

than those without palliative chemotherapy (16 months vs. 4 months, p<0.01).

52

Table 12: Relapse rates and treatments for relapse, by income quintiles

Quintile

(N=12,804)

N #

Relapsed

at 5 yrs

%

overall

Liver

resection

%

overall

% of

relapsed

pts

Lung

resection

%

overall

% of

relapsed

pts

Chemo %

overall

% of

relapsed

pts

1 (poorest) 2298 616 26.8% 35 1.5% 5.7% 14 0.6% 2.3% 252 11.0% 40.9%

2 2756 721 26.2% 43 1.6% 6.0% 20 0.7% 2.8% 310 11.2% 43.0%

3 2596 687 26.5% 60 2.3% 8.7% 33 1.3% 4.8% 298 11.5% 43.4%

4 2478 623 25.1% 38 1.5% 6.1% 30 1.2% 4.8% 311 12.6% 49.9%

5 (richest) 2676 669 25.0% 58 2.2% 8.7% 46 1.7% 6.9% 318 11.9% 47.5%

% relapsed among income quintiles, p=0.50; % liver resections, p=0.7; %lung resections p<0.01; % chemotherapy, p=0.46

Table 13: Relapse rates and treatments for relapse, by LHIN of residence

LHIN

(N=12,804)

N #

Relapse

at 5 yrs

%

overall

Liver

resection

%

overall

% of

relapsed

pts

Lung

resection

%

overall

% of

relapsed

pts

Chemo %

overall

% of

relapsed

pts

(1) Erie St. Clair 797 195 24.5% 15 1.9% 7.7% <5 <1.0% <3% 88 11.0% 45.1%

(2) South West 1196 317 26.5% 28 2.3% 8.8% 12 1.0% 3.8% 144 12.0% 45.4%

(3) Waterloo

Wellington

733 200 27.3% 15 2.0% 7.5% 8 1.1% 4.0% 89 12.1% 44.5%

(4) Hamilton Niagara

Haldimand Brant

1643 475 28.9% 31 1.9% 6.5% 24 1.5% 5.1% 218 13.3% 45.9%

(5) Central West 510 128 25.1% 11 2.2% 8.6% 6 1.2% 4.7% 71 13.9% 55.5%

(6) Mississauga Halton 861 217 25.2% 16 1.9% 7.4% 11 1.3% 5.1% 103 12.0% 47.5%

(7) Toronto Central 1126 291 25.8% 25 2.2% 8.6% 13 1.2% 4.5% 107 9.5% 36.8%

(8) Central 1439 348 24.2% 27 1.9% 7.8% 20 1.4% 5.7% 182 12.6% 52.3%

(9) Central East 1440 358 24.9% 19 1.3% 5.3% 15 1.0% 4.2% 161 11.2% 45.0%

(11) Champlain 1255 324 25.8% 17 1.4% 5.2% 10 0.8% 3.1% 132 10.5% 40.7%

(12) North Simcoe

Muskoka

486 129 26.5% <5 <1.0% <4.0% 8 1.6% 6.2% 50 10.3% 38.8%

(13) North East 1011 258 25.5% 20 2.0% 7.8% 9 0.9% 3.5% 117 11.6% 45.3%

(14) North West 307 76 24.8% 6 2.0% 7.9% <5 <1.5% <6.0% 27 8.8% 35.5%

% relapsed among LHINs, p=0.34; % liver resections, p=0.63; % lung resections, p=0.61; % chemotherapy, p=0.09

53

Table 14: LHIN of institution performing liver and lung resections

LHIN # Liver

resection

% of total

liver

resections

# Lung

resection

% of total

lung

resections

(1) Erie St. Clair <5 <2.0% 0 0.0%

(2) South West 40 17.1% 15 10.3%

(3) Waterloo Wellington <5 <2.0% <5 <4.0%

(4) Hamilton Niagara

Haldimand Brant

35 15.0% 27 18.6%

(5) Central West 0 0.0% <5 <4.0%

(6) Mississauga Halton <5 <2.0% <5 <4.0%

(7) Toronto Central 124 53.0% 54 37.9%

(8) Central <5 <2.0% <5 <4.0%

(9) Central East <5 0.9% <5 <4.0%

(11) Champlain 17 7.3% 10 6.9%

(12) North Simcoe

Muskoka

0 0.0% <5 <4.0%

(13) North East <5 <2.0% 6 4.1%

(14) North West 0 0.0% <5 <4.0%

Missing <5 <2.0% 6 4.2%

Total 234 143

54

Model #3 – Surgical resection for relapse

The third exploratory analysis was to determine factors associated with surgical resection (lung or liver

resection) for relapsed disease, among patients who had evidence of relapse in the follow-up period

(group #2). The total number of patients with the outcome was 353 in this analysis, due to 24 patients

recorded as having received both a liver and lung resection. The initial analysis was performed censoring

MD visits and tests within 60 days prior to the first evidence of relapse (Table 15). Factors that were

negatively associated with the receipt of potentially curative surgery included increasing age (OR 0.97,

95% 0.96-0.98), increased Charlson comorbidity (overall p < 0.01), and medical oncology follow-up

frequency (OR 0.85, 95%CI 0.75-0.97). Factors positively associated with receiving surgical treatment

included being in the third (OR 1.63, 95%CI 1.11-2.39) or fifth income quintile (OR 1.95, 95%CI 1.34-

2.84), having a high risk primary tumour (OR 1.70, 95%CI 1.31-2.22), more recent period of diagnosis

(OR 1.33, 95%CI 1.06-1.67), and high frequency of body imaging (OR 1.27, 95%CI 1.07-1.49). To

assess sensitivity of covariates in this model to the length of the censoring period prior to the first

evidence of relapse, this analysis was repeated with a censoring period of 0, 30, 90 and 120 days. The

only variable sensitive to these changes was that of body imaging frequency, where increasing frequency

was significantly associated with surgical resection if the censoring period was 0-60 days (OR 1.3).

However, if tests and visits were censored 90 or 120 days prior to first evidence of relapse, this variable

no longer had significant association with surgical resection of disease relapse (OR 1.1-1.2,Figure 10).

55

Table 15. Model #3. Univariate and multivariable analysis for receiving surgical (lung or liver)

resection for CRC relapse, among patients who had evidence of disease relapse in follow-up period

N = 3316 Univariate statistics Multivariable model

No relapse

surgery (N=2963)

Relapse

surgery (N=353)

P OR 95%CI P

Age at relapse 66.3* 61.7* <0.01 0.97 0.96-0.98 <0.01

Male 1731 (89.3%) 208 (10.7%) 0.86 Referent

Female 1232 (89.5%) 145 (10.5%) 0.96 0.76-1.21 0.71

Income quintile

1 (poorest)

569 (92.4%)

47 (7.6%)

<0.01

Referent

2 661 (91.7%) 60 (8.3%) 1.08 0.72-1.62 0.71

3 604 (87.9%) 83 (12.1%) 1.63 1.11-2.39 0.01

4 557 (89.4%) 66 (10.6%) 1.27 0.85-1.91 0.23

5 (richest) 572 (85.5%) 97 (14.5%) 1.95 1.34-2.84 <0.01

Charlson

classification**

Low (0-1)

1139 (85.9%)

187 (14.1%)

<0.01

Referent

Medium (2) 864 (90.5%) 91 (9.5%) 0.56 0.43-0.74 <0.01

High (>2) 960 (92.8%) 75 (7.2%) 0.40 0.30-0.54 <0.01

High risk primary 1539 (86.5%) 241 (13.5%) <0.01 1.70 1.31-2.22 <0.01

Low risk primary 1424 (92.7%) 112 (7.3%) Referent

GS visit frequency 0.78† 0.94† 0.01 1.10 0.99-1.23 0.07

MO visit frequency 0.74† 0.76† 0.70 0.85 0.75-0.97 0.02

Body imaging frequency 0.57† 0.70† <0.01 1.27 1.07-1.49 <0.01

Diagnosed 1996-1998 1534 (90.9%) 154 (9.1%) <0.01 Referent

Diagnosed 1999-2001 1429 (87.8%) 199 (12.2%) 1.33 1.06-1.67 0.02

Urban 2461 (89.1%) 300 (10.9%) 0.36 Referent

Rural 502 (90.5%) 53 (9.5%) 0.96 0.70-1.32 0.80

Colon primary 1943 (90.2%) 210 (9.8%) 0.02 0.87 0.69-1.10 0.25

Rectal primary 1020 (87.7%) 143 (12.3%) Referent

*mean age of group; **Indexed at time of first evidence of relapse; † mean frequency per 6 months;

GS, general surgeon; MO, medical oncologist

56

Figure 7. Sensitivity analysis: Forest plot of odds ratios and 95% confidence intervals of body

imaging frequency, depending on censoring interval prior to first evidence of relapse

57

Secondary Objective: Comparison with primary chart reviewed cohort

Of the 513 patients from the primary chart reviewed cohort, 353 (68.8%) were matched to the study

cohort prior to year-one exclusions. For the 160 patients that did not match to the study cohort,

examination of their OCR record indicated that 56 patients had multiple primaries; 44 patients did not

meet the criteria of diagnosis date, diagnosis code, or histology code; 6 patients did not meet age criteria;

44 patients had a colorectal resection greater than 14 days prior to, or 120 days following the diagnosis

date, and 11 patients had a procedure code that was not defined as a colorectal resection.

Of the 353 patients who matched to the study cohort, 118 were excluded from analysis by the primary

chart review due to being restaged with metastatic disease, or relapsing within a year of colorectal

resection, while 235 were eligible for follow-up. According to year-one exclusions applied in the

administrative data, 106 patients were excluded while 247 of these patients were considered eligible for

follow-up. A comparison of these two classifications is summarized in Table 16. For the exclusion of

patients due to probable relapse prior to the start of the follow-up period, the sensitivity was 58.5% and

the specificity was 84.2%. The positive predictive value was 80.2% while the negative predictive value

was 65.1%. For the 49 patients that were false negatives (excluded in the primary chart review, but

included in the present study), 44 patients were later classified as having had relapse of disease. The

interval from the date of resection to the date of detection of relapse ranged from 380 to 1288 days, with a

median of 531 days. Out of the 37 patients that were false positives (eligible for follow-up in the primary

chart review but excluded in the present study), 12 had a diagnosis of advanced disease, 7 had a late

course of chemotherapy, 3 had a long course of chemotherapy, 6 had a palliative care consult, and 6 had a

liver procedure. Three of the false positives were excluded due to missing mean neighborhood income

quintile.

The 198 patients correctly identified as being eligible for follow-up were examined for the accuracy of

classification of relapse. From the chart reviewed data, 40 patients relapsed while the remaining 158

patients did not relapse. According to the administrative data algorithm used to classify relapse, 46

patients were classified as relapse, while 152 patients were considered to have no evidence of disease.

The comparison of this classification was compared to the reference standard by chart review in Table 17.

For this cohort of patients, the sensitivity of relapse detection was 87.5%, while the specificity was

93.0%. The positive predictive value was 76.1% while the negative predictive value was 96.7%. The

location of relapse and whether or not it was resected was summarized for the 5 false negatives in Table

18. For the 11 false positives, 4 patients had a diagnosis of advanced disease in the follow-up period, 2

58

patients received a liver biopsy, 2 received a lung biopsy, 3 received chemotherapy and 5 received a

palliative care consult. None of the false positives received a liver or lung resection.

For the overall group, the accuracy of the algorithm for classifying patients as having relapsed over the

entire follow-up period (years 1-5) was assessed (Table 19). From the chart reviewed data, 158 patients

relapsed in years 1-5, while the remaining 195 patients did not relapse. According to the administrative

data algorithm used to classify relapse, 196 patients were classified as relapse, while 157 patients were

considered to have no evidence of disease. When examining this entire follow-up period without first

finding a group of patients eligible for follow-up at year 2, the algorithm for detecting relapse yielded a

sensitivity of 93.7%, specificity of 75.4%, positive predictive value of 75.5% and negative predictive

value of 93.6%.

In the chart reviewed data, 134 patients had either their pathologic or clinical stage recorded. Of these

patients, 33 colon cancer and 28 rectal cancer patients had stage II disease; 40 colon cancer and 33 rectal

cancer patients had stage III disease. Among stage II patients, 21 (63.6%) colon cancer and 19 (67.9%)

rectal cancer patients were classified as high risk. Among stage III patients, 38 (95.0%) colon cancer and

31 (93.9%) rectal cancer patients were classified as high risk.

59

Table 16. 2x2 Frequency table for eligibility for follow-up using administrative data compared to

the reference standard of primary chart review

Status from primary chart review

(reference standard)

Administrative data

algorithm

Excluded due to

metastases, early relapse

Eligible for follow-up

Excluded 69 37 106

Eligible for follow-up 49 198 247

118 235 Total: 353 patients

Table 17. 2x2 Frequency table for relapse detection using administrative data compared to the

reference standard of primary chart review



Administrative data

algorithm

No relapse Relapse

No relapse 147 5 152

Relapse 11 35 46


Table 18. Location of relapse and surgery for false negatives (relapsed by chart review, but not

detected in administrative data)

Patient Follow-up year of

relapse

Location of relapse Surgical resection?

1 4 Local Yes

2 4 Lung No

3 2 Lymph nodes Yes

4 5 Intraabdominal No

5 4 Local, lung No

Table 19. 2x2 Frequency table for detection of relapse over all follow-up years 1-5 using

administrative data, compared to the reference standard of primary chart review



Administrative data

algorithm

No relapse Relapse in years 1-5

No relapse 147 10 157

Relapse in years 1-5 48 148 196


60

Discussion

This study is the first to provide a population-based description of the processes of care of Ontario CRC

patients following their potentially curative resection. Using administrative databases of hospital

discharge abstracts and physician billings, it was possible to examine the health services that patients

received in the follow-up period. It is important that this initial study is performed in order to further

evaluate the current level of care that CRC patients receive, and identify potential disparities in the

delivery of health services. Following this, hypotheses may be proposed in order to further evaluate

mechanisms behind any differences in health care and how to address them. Several difficult challenges

were addressed, including how to measure test frequency, accounting for diagnostic versus surveillance

testing, using an algorithm to identify relapsed patients, and validating this algorithm on a small cohort of

primary chart reviewed patients. The results of the exploratory analyses suggested several hypotheses for

future studies to investigate, including potential factors associated with the receipt of colonoscopy and

body imaging in the follow-up period, and factors that may be associated with receiving surgery for

relapse.

Cohort formation

In order to identify a cohort of patients who received a potentially curative CRC resection and were

eligible for follow-up, a series of exclusion criteria were applied over events in the first year after

resection. This also allowed for the completion of any adjuvant treatment. The study years 1996-2001

were chosen for CRC diagnosis in order to examine as many patients as possible with complete five year

follow-up data, yet not include patients from too remote a time period. From the initial cohort of 20,635

patients who had a CRC diagnosis and resection within 120 days, 7,831 were excluded based on criteria

over the first year after resection. This number of excluded patients has face validity, as approximately

20-30% of CRC patients will present with stage IV disease (19, 93, 126), and additional relapses are

detected in the first year after resection. It is possible that a group of patients who were cured of their

primary disease were among the excluded group. For example, some patients who were free of disease

but received a liver biopsy, or had the start of adjuvant chemotherapy legitimately delayed, were excluded

due to the conservative nature of the exclusion criteria. However, this conservative approach was deemed

appropriate, in order to reduce contamination of the study cohort with patients who were not disease free.

Among the study cohort, the receipt of adjuvant chemotherapy was used as a proxy to represent primary

CRC tumours with a high risk of recurrence. This was necessary as the stage of the primary tumour is

one of the most important prognosticators, and may potentially confound future observations such as

61

frequency of follow-up, and the likelihood of disease relapse. However, this variable is not available

within the Ontario Cancer Registry or any of the administrative databases for the time period of the study.

In a study of patients from the Ontario Familial Colon Cancer Registry diagnosed from January 1, 1999 to

December 31, 2000, 94% of stage III and 38% of stage II cancers in Ontario received adjuvant

chemotherapy, where most of the stage II patients were those with high risk features (clinical obstruction

or tumor perforation at presentation, T4 lesion, poor differentiation, lymphatic invasion, perineural

invasion, vascular invasion or mucin production) (127). Therefore, in the absence of a variable that

explicitly denotes the stage of the primary CRC, the administration of adjuvant chemotherapy appeared as

a suitable proxy for high risk (or stage IIb/III) colon cancer. It should be noted that for rectal cancer

however, all stage II and III patients are considered high risk (and are recommended adjuvant

chemoradiation). The accuracy of using adjuvant chemotherapy to identify patients at high risk for

relapse for both colon and rectal patients was evaluated in a subsequent part of this study.

Face and content validity for the definition of adjuvant chemotherapy was suggested by the interval to the

start date, and number of administrations. In unpublished data (128) from similar data sources examining

the receipt of adjuvant chemotherapy for those patients presenting with non-metastatic disease, the

interquartile range for the start date was found to be 41-70 days after resection. The slightly earlier

interquartile range of 38-62 days in the present study likely reflects the exclusion of patients who relapsed

in the first year of follow-up (and received palliative chemotherapy), in addition to those who were

metastatic at presentation. Furthermore, the number of doses of chemotherapy was consistent with the

5FU/LV regimens, where once a day administration for 5 days for a total of 6 cycles matched the modal

value of 30 administrations in the study group.

Visits and tests – group #1

In order to separate patients with complete and incomplete follow-up times, MD visit and test frequency

was evaluated among two groups: those who were alive at the end of the 5 year follow-up period and had

no evidence of relapse (ie. no censoring events in the follow-up period, group #1), and those patients who

had evidence of disease relapse within the follow-up period (ie. a censoring event within the follow-up

period, group #2). Due to possible differences in follow-up patterns, these groups were also sub-stratified

to colon and rectal patients, and those with a primary CRC with high or low risk for recurrence.

One important study regarding follow-up MD visits and tests was previously published by Earle et al (19)

in 2003. In this study, surgeons, medical oncologists, and radiation oncologists were surveyed regarding

their beliefs in follow-up practices, after being given a vignette of a 50 year old man with stage III colon

62

cancer. The observations from the administrative dataset analysis were similar to that reported based on

provider opinion. For example, the majority of those surveyed recommended specialist visits at least

every 6 months to yearly, from follow-up years 2-5. If the average patient was seen every 6 months in

years 2 and 3, and yearly in years 4 and 5, there are at least 6 specialist visits. Slightly more than half

(55.1%) of high risk patients saw their medical oncologist more than 5 times, and 39-42% saw their

general surgeon more than 5 times. Thus, it appears that most patients receive the recommended number

of specialist visits when combining general surgery and medical oncology. The high observed rate of

endoscopy was also reflected in the survey, where for each year of follow-up, more than 65% of

physicians recommended endoscopic surveillance. With respect to body imaging, less than one third of

physicians were recommending ultrasound, and less than 10% of physicians recommended CT imaging,

for any of the five follow-up years.

The vast majority of patients in group#1 visited their family physician more than five times during years

2-5 of follow-up. This likely represents active utilization of the health care system and suggests that the

majority of patients have at least access to this aspect of health care while in follow-up. A marked, but

not surprising discrepancy was noted in the follow-up frequency for medical oncologists. Since the proxy

for high-risk primary tumours was the receipt of adjuvant chemotherapy, it was expected that many of

these patients would be continued to be followed by their medical oncologist after completion of their

regimen. Almost 30% of patients classified as low-risk had at least one visit to a medical oncologist.

Given that these patients did not receive chemotherapy, this proportion appears high, because a medical

oncologist is unlikely to follow a patient that they did not treat. A likely explanation for this finding is

related how a medical oncologist was defined in this study. Because there is no specific OHIP billing

code for medical oncologist, a list of medical oncologists was derived from the main specialty designation

in the IPDB of those physicians who billed adjuvant chemotherapy. These main specialty designations

from the IPDB may have been internal medicine, hematology, GP/FP, or medical oncologist. Therefore

any visit to a physician who billed for chemotherapy, but for an unrelated reason, would be misclassified

as a medical oncology visit.

General surgeon follow-up appeared to be similar among both high and low risk patients, as well as colon

and rectal cancer patients. For all groups, 60-65% of patients had at least 3 visits over follow-up years 2-

5, and between 33.3% and 42.3% had greater than 5 visits. These observed frequencies appear to be

consistent with current guidelines (94, 106), averaging to at least one visit per follow-up year. Follow-up

to radiation oncology was evaluated for rectal cancer patients only, as multidisciplinary treatment for

rectal cancer often includes radiation, but not for colon cancer. Follow-up was generally low, with more

63

than half the rectal patients not seeing radiation oncology at all in the follow-up period. Gastroenterology

follow-up visits were not assessed in this study, as these visits are expected to be collinear with

endoscopic examinations, and that gastroenterologists do not usually provide oncologic follow-up of CRC

patients.

Examining the role of preoperative or postoperative (adjuvant) radiation in this cohort was potentially

difficult. The role of preoperative radiation for rectal cancer had been reported by the Swedish Rectal

Cancer trial in 1997 (13) however the definitive trial by the German Rectal Cancer Study Group (14) was

not published until 2004. Therefore, preoperative radiation was not in universal practice in the study

period. With regard to adjuvant radiation, although this was part of the NIH consensus guidelines since

1990 (10), the administration of radiation administration was not directly coded into OHIP, due to an

alternative funding plan by radiation oncologists (although consultation was captured). Therefore data

from examination of radiation fee codes may be incomplete.

Endoscopic follow-up

Most patients (>90%) appeared to receive at least one endoscopic modality at some point between CRC

resection and 5 years afterwards. Although current endoscopic guidelines call for endoscopy to be

repeated every 3-5 years (if no new polyps are found) (98), more than two thirds of patients were

receiving between two and five exams in five years of follow-up. Some of these cases may be attributed

to repeat colonoscopies due to previous incomplete examinations, or there were polyps removed that

necessitated a repeat exam after one year. However, the complete colonoscopy rate was 78.9%, and

therefore it is unlikely that this many repeat examinations were all due to incomplete examinations.

There remains the possibility that many patients receive more endoscopies than currently recommended,

especially since Earle et al. (19) also found that at least 65% of surveyed specialists recommended colonic

surveillance in each of the five follow-up years. Further study is warranted to investigate the potential

overuse of this health care resource. On the other hand, the polypectomy rate of 20.9% (or one in 5

colonoscopies) emphasizes the importance of appropriate endoscopic surveillance following CRC

resection. A small but not insignificant number of patients did not receive endoscopy in the follow-up

period (7.1% of colon patients, 6.5% of rectal patients), and factors associated with this were explored.

Model #1 - Exploratory analysis on endoscopy

In model #1, increasing age and Charlson score had negative associations with receiving at least one

endoscopy modality in follow-up years 1 through 5. These factors have face validity, as with any

invasive procedure, the risks associated with the procedure may outweigh any potential benefits in the

64

context of the age or associated comorbidities of the patient. However, it should be emphasized that age

and comorbidity alone should not be used as justification for not performing endoscopy, but should be

among factors to consider when offering endoscopy to individual patients. The positive association of

more recent period of diagnosis with the outcome also has face validity, as the new guidelines which

appeared in this period emphasized the importance of post resectional endoscopic surveillance.

In this logistic regression model, the cutpoint of zero vs. one or more endoscopies in the follow-up period

was chosen as the outcome. Determining the “minimum acceptable” number of tests in the follow-up

period requires several considerations. Current guidelines (first endoscopy within the first 3 years from

primary CRC resection, and repeating up to every 5 years if normal) may allow even one examination to

be “acceptable”, although repeat examinations are necessary if polyps are found or the examination was

incomplete. If there were multiple examinations, then temporality of the tests presents a further

consideration. For example, if two endoscopies were performed in each of the first two follow-up years,

but none thereafter, it may be argued this is a waste of resources. But a single endoscopy in follow-up

year 1 followed by an endoscopy in year 5 may be considered acceptable. Therefore, choosing cutpoints

other than zero vs. one or more endoscopies requires knowledge of the test indication, and consideration

of temporality, which are difficult to incorporate using analyses of administrative data.

It was observed that the two highest income quintiles had an increased likelihood of receiving endoscopy.

Since endoscopy tests were counted from OHIP billings, this phenomenon could not be attributed to the

purchase of health care by more wealthy patients. It is possible that this may be a reflection of patients in

higher socioeconomic strata being able to more effectively advocate for their own healthcare and for

receipt of health services. This difference among income strata was also observed in other studies in

managed care settings, where individuals were unlikely to purchase health services. In 2001, Elston

Lafata and colleagues (129) examined post resectional surveillance care among a cohort of 251 patients at

a managed-care institution. By the end of 5 years, 77% of the cohort had received colonoscopic

examination. Similar to the results of the present study, a multivariable model examining the likelihood

of colonoscopic examination, increasing age and comorbidity score had a negative association, while

increasing median household income by ZIP code had a positive association. There were no differences

by sex, type of curative treatment, site or stage of disease. Further study involving individual level data

and actual household income may be useful in further defining the relationship between receipt of

surveillance endoscopy and socioeconomic status. It is not until these potential explanatory mechanisms

are elucidated that further intervention such as knowledge translation initiatives, or deployment of

resources, can be used to address SES as a potential barrier to receiving surveillance endoscopy.

65

Other variations in endoscopic follow-up have been previously documented in the literature (109, 130).

Cooper et al. (109) examined over 5700 patients aged 65 and over from the Surveillance Epidemiology

and End Results-Medicare linked database, and their Medicare claims from 6 months after CRC resection

to 36 months afterwards. In this study, only 2903 (51%) of patients received at least one endoscopy test

in this follow-up period, with an average of 2.9 procedures, where at least one code for polypectomy or

biopsy was present for 21% of patients. The polypectomy rate per colonoscopy, however, was much

higher, ranging from 31.7% for colonoscopies performed earlier in the follow-up period, to 41.2% for

those performed later in the follow-up period. Furthermore, factors associated with the use of

colonoscopy were explored, with decreased use associated with increasing age, and geographic variation

was observed for colonoscopy rates. Income quintile was not explored in their analysis. Ellison et al

(130) also examined the potential for racial variation in bowel surveillance following curative CRC

resection. Following adjustment for sex, age, geographic region, comorbidity, and hospital

characteristics, African American patients were 25 percent less likely to receive colonic surveillance than

white patients.

Body imaging follow-up

Overall, almost one third of patients did not receive any body imaging modality in the 5 year follow-up

period, although most of these patients were those with low risk disease (about 77% of the 2760 patients).

However, even 19% of high risk patients did not receive any imaging modality in the follow-up period.

Although body imaging was not a requirement of surveillance guidelines during the study period, it was

surprising that Earle et al. showed that most specialists do not recommend any routine follow-up body

imaging, and that these attitudes were reflected in the observations in the present study. In the last

decade, many improvements have been made in both imaging and increasing eligibility for surgery

(particularly liver resection), two different meta-analyses have suggested a benefit of body imaging (92,

106) and current ASCO guidelines even mandate annual CT for the first 3 years in high risk patients (96).

Given these facts, one may consider that at the very least, patients at high risk for relapse would have

received one body imaging test throughout the entire follow-up period.

Model #2 – Exploratory analysis on the use of body imaging

In analyzing factors associated with the use of body imaging in years 2-5, stratification by high or low

risk primary was necessary to address its interaction between general surgeon and medical oncology

follow-up. Although the OR estimates were different for these covariates in either strata, both general

surgery and medical oncology follow-up was positively associated with the use of body imaging in high

66

or low-risk patients. In addition, since nearly all patients had seen their GP (as only 3.8% of these

patients had no GP visits in 5 years, Table 6), these results suggest that follow-up with a specialist is

important for receiving some body imaging modality, regardless of GP follow-up. In the aforementioned

study by Earle et al (19), 64% of oncology physicians surveyed stated that they routinely discharge

patients at some point to their primary care physicians for follow-up care. Because these results show an

association with at least one specialist visit with the use of body imaging, it may be possible that a

discharge of a patient to their GP early in the follow-up period may decrease their likelihood of receiving

imaging studies later in the follow-up period due to less familiarity with guidelines or less focus on CRC

care in a primary care setting. There has been at least one previous study comparing general surgeon to

GP-led follow-up of CRC patients (107). This study also showed that patients in the surgeon-led arm

were more likely to receive both imaging and endoscopic surveillance, although it was underpowered to

show any difference in death or recurrence rates.

Although these results suggest that specialist follow-up may be different than GP follow-up, further study

is required to confirm if there truly is a benefit to specialist follow-up. It is possible that specialists are

more familiar with specific surveillance guidelines and are thus more likely to adhere to them. There is a

large volume of literature that compares generalist to specialist follow-up. A recent systematic review

(131) examined 49 articles that compared generalist to specialist care for discrete medical conditions.

Although the majority of articles reviewed (24) favored specialist care, selection bias was addressed in

only 58% of these studies, and these articles were also less likely to consider key potential physician or

patient related confounders in their analysis. For future studies to appropriately evaluate or confirm the

present findings regarding specialist or GP follow-up, attention must be paid to methodology and

confounding variables prior to drawing conclusions.

Visits and tests – group #2

Visits and tests were examined for the second group of patients: those who relapsed within the 5 year

period, and this analysis was repeated by examining billings up to 60 or 90 days prior to the first evidence

of CRC relapse. This period of censoring was employed in order to account for any physician visits or

diagnostic testing prompted by symptoms prior to the diagnosis of relapse. Not surprisingly, frequencies

were slightly lower in the 90 day analysis due to an extra month of censoring. In comparison with those

who had no evidence of relapse, this group of patients had similar follow-up frequencies. For example,

GP follow-up among relapsed patients averaged about 2-3 visits per 6 months, translating to 4-6 visits per

year. In a similar manner to non-relapsed patients, medical oncology follow-up frequency and body

imaging frequency was much less for patients with low risk disease. For endoscopy modalities, patients

67

who relapsed in year 2 had almost double the frequency of endoscopy than others who relapsed in later

years, and this was observed using 60 or 90 day censoring. This phenomenon is likely related to a smaller

time denominator for these earlier relapses, and not due to a true higher frequency of endoscopy tests.

CRC relapse and treatment

In total, 3,316 patients had evidence of relapse in the follow-up period and this total rises to 3,454 when

including those who died of cancer only. Taken along with the 7,814 patients that were excluded in

follow-up year 1, approximately 50% of the original cohort of patients who received a CRC resection

(N=20,635) were classified with metastatic or disease relapse either at presentation or at some point in

follow-up, matching historically reported statistics (16-20). Overall, most patients relapsed in year 2 or 3

with decreasing frequencies in later years, emphasizing the importance of early follow-up for the highest

yield of detection (Table 11).

Among 3,185 high risk colon cancer patients, 1,071 relapsed giving a relapse rate of 34%. For the 5,579

low risk colon cancer patients, 1,082 relapsed, giving a relapse rate of 19.4%. In the literature, it has been

reported that the risk of relapse from stage II CRC is 25-30% (132, 133). Since patients classified as low

risk in the present study comprised mostly of stage I and II patients, the rate of relapse among these

patients appears to be consistent with the literature. However, although it does appear that low risk

patients appropriately have a lower risk of relapse, it was observed that out of relapsed patients, a higher

proportion from years 3-5 originally had a low risk primary tumour (Table 11). Although the date of

relapse as determined by administrative data may not be highly accurate (as suggested by the primary

chart validation), this observation may suggest further insight into the biology of low risk disease.

Although the absolute risk of relapse is lower than in high risk disease, relapses that do occur may be

more likely to occur later in the follow-up period. This observation is not likely sufficient to suggest any

changes to current recommendations for CRC surveillance for low risk patients, however, it may lower

the threshold for clinicians to perform at least one test such as abdominal ultrasound in the later years of

the follow-up period, where potential harm is minimal but with potential benefit of detecting treatable

relapse.

Overall, 11.3% of relapsed patients received a liver or lung resection, or 1.8% of the original cohort

received potentially curative surgery. Previous population based studies examining the use of liver or

lung resection in CRC patients have not consistently used a denominator in their analyses. Ideally, the

denominator for evaluating the proportion who received a potentially curative liver or lung resections is

the group of patients with resectable disease who are fit for surgery. Although this denominator is

68

extremely difficult, if not impossible, to obtain with administrative databases, important inferences can

still be made using other denominators that are available. In the aforementioned study by Earle (19), post

CRC resection surveillance was discussed in the context of how many patients could potentially benefit

from it. It was estimated that of patients that receive definitive treatment for CRC, 50% will relapse, 10-

15% are potentially resectable (with respect to liver metastases), and only about a third of those are

curable. Therefore, 3-5% of CRC patients can be potentially cured by either presenting with symptoms or

through a surveillance regimen. With this estimate, and observing that only 1.8% of the cohort of CRC

patients received potentially curative surgery, there is a potential group of relapsed CRC patients who

were eligible but did not receive treatment.

Treatment of relapse – mean neighborhood income quintile

When analyzing relapses by mean neighborhood income quintile, interesting observations were noted.

For patients who had evidence of relapse, the proportion appeared to decrease with higher income quintile

(although this trend was not statistically significant). Socioeconomic status has been associated with

cancer survival in some American studies (134-136), as well as within Ontario (137). Because these

analyses were by socioeconomic strata, the differences in cancer mortality rates in these studies were

suggested to be confounded by strata specific cancer incidence rates (138). However, the present study

first identifies CRC patients, and then stratifies by socioeconomic strata, and increasing proportions of

relapse in lower strata were still observed. There were significant differences in the receipt of lung

resection among income quintiles, and increasing proportions treated with liver resection or

chemotherapy in higher quintiles (but not statistically significant). These findings suggest that despite a

universal health care system that is designed for equitable access among all socioeconomic groups, there

may be a potential difference in access to, or administration of health care. This may in part be due to

unmeasured confounders associated with both SES and suitability for lung resection (e.g. smoking status).

And as mentioned in the discussion of follow-up endoscopy, these differences may also be due to patients

in higher income quintiles being able to better advocate for their health care needs and access to care.

Regarding lung resections, it was observed that the rate among the group of relapsed patients was 4.3%

(Table 12). This figure is more than twice the historically estimated resectability rate of 1-2% (69, 75, 80,

139), although more current data may suggest higher resectability rates. There is an unlikely possibility

that the numbers observed are artificially inflated, as lung resections may be performed for benign

disease. Preliminary analyses showed that 92% of all lung procedures had a cancer related diagnosis code,

and therefore there lies a potential that resections occurred for primary lung malignancies that were not

coded to OCR. There also may be an underestimate of the number of relapsed patients, and the resulting

69

smaller denominator would yield a higher resection rate. However, even historical studies may not be

able to account for all relapsed patients, and it is also unlikely that only half of all relapsed patients were

detected in the present study. Therefore, an important hypothesis is generated, where the number of

relapsed patients with resectable lung lesions is in fact much higher than previous studies have suggested.

If these observations are confirmed, there may be justification to explore recommending increased chest

surveillance in addition to liver surveillance. As observed, the rate of chest CT is low overall, and there is

a possibility that patients with potentially resectable lung relapses were missed as a result.

Treatment of relapse - LHINs

Among the Ontario LHINs, the proportion of patients receiving lung surgery, liver surgery, or

chemotherapy was examined, with the denominators of all relapsed patients and all resected CRC

patients. Regardless of the denominator used, the proportions of patients who received any of these types

of treatment were not statistically different. In contrast to these findings, studies of other populations

using administrative databases have shown that regional variation exists for CRC related treatment. For

example, in addition to the initiation and completion of adjuvant chemotherapy for CRC, geographic

location has been associated with CRC lymph node evaluation (12), and appropriate surgical resection of

locally advanced CRC (140).

Focusing on the LHINs were surgical treatment was given, it was observed that for both liver and lung

resections, the same four LHINs had the highest number of surgeries: Toronto Central, Hamilton Niagara,

Southwest, and Champlain. These LHINs correspond to the main surgical academic institutions in

Ontario: the University of Toronto, McMaster University, the University of Western Ontario, and

University of Ottawa. The remaining academic institution (Queens University) could not be accounted

for as it is located within the excluded LHIN (Southeast). Noting that there was no significant difference

between LHINs for receiving surgical treatment for relapse, this observation likely reflects regionalization

of specialized procedures such as solid organ resection for metastatic cancer, where higher volumes may

translate to higher survival. For these patients, this is especially important given that academic centers are

often able to provide the multidisciplinary care that is essential in the management of cancer relapse. In

addition, many studies have explored the volume-outcome relationship for complex surgery. Dimick et al

(141) examined the National Inpatient Sample in the United States for all patients in 1996 to 1997 with

liver resection. The most common indication for these operations was secondary metastases (52%). On

multivariable analysis, high volume hospitals had a 40% lower mortality rate compared with low-volume

hospitals (OR 0.60, 95%CI 0.39-0.92). In Ontario, the effect of higher volume hospital on survival

following liver resection for CRC relapse was examined by Shah et al. (142). Higher volume hospital

70

was found to have a statistically significant benefit for survival (HR 0.72, 95%CI 0.56-0.91),

complimenting the observations from the present study.

Treatment of CRC relapse - survival

An examination of the survival data for surgical resection and chemotherapy yielded results which were

consistent with that of that of the literature. The 5 year OS for liver resections was 45% which was in

agreement with a previous study examining liver resections for CRC relapse in Ontario (142) where a

43% 5 year OS was observed, and also for recent single institution series with 5 year OS of greater than

40% (41, 51). The 5 year OS of 48% for lung resections was also within the reported range in previous

studies (30-60%) (73-77, 85-87). However, the 5 year OS for those patients who did not receive surgery

was slightly higher than that reported for patients with untreated disease relapse, even if they received

palliative chemotherapy. A possible explanation for this observation is that due to the algorithms used,

the identification of patients who received surgical resection for relapse are highly specific, however there

may have been misclassification of those patients who appeared to relapse but did not receive any

(surgical or medical) treatment. Therefore, the fixed number of misclassified patients will falsely elevate

both 5 year OS and median survival.

Model #3 - Use of surgery in the management of relapse

In this analysis, an important limitation must be acknowledged – not all patients in the population may

have been eligible for surgical treatment. From the data sources used, there is not sufficient information

to determine clinically important parameters such as the burden, anatomic distribution, or resectability of

disease. In addition, there are also physician factors that play a role in the selection of a patient for

surgery. However, there was no method to reliably exclude ineligible patients from this population.

Therefore the results of this analysis should be interpreted as both exploratory and preliminary.

In model #3, the third and fifth income quintiles were more likely to have had surgery than other

quintiles. Although it is difficult to explain why two non-consecutive quintiles may have a higher

likelihood of surgery than others, the point estimates of OR’s suggest that there may be an increasing

likelihood with higher income quintile (point estimates increasing from 1.00 to 1.95). A lower OR

observed in the fourth quintile may have been a spurious non-statistically significant result attributed to

the relatively low number of outcomes (353) in this population.

As it was shown that these complex surgical procedures are concentrated in LHINs with academic

institutions, further study regarding the use of high volume hospitals that perform complex procedures

71

such as lung and liver resection is warranted. In particular, patient characteristics such as age, sex,

socioeconomic status and race should be among factors examined. Liu et al (143) examined patient

characteristics associated with high volume hospitals in California performing complex procedures

including lung cancer resection. In addition to race, disparities were also found based on health insurance

status where Medicaid and uninsured patients were less likely to be treated in high volume hospitals.

Although Ontario employs a universal health care system, there remains the possibility of disparities in

access to care which need to be explored. This need is further supported by the previous observation that

higher rates of relapse were found in lower income quintiles (although not statistically significant), and

that more patients underwent lung surgery in higher income quintiles.

Other observations in this analysis included a lower likelihood of receiving surgery with increasing age or

increasing comorbidity, which reflects patient selection for complex and potentially high risk surgery.

The positive association of more recent year of diagnosis with surgical resection was likely due to the

increasing rates of identification, referral, and aggressive resection of CRC relapse (41, 89, 142).

Although high risk primaries likely have disease biology that is associated with a poorer prognosis

(higher rate of relapse), it appears that more resectable relapses occur among this group (13.5% of

relapsed high risk patients with relapse resection vs. 7.3% of relapsed low risk patients). However, it is

difficult to further comment on the validity of this observation without examination of individual charts of

relapsed high and low risk patients who relapsed.

Since patients who are diagnosed with relapse may have a series of physician visits or diagnostic imaging

tests prior to surgery or chemotherapy, censoring a period of time up to the date of relapse was used to

address this. In a previous study of wait times for surgery (144), median lung cancer surgery wait time

was 34 days in 2000. Therefore, the conservative period of 60 days was chosen as the default length of

time to censor further physician visits and test events. To test the sensitivity of the covariates to the

length of time chosen to censor, this analysis was repeated with censoring periods from 0 to 120 days

(Figure 7). With an increasing censoring period, potentially important information including surveillance

testing would be excluded, and it was expected that all visit and test variables would lose any statistical

association with the outcome. However, body imaging frequency was the only sensitive variable, where

it was no longer significant for the outcome of surgical resection of relapse after censoring greater than 60

days. Although previous meta-analyses have also shown a potential benefit for increased body imaging

frequency (92) it is impossible to quantitate the magnitude of an ideal rate of body imaging because of the

variability in rate between patients, and there is no consistent baseline for comparison. The rate of body

imaging likely needs to be individualized for each patient. However, there does appear to be some benefit

72

with an increased frequency, where there is a higher likelihood of receiving resection of relapse due to

earlier detection.

Secondary objective: Comparison with chart reviewed cohort

In order to confer validity to observations made in this study, it was necessary to assess the accuracy of

algorithms used to exclude patients prior to the start of the follow-up period, the definition of disease

relapse, and the use of adjuvant chemotherapy as a proxy for high risk disease. By obtaining information

from a primary chart reviewed cohort of patients from the same time period of this study, these data may

be used as a reference standard to assess the algorithms.

Although the majority of chart reviewed patients were linked to their respective encrypted identifier

among administrative databases, a portion (68.8%) of them was linked to the study cohort prior to first

year exclusions. This was explained by examining the OCR record of non-matched patients, and was

accounted for by other exclusion criteria such as age, diagnosis with other primary tumors, histology, or

disease site. A group of patients (n=54) had colorectal resections outside of the date constraints of the

inclusion criteria, or by not having a procedure code that was considered a colorectal resection.

Despite the relatively low sensitivity (58.5%) for detecting and excluding patients who had presented with

metastases or had early relapse within one year, 44 of the 49 patients misclassified as being eligible for

follow-up were still classified as having relapse at some later time beyond one year. In addition, the

algorithm used to classify study patients as having disease relapse in the follow-up period had a

sensitivity of 87.5% and specificity of 93.0%, when compared to primary chart reviewed data. Given

these observations, the accuracy for detecting disease relapse was assessed for the entire group of patients

(both eligible and not eligible for follow-up). The sensitivity and negative predictive value was 93.7%

and 93.6%, respectively, and as a tradeoff this resulted in a lower specificity (75.4%) and positive

predictive value (75.5%). Therefore, these results show that this algorithm had a reasonable

discriminatory power to use in population-based studies to detect patients with disease relapse using

administrative data. Of note however, the dates of the first evidence of disease relapse from

administrative data codes may not correspond well with the true date of disease relapse, since some

relapses in the first year were not detected until later in the follow-up period. This is an important

observation, considering that preliminary data from objective #1 suggested that patients with low risk

tumours appeared to have higher rates of relapse in later years of follow-up.

73

Although the number of patients from the validation dataset was small (353 patients), these figures confer

both face and content validity to how patients were classified. An advantage to this data validation is that

future studies examining relapsed patients may use or build upon the present algorithm in their

methodologies while having an estimate of its accuracy. A limitation of the algorithm was demonstrated

when examining the locations for the false negatives. Four of the five false negative patients had relapses

in ill-defined sites such as local, lymph nodes, and intraabdominal. For the cases that received surgical

resection, the surgical procedure could not easily be deduced based on the site of recurrence (lymph node,

local), and therefore cannot be explicitly defined through administrative data codes. Also, despite that

information that is derived directly from chart review, the reference standard has the limitation of only

consisting of patients from two hospitals, and therefore may be subject to selection bias. The validation

of data accuracy would be complemented by a comparison with another reference standard of a larger

dataset, sampled from the entire province such as the Ontario Familial Colon Cancer Registry (OFCCR)

(145).

The classification of high risk disease yielded a high capture rate of both stage III colon (95.0% of stage

III patients correctly classified as high risk) and rectal cancer (93.9%) patients. However, 63.6% of stage

II colon cancer patients were classified as high risk for relapse. Although selection bias may partially

explain the difference between this proportion and that previously reported (38%) (127), there may be an

increasing number of stage II colon cancer patients receiving adjuvant chemotherapy. Interestingly, only

67.9% of stage II rectal cancer patients appeared to receive adjuvant chemotherapy and classified as high

risk, despite that guidelines call for all stage II and III rectal cancers patients to receive adjuvant

chemoradiation. From the available data, it is unclear why this proportion appears low. A chart review of

these patients would be required to determine whether the remaining 32% of stage II rectal patients were

appropriately not given adjuvant chemotherapy (eg. performance status, etc).

Limitations

In this descriptive study using administrative data, there exist several inherent limitations, as well as

limitations in the methodology and the interpretation of results. Although an advantage of population-

based studies is that single-institution bias is avoided and there are usually sufficient numbers of patients

to power multivariable analyses, the conclusions are limited to observed associations and cannot ascertain

causation. Individual level data from primary chart reviews (eg. additional CRC risk factors such as

history of inflammatory bowel disease, familial adenomatous polyposis [FAP], hereditary non-polyposis

74

colorectal cancer [HNPCC] or family history) would be appropriate to either complement or follow-up

the hypotheses generated from these studies.

Although the OCR is a rich source of data for incident cancers, one significant limitation was that the

stage of the tumor was not recorded for the time period of the study. This was an important potential

confounding variable for analyses, as stage is one of the most important predictors for prognosis (146)

and determining the appropriate surveillance. Since higher stage tumors are also recommended adjuvant

chemotherapy, this confounding effect was addressed by classification of high or low risk based on

receipt of adjuvant chemotherapy, which can be detected in administrative data. Classification of high or

low risk, however, was not expected to be collinear with stage, as receipt of adjuvant chemotherapy

usually applies to stage III but also some high risk stage II colon cancers (11, 147), as well as all stage II

rectal cancers (10). In addition, there was a potential for misclassification if patients had a high risk

tumour but did not receive chemotherapy due to medical risk. This rate of misclassification was expected

to be small, because if a patient was fit enough to undergo surgery, there was a high likelihood that they

would also be fit enough to undergo chemotherapy. An advantage of this method of classification is

represented by the patient who prematurely ends their chemotherapy regimen due to toxicity or

intolerance. In this case they would still be classified as high risk as this definition was based on receipt

of at least one course of chemotherapy following primary resection.

As data from CIHI-DAD was recorded from hospital discharge abstracts, information is lacking from

patients who were never admitted to hospital. For patients who are healthy and free of disease, this does

not present a significant bias, as follow-up visits and tests were determined using OHIP billing data. For

relapsed patients, this was addressed by examining both hospital diagnosis codes and OHIP billings from

potential outpatient claims (chemotherapy, palliative care) in the definition of disease relapse. However,

patients who do not interact at all with the health care system, or who relapse but do not receive surgery,

biopsy, chemotherapy, or palliative care cannot be detected. This was addressed by exploring the number

of patients who had no evidence of relapse through OHIP billing (chemotherapy, palliative care, surgery,

biopsy) or discharge abstract (advanced disease diagnosis, surgery, biopsy) but yet had a cancer related

cause of death. This group of patients only constituted a small proportion (138, 1.1%) of the study

cohort, or potentially only 4.0% of relapsed patients.

In order to describe the proportion treated for relapse, it was necessary to use the appropriate

denominator. The ideal denominator to use would be those patients who are eligible for each treatment

(surgery or chemotherapy) – those who are fit for surgery with resectable relapses, or those who are

ineligible for surgery but fit enough to allow them to undergo chemotherapy. Details such as resectability

75

and fitness for surgery are not available in administrative data, and would require a complete review of

the chart (including all imaging) which is unfeasible with the number of patients in this study. This is

further complicated by varying selection criteria for surgery, such as how to manage bilobar lesions, or

poor prognostic factors (patient or disease related). The next possible denominator would be all relapsed

patients. Although there is no data source to explicitly ascertain the relapse status of a patient, an

algorithm to classify them was used. Because of potential misclassification of patients by using this

algorithm as either false negatives or false positives, the denominator of CRC patients with a primary

colorectal resection was also used. Although this denominator was easier to define, the trade-off was that

it included the most number of “ineligible” patients, including those that did not experience disease

relapse. However, this population was useful as a common denominator for comparisons of different

groups (LHINs, income quintiles) as the proportion of ineligible patients should remain constant.

Another limitation to using administrative databases is that the indications for tests cannot be ascertained

without primary chart review. For example, when examining tests preceding disease relapse, it was not

possible to determine whether tests were done for surveillance, or as part of diagnosis before the first

relapse event was recorded. This was addressed by repeating analyses with different lengths of time for

censoring visits and tests prior to relapse, and by performing a sensitivity analysis of the variables in the

exploratory analysis. However, disentangling surveillance from diagnostic testing in addition to

identifying those who have experienced disease relapse remains to be a significant task, which will

always remain a challenge and limitation when analyzing administrative data.

Lastly, a common follow-up test, CEA level, was not available in any of the data sources. This test was

potentially important in describing follow-up patterns following resection, particularly in patients who are

considered low risk and have serial CEA testing as their only surveillance modality. It may be possible

that for many of the patients that did not receive any body imaging in the follow-up period, there may

have been surveillance via this blood test. Furthermore, an elevated CEA level may be the index test that

triggers other follow-up examinations such as endoscopy or body imaging. Apart from performing

primary chart review to determine the frequency of CEA testing, it may be possible to link data from

laboratory databases. Information from such a linkage would be complementary to the findings in the

present study.

76

Summary and future directions

In this descriptive study, the processes of care that Ontario CRC patients receive were documented. In

general, endoscopic surveillance following resection appears to be performed at a relatively high rate,

where overall only 7.1% of colon cancer and 6.5% of rectal cancer patients did not receive any

endoscopic exam after CRC resection. However, this small percentage of patients is not insignificant.

Using the results from the exploratory analysis as a starting point, further research may be initiated to

determine the mechanism behind why demographic factors such as socioeconomic status is related to the

receipt of follow-up endoscopy. The use of body imaging was found be to be relatively low. Although

the observed results parallel the opinions of oncologists expressed in a prior survey (19), body imaging

was potentially a factor associated with the increased likelihood of receiving surgical treatment for

relapse. Given this, both resource-based and opinion-based barriers to receiving body imaging should be

explored in future studies as there are potential areas that may be addressed through budgetary

redistributions or educational interventions, respectively.

An algorithm to detect CRC relapse in administrative data was used to identify and describe this group of

patients. The rate and treatment of relapse was analyzed among LHINs and income quintiles, and

potentially important hypotheses were generated from observing differences among socioeconomic strata.

It appeared that potentially curative resections of CRC relapse were performed in regions with academic

surgical institutions, regardless of region of residence. Exploratory analyses were performed to determine

potential factors associated with surgical resection of CRC relapse, and the complexity of defining

follow-up was attempted. Finally, by using a primary chart reviewed cohort of CRC patients in Ontario

as a reference standard, this algorithm for detecting CRC relapse was shown to be highly sensitive and

specific. The receipt of adjuvant chemotherapy was also shown to be a sensitive method of detecting

stage III colon and rectal cancer patients.

With the establishment of an algorithm to detect CRC relapse in Ontario administrative databases

validated with a chart reviewed population, clinically relevant outcomes can be detected for use in future

studies. The description of the processes of care that Ontarians receive after CRC resection and potential

impact on outcomes, builds a foundation for future studies to establish the relationships between different

processes and outcomes, and potentially develop useful quality indicators. These will be critical in the

goals of ensuring quality and equitable treatment for Ontarians, and may serve as a model for other

jurisdictions to develop their own quality indicators. With this ongoing research, the level of care,

surveillance and treatment for this significant disease will continue to improve.

77

Appendix

Table A.1 OHIP fee codes used to identify colorectal resectional surgery

OHIP Fee code Description

S166 Right hemicolectomy

S167 Excision and anastomosis – large intestine – any portion

S168 Subtotal colectomy and ileostomy

S169 Total colectomy, ileo-rectal anastomosis

S170 Total colectomy, ileo-rectal anastomosis, abdomino-perineal resection

S171 Left hemicolectomy

S172 Total colectomy with loop ileostomy

S173 Same as S170 – 2 surgeon team, abdominal

S174 Same as S170 – 2 surgeon team, perineal

S177 Intestinal obstruction – with resection

S213 Proctectomy – anterior resection/protosigmoidectomy

S214 Proctectomy – abdominoperineal resection / pullthrough

S215 Proctectomy – 2 surgeon team, abdominal

S216 Proctectomy – 2 surgeon team, perineal

S217 Proctectomy – Hartmann procedure

78

Table A.2 CIHI procedure codes for colorectal resectional surgery

CCP code Description

57.5 Partial excision of large intestine

57.51 Multiple segmental resection of large intestine

57.52 Cecectomy

57.53 Right hemicolectomy

57.54 Resection of transverse colon

57.55 Left hemicolectomy

57.56 Sigmoidectomy

57.59 Other partial excision of large intestine

57.6 Total colectomy

60.2 Local excision or destruction of lesion or tissue of rectum

60.24 Local excision of rectal lesion or tissue

60.4 Abdominoperineal resection of rectum

60.5 Other resection of rectum

60.51 Anterior resection with concomitant colostomy

60.52 Other anterior resection

60.55 Hartmann resection

60.59 Other resection of rectum NEC

CCI code Description

1.NM.87.* Excision partial, large intestine, laparoscopic or open

1.NM.89.* Excision total, large intestine, laparoscopic or open

1.NM.91.* Excision radical, laparoscopic or open

CCP, Canadian Classification of Procedures (pre-2002)

CCI, Canadian Classification of Interventions (2002-present)

NEC, Not elsewhere classified

79

Table A.3 ICD-9 codes for secondary disease

ICD-9 Code, description Notes:

196 Secondary and unspecified malignant neoplasm of

lymph nodes

Excludes: any malignant neoplasm of lymph nodes, specified as primary (200.0-202.9) Hodgkin's disease (201.0-201.9) lymphosarcoma (200.1)

reticulosarcoma (200.0) other forms of lymphoma (202.0-202.9)

196.0 Lymph nodes of head, face, and neck Cervical, Cervicofacial, Scalene Supraclavicular

196.1 Intrathoracic lymph nodes Bronchopulmonary, Intercostal, Mediastinal, Tracheobronchial

196.2 Intra-abdominal lymph nodes Intestinal, Mesenteric, Retroperitoneal

196.3 Lymph nodes of axilla and upper limb Brachial, Epitrochlear, Infraclavicular, Pectoral

196.5 Lymph nodes of inguinal region and lower limb Femoral, Groin, Popliteal, Tibial

196.6 Intrapelvic lymph nodes Hypogastric, Iliac, Obturator, Parametrial

196.8 Lymph nodes of multiple sites

196.9 Site unspecified

197 Secondary malignant neoplasm of respiratory and

digestive systems

Excludes: lymph node metastasis (196.0-196.9)

197.0 Lung Bronchus

197.1 Mediastinum

197.2 Pleura

197.3 Other respiratory organs Trachea

197.4 Small intestine, including duodenum

197.5 Large intestine and rectum

197.6 Retroperitoneum and peritoneum

197.7 Liver, specified as secondary

197.8 Other digestive organs and spleen

198 Secondary malignant neoplasm of other specified sites Excludes: lymph node metastasis (196.0-196.9)

198.0 Kidney

198.1 Other urinary organs

198.2 Skin Skin of breast

198.3 Brain and spinal cord

198.4 Other parts of nervous system Meninges (cerebral) (spinal)

198.5 Bone and bone marrow

198.6 Ovary

198.7 Adrenal gland Suprarenal gland

198.8 Other specified sites

198.81 Breast

Excludes:

skin of breast (198.2)

198.82 Genital organs

198.89 Other

199 Malignant neoplasm without specification of site

199.0 Disseminated

Carcinomatosis unspecified site (primary) (secondary) Generalized: cancer unspecified site (primary) (secondary) malignancy unspecified site (primary) (secondary)

Multiple cancer unspecified site (primary) (secondary)

199.1 Other

Cancer unspecified site (primary) (secondary) Carcinoma unspecified site (primary) (secondary) Malignancy unspecified site (primary) (secondary)

80

Table A.4 Surgery and biopsy codes for lung and liver, OHIP claims and CIHI procedure codes

Liver

Code Code type Classification Procedure

S267 OHIP Resection Excision, liver, 3 or 4 segments

S270 OHIP Resection Excision, liver, one or two segments

S271 OHIP Resection Excision, liver, five or more segments

S275 OHIP Resection Excision, liver, partial lobectomy >=5cm S269 OHIP Other Excision, liver, local excision of lesion < 5cm

62.12 CCP Resection Partial hepatectomy

62.2 CCP Resection Lobectomy of liver

62.3 CCP Resection Total hepatectomy

62.19 CCP Other Other destruction of lesion of liver

62.81 CCP Biopsy Percutaneous biopsy of liver

62.82 CCP Biopsy Other biopsy of liver

62.89 CCP Biopsy Other invasive diagnostic procedures on liver

1.OA.87* CCI Resection Excision, partial, liver using laparoscopic or open

approach

1.OA.59* CCI Other Destruction of liver, endoscopy, percutaneous or open, using cryoprobe, laser, radiofrequency, device

NEC, chemical

2.OA.71* CCI Biopsy Biopsy, liver, using laparoscopic, open or

percutaneous approach

Lung

M142 OHIP Resection Pneumonectomy

M143 OHIP Resection Lobectomy

M144 OHIP Resection Segmental resection

M145 OHIP Resection Wedge resection

Z338 OHIP Biopsy Biopsy of pleura or lung with limited thoracotomy

M138 OHIP Biopsy Hilar lymph node or lung biopsy with full

thoracotomy

Z340 OHIP Biopsy Biopsy of lung, needle

44.3 CCP Resection Segmental resection, lung 44.4 CCP Resection Lobectomy, lung

44.5 CCP Resection Complete pneumonectomy

44.22 CCP Other Endoscopic excision or destruction of lesion or

tissue of lung

44.29 CCP Other Other local excision or destruction of lesion or

tissue of lung

45.83 CCP Biopsy Percutaneous (needle) biopsy of lung

45.84 CCP Biopsy Other biopsy of lung

1.GT.59* CCI Other Destruction of lung NEC, endoscopic, laser or

device NEC

1.GR.87* CCI Resection Excision, partial, lobe of lung 1.GR.89* CCI Resection Excision, total, lobe of lung

1.GR.91* CCI Resection Excision, radical, lobe of lung

2.GT.71* CCI Biopsy Biopsy, lung

81

Table A.5 Chemotherapy codes, OHIP claims

OHIP fee code Description

G281 Additional injection (to G381)

G339 Single agent intravenous chemotherapy

G345 Multiple agent intravenous chemotherapy

G359 Special single agent chemotherapy

G381 Single injection (for agents other than doxorubicin,

cisplatin, bleomycin or high dose methotrexate)

Table A.6 Physician consultation codes, OHIP claims

OHIP fee codes Description

A001, A003-A008, A905 Consultation, general practitioner

A033-A036, A935 Consultation, general surgeon

A435, A131, A133, A134, A135, A136, A138 Internal medicine

A611, A613, A614, A615, A616, A618 Hematology

A345, A745, A346, A343, A340, A341, A348 Radiation oncology

Table A.7 Imaging and endoscopic modalities, OHIP claims

OHIP fee code Description

X406, X407, X125 CT Thorax

X409, X410, X126, X231, X232, X233 CT abdomen/pelvis

J135, J435, J128, J428 Ultrasound abdomen

Z512, Z514, Z535, Z536, Z555, Z580 Colonoscopy/sigmoidoscopy

X451, X455, X461, X465 MRI abdomen/pelvis

82

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