Health-Related Quality of Life of Cancer andNoncancer Patients in Medicare Managed Care

Frank Baker, Ph.D.1

Samuel C. Haffer, Ph.D.2

Maxine Denniston, M.S.P.H.1

1 Behavioral Research Center, American CancerSociety, Atlanta, Georgia.

2 Centers for Medicare and Medicaid Services,Baltimore, Maryland.

Presented at the DHHS conference, “Partnershipsfor Health in the New Millennium: LaunchingHealthy People 2010,” Washington, DC, January26, 2000.

Address for reprints: Frank Baker, Ph.D., Behav-ioral Research Center, American Cancer Society,1599 Clifton Road, Atlanta, GA 30329; Fax: (404)321-4669; E-mail: fbaker@cancer.org

Received June 28, 2002; revision received August29, 2002; accepted September 9, 2002.

*This article is a US Government work and, assuch, is in the public domain in the United Statesof America.

BACKGROUND. Data from the Health Care Financing Administration’s (HCFA)

Medicare Health Outcomes Survey (MHOS) of patients enrolled in managed care

services through Medicare were analyzed. The MHOS provided baseline estimates

of quality of life of cancer survivors in comparison to a frequency age-matched

cohort of noncancer patients.

METHOD. In 1998, the MHOS was mailed to a random sample of 279,135 benefi-

ciaries. Completed surveys were received from 167,096 respondents (60%). Some

22,747 respondents who had been diagnosed with cancer were frequency age

matched to an equal number of noncancer patients.

RESULTS. Cancer survivors had statistically significantly poorer scores than non-

cancer patients on all eight subscales as well as on the Physical Component and

Mental Component summary measures of the Medical Outcomes Study Short

Form-36 (MOS SF-36). Comparisons by type and number of cancers for which an

individual was currently in treatment showed lowest quality of life for those in

treatment for lung carcinoma, followed by those who were in treatment for more

than one type of cancer.

CONCLUSION. The data suggest that cancer shows negative effects on health-related

quality of life that are not explainable by simple effects of age because frequency

age-matched cancer survivors had statistically significantly lower scores on all 10

scores of the MOS SF-36. Effect sizes are evaluated to determine the clinical

significance of these differences in health-related quality of life. The MHOS offers

useful data for planning and improving cancer policy and programs. Cancer 2003;

97:674 – 81. Published 2003 by the American Cancer Society.*

DOI 10.1002/cncr.11085

KEYWORDS: quality of life, oncology, cancer survivors, managed care, Medicare,program planning, American Cancer Society, prostate carcinoma, breast carcinoma,colorectal carcinoma

Cancer occurs later in life, with nearly 80% of all cancers diagnosedamong individuals at 55 years and older.1 Currently, cancer is the

second leading cause of death in the United States.1 However, due toimprovements in prevention, early detection, and treatment, cancerdeath rates for all sites combined decreased an average of 0.6% peryear from 1990 to 1996.2 There are an estimated 8.9 million cancersurvivors in the United States.3 The term “cancer survivor” is definedin several ways. The traditional National Institutes of Health defini-tion of a cancer survivor was someone who had survived cancer for 5years and was disease free. The American Cancer Society (ACS) hasadopted a broader definition of a cancer survivor. Its definition in-cludes people from the time of their diagnosis with cancer and for thebalance of their lives, a definition that has been used by the National

674

Published 2003 by the American Cancer Society*

Coalition for Cancer Survivorship for a number ofyears.4 This is the definition used in this article.

The ACS has issued three cancer challenge goalsfor the year 2015, which include decreasing incidenceand mortality due to cancer. Recognizing that cancerand its treatment may result in physical impairmentsas well as psychosocial losses, these goals also includeimproving the health-related quality of life (HRQOL)of cancer survivors.5 Attempting to achieve any ofthese three goals poses formidable difficulties. How-ever, unlike incidence and mortality, quality of life hasthe additional problem of lacking a commonly agreedupon standard of measurement for assessing the cur-rent status of this variable and any progress that ismade in improving it.

Over the past two decades, increased attentionhas been given to developing HRQOL as an operation-ally defined patient-report based measure, and HRQOLhas become a standard outcome measure in cancerclinical trials.6,7 Recognition of the need to includeHRQOL as part of population-based assessments ofhealth status has also increased. The ACS is beginningto conduct its own population-based studies of theHRQOL, psychosocial adaptation, and changing needsof cancer survivors. However, this will take time, anddata are needed now to use as a guide for programdevelopment. The available data on the HRQOL ofcancer survivors are provided by relatively small op-portunistic samples. Because of the difficulties of sep-arating the effects of cancer on HRQOL from effectsthat are due to comorbid conditions and other lifechanges, additional data on a comparable sample ofnoncancer patients are needed for comparison.

The available data comparing the quality of life ofcancer survivors with individuals who have never hadcancer show little difference. A Canadian study8 com-pared the HRQOL of breast carcinoma survivors 8years after diagnosis. In that study, fewer cancer sur-vivors reported positive quality of life than similarlyaged controls, but these differences were small andnonsignificant. Another Canadian study9 comparedindex cancer cases with neighborhood controls of asimilar age and gender. The quality of life of the cancersurvivors was found to be similar to the neighborhoodcontrols. A French population-based case– controlstudy found that testicular carcinoma survivors with amean follow-up of 11 years did not differ significantlyin HRQOL from controls.10 A Swedish study11 compar-ing HRQOL in long-term head and neck carcinomasurvivors with general population norms showed nosignificant differences except on the role-physicalscale of the Medical Outcomes Study Short Form-36(MOS SF-36). These studies did not include U.S. sam-ples and were limited in sample size. This article com-

pares cancer survivors with noncancer patients in areasonably large sample of respondents.

In April 1999, the ACS hosted a conference inArlington, VA, to bring together major governmentagencies to identify possible collaborations and toshare information on how each was attempting tomeasure the HRQOL of various populations. This ar-ticle is the result of a successful collaboration initiatedat that meeting, i.e., a collaboration between the ACSand the Health Care Financing Administration (HCFA;recently renamed the Centers for Medicare and Med-icaid Services). The collaboration led to an analysis ofdata from the 1998 Medicare Health Outcomes Survey(MHOS) of patients receiving managed care servicesthrough Medicare. This analysis compared theHRQOL responses of cancer survivors with those offrequency age-matched respondents who were notcancer survivors, using the definition of cancer survi-vor as any person who is living after a diagnosis ofcancer.

MATERIALS AND METHODSSurvey InstrumentThe MHOS was developed by the National Committeefor Quality Assurance (NCQA) under contract to HCFAto measure the outcomes of care provided by Medi-care � Choice organizations to Medicare beneficiariesenrolled in these health plans. This performance mea-sure was included in the 1998 Health Plan EmployerData and Information Set (HEDIS 3.0) for Medicare. Atechnical expert panel of representatives from healthplans, health services researchers, and clinicians as-sisted in the development of the tool.12 Originallycalled the Health of Seniors survey and later renamedthe Medicare Health Outcomes Survey, the MHOSincluded a 95-item core and a five-item variable mod-ule.

MeasuresThe core instrument included a measure of HRQOLand questions to collect demographic information.The HRQOL measure was the MOS SF-36, a 36-itemwell tested, valid, and reliable self-report tool that hasbeen used in hundreds of studies world-wide to mea-sure HRQOL.13

The eight scales of the MOS SF-36 include thefollowing:

1. Physical functioning (PF). Ten questions that askthe extent to which health limits the performanceof physical activities.

2. Role-physical (RP). Four questions that ask indi-viduals the extent to which their physical health

Quality of Life of Cancer Patients/Baker et al. 675

limits them in their work or other usual activitiesin terms of time and performance.

3. Bodily pain (BP). Two questions that ask individ-uals about the severity of their pain and the extentto which pain interferes with normal work, includ-ing work outside the home and housework.

4. General health (GH). Five questions that ask indi-viduals to rate their current health status overall,their susceptibility to disease, and their expecta-tions for health in the future.

5. Vitality (VT). Four questions that ask individuals torate subjective well-being in terms of energy andfatigue.

6. Social functioning (SF). Two questions that askindividuals about limitations in normal socialfunctioning due specifically to health.

7. Role-emotional (RE). Three questions that askwhether emotional problems have interfered withaccomplishments at work or other usual activitiesin terms of time as well as performance.

8. Mental health (MH). Five questions that ask howfrequently the respondent experiences feelings re-lated to anxiety, depression, loss of behavioral oremotional control, and psychological well-being.

These eight scales provide the basis for calculatingtwo summary measures, the Physical ComponentSummary (PCS) and the Mental Component Summary(MCS). One additional question that asks the respon-dents to rate their general health compared to oneyear ago is also included but is not used in calculatingthe two summary measure scores. The MOS SF-36 isscored so that higher scores represent better function-ing on both the two summary measures and on alleight subscales. Norm based scaling is used so thatscores are standardized using normative values for thegeneral U.S. population. A score of 50 represents thenational average for both the summary scores and forthe subscales. A score that is 10 points above or belowthe mean score of 50 represents a difference of 1standard deviation from the national average.

ProceduresThe survey was sent to a random sample of 1,000Medicare beneficiaries continuously enrolled for atleast six months in each plan with a Medicare contractin place on or before January 1, 1997. In plans with1,000 or fewer Medicare enrollees, all eligible mem-bers were surveyed. The sampling frame included theaged and the disabled but excluded those eligible forMedicare because of end stage renal disease, sincethese patients are not eligible to enroll in a managed-care plan. To ensure the validity and reliability of thedata collected, plans were instructed to contract with

one of six NCQA-certified vendors for administrationof the survey. The survey was administered to the firstcohort at baseline (May 1998) and again to the samecohort in spring 2000. A new cohort will be selectedeach year for baseline measurement.

Cohort 1 data collection began in May 1998 andincluded 279,135 beneficiaries enrolled in 268 man-aged care plans covering 287 market areas. Completedsurveys were received from 167,096 respondents, araw response rate of 60%. Data files were aggregatedby NCQA and forwarded to HCFA’s data cleaning,analysis, and dissemination contractor, the HealthServices Advisory Group Health Outcomes Team. Ananalytic data set was created that merged plan char-acteristics from HCFA administrative data files withthe survey response data and patient demographicand entitlement information from the Medicare En-rollment Data Base. This augmented file was deliveredto HCFA in November 1998.

For purposes of this study, two separate files werecreated from the MHOS Cohort 1 final data set. Thefirst file consisted of all respondents who answeredpositively when asked if a physician had ever toldthem that they had any cancer other than skin carci-noma (Q33). This yielded 22,747 unique respondentswhom we defined as cancer survivors using the ACSdefinition of a cancer survivor as anyone still livingafter a cancer diagnosis.

The second data set created was a file of respon-dents who indicated that no physician had ever toldthem that they had cancer other than skin carcinoma.A frequency age-matched sample of noncancer pa-tients was randomly selected for inclusion in the an-alytic data set using 13 age categories: 29 or younger,30 –39, 40 – 49, 50 –59, 60 – 64, 65– 69, 70 –74, 75–79, 80 –84, 85– 89, 90 –94, 95–99, and 100 years or older. Weused a frequency age-matched cohort analytic ap-proach to better assess differences between cancersurvivors and those who had never been diagnosedwith cancer.

Data AnalysisBoth for those who were cancer survivors and thosewho were not, only individuals whose Medicare enti-tlement was based on being aged 65 or older wereincluded in the analyses. Individuals younger than 65(whose entitlement was based on a disability) werenot included. A single SAS data file including all indi-viduals who met these criteria (n � 43,757) was cre-ated for use in the analyses. One-way and two-wayanalyses of variance performed in PROC GLM wereused to compare mean MOS SF-36 standardizedscores. Tukey’s honestly significant difference (HSD)tests were used in post hoc testing. Chi-square tests in

676 CANCER February 1, 2003 / Volume 97 / Number 3

PROC FREQ were used for demographic comparisons.Multiple linear regression analyses to test for indepen-dent predictors of MOS SF-36 subscale and summaryscores were performed in PROC REG.

RESULTSTable 1 presents data on sample characteristics. Boththe cancer survivors and those who did not report

having been diagnosed with any cancer other thanskin carcinoma (hereafter referred to as the no-cancergroup or noncancer subjects) were equally dividedbetween the elderly (65–74 years old) and the olderelderly (75 years and older). Both groups had a some-what higher percentage of female than male respon-dents and were predominately white and non-His-panic. The majority of individuals in both groups werecurrently married and about 30% in each group werewidowed. About 30% of both groups had less than ahigh school education, and 34.4% of each group re-ported graduation from high school as their highesteducational attainment. Less than one-fifth in eachgroup reported an annual household income of lessthan $10,000, whereas less than one-third of eachgroup reported an annual household income of$10,000 –$19,999. Among the cancer survivors, 11.8%,5.4%, 3.0%, and 16.7%, respectively, reported currentlybeing in treatment for breast, colorectal, lung, or pros-tate carcinoma only. An additional 2.1% reported be-ing in treatment for more than one of these fourcancers.

Table 2 presents mean scores for the two sum-mary measures and for the eight subscales of the MOSSF-36 by cancer status (cancer survivor or no-cancergroup) and by age group (65–74 and 75 or older). Forthe entire sample and within each age group, cancersurvivors had significantly lower mean scores on all 10scales than did the noncancer subjects (all P � 0.001).As would be expected, individuals aged 65–74 hadsignificantly higher mean scores than those aged 75and older.

Effect size, which refers to the strength of a rela-tionship in a population or the degree of departurefrom a null hypothesis, offers a way to judge the clin-ical or practical importance of a result.14 Using a SD of10, it was determined that effect sizes were small (de-fined as 0.2– 0.4) for PC, PF, RP, GH, VT, and SF scales,with a range of 0.22– 0.30, corresponding to score dif-ferences of 2.2–3.0 points. The remaining four scales—MC, BP, RE, and MH— had effect sizes less than 0.2.Although four, the differences were statistically signif-icant for these four scales, they are not practicallysignificant, as judged by the magnitude of the effect.

Multiple linear regressions showed that havingbeen diagnosed with cancer was still a significant pre-dictor of MOS SF-36 summary and subscale scoreseven after the effects of a number of other variableswere taken into account. Variables for inclusion in theregression models were selected based on a technicalreport prepared for the HCFA and NCQA.15 Nonmed-ical variables included in the models were age (inyears), gender, race (white/nonwhite), Hispanic eth-

TABLE 1Sample Characteristics by Cancer Status: MHOS 1998 Baseline Data(n � 43,757)

Characteristic

Cancersurvivors No cancer

No. (%) No. (%)

Age group (yrs)65–74 10,969 (50.6) 11,137 (50.5)75 and older 10,716 (49.4) 10,935 (49.5)

Gendera

Male 9774 (45.1) 9126 (41.4)Female 11,911 (54.9) 12,946 (58.6)

Racea

American Indian 143 (0.7) 164 (0.8)Asian/Pacific Islander 231 (1.1) 414 (1.9)Black/African-American 1059 (5.0) 1396 (6.5)White 19,387 (91.5) 19,079 (88.6)Other or multiracial 351 (1.7) 481 (2.2)

Hispanica

Yes 697 (3.3) 965 (4.5)No 20,283 (96.7) 20,284 (95.5)

Material statusa

Married 12,582 (59.0) 12,347 (56.8)Divorced/separated 1904 (8.9) 1813 (8.3)Widowed 6387 (29.9) 7001 (32.2)Single, never married 459 (2.2) 577 (2.7)

Educationa

Less than HS 5993 (28.2) 6981 (32.5)HS/GED 7289 (34.4) 7413 (34.4)Some college/2-yr degree 4717 (22.2) 4252 (19.8)Four-year college degree 1543 (7.3) 1371 (6.4)More than 4-year college degree 1666 (7.9) 1477 (6.9)

Household incomea

Less than $10,000 2776 (15.8) 3200 (18.7)$10,000–$19,999 5501 (31.4) 5314 (31.0)$20,000–$49,999 7395 (42.2) 7028 (41.0)$50,000–$79,999 1244 (7.1) 1066 (6.2)$80,000 or more 608 (3.5) 535 (3.1)

Currently in treatment for N/A N/ABreast carcinoma only 2560 (11.8)Colorectal carcinoma only 1178 (5.4)Lung carcinoma only 651 (3.0)Prostate carcinoma only 3627 (16.7)In treatment for more than one

of the above 456 (2.1)

MHOS: Medicare Health Outcomes Survey; HS: high school; GED: general education.a Chi-square P value � 0.001 for comparing cancer survivors with those who reported not having been

diagnosed with any cancer other than skin carcinoma.

Quality of Life of Cancer Patients/Baker et al. 677

nicity (yes/no), annual income (�/� $20,000), maritalstatus (married/not married), education (�/� highschool graduate), home ownership (yes/no), and datacollection mode (paper/phone). In addition to cancer,the models included the following medical conditions:hypertension; angina or coronary artery disease; con-gestive heart failure; myocardial infarction; stroke;chronic obstructive pulmonary disease, emphysema,or asthma; Crohn disease, ulcerative colitis, or irritablebowel disease; arthritis of the hand or wrist; arthritis ofthe hip or knee; sciatica; and diabetes.

Table 3 shows regression results for variables thatwere significant in the multiple linear regression mod-els for the PCS and MH. Results for these two scales

are presented because they are typical of those for all10 scales with respect to the relative sizes of the esti-mated betas for cancer compared with those for othervariables that were also significant in the models. Inaddition, the betas for cancer for these two scalesrepresent the range of betas for cancer over the 10scales (from �0.777 to �2.573) because they are thesmallest (�0.777) and one of the largest (�1.979).

To investigate the effect of current treatment forcancer on MOS SF-36 mean scores, subjects were as-signed to one of seven groups: no cancer (n � 22,072);

TABLE 2Mean MOS SF-36 Standardized Scores by Cancer Status and AgeGroup: MHOS 1998 Baseline Data

MOS SF-36 scale

Mean (SD) for MOS SF-36 scale

Total sample(n � 43,757)

Age group (yrs)

65–74(n � 22,106)

> 75(n � 21,651)

PCSCancer 38.5 (12.0)a 40.6 (12.0)a 36.2 (11.7)a

No cancer 41.2 (11.8) 43.7 (11.3) 38.5 (11.7)MCS

Cancer 51.4 (10.7)a 52.1 (10.3)a 50.6 (11.1)a

No cancer 52.6 (10.0) 53.4 (9.4) 51.7 (10.5)Physical function

Cancer 38.3 (13.1)a 41.1 (12.5)a 35.4 (13.1)a

No cancer 40.5 (12.9) 43.7 (11.8) 37.2 (13.2)Role-physical

Cancer 40.6 (12.9)a 42.8 (12.8)a 38.2 (12.6)a

No cancer 43.0 (12.8) 45.7 (12.2) 40.3 (12.8)Bodily pain

Cancer 43.2 (11.4)a 44.2 (11.2)a 42.2 (11.4)a

No cancer 45.0 (11.2) 46.3 (10.7) 43.6 (11.4)General health

Cancer 43.0 (11.4)a 44.0 (11.4)a 41.9 (11.3)a

No cancer 46.0 (10.8) 47.5 (10.6) 44.6 (10.9)Vitality scale

Cancer 45.5 (11.2)a 47.0 (11.1)a 43.9 (11.1)a

No cancer 47.9 (10.8) 49.7 (10.4) 46.1 (10.9)Social function

Cancer 45.7 (12.8)a 47.3 (12.2)a 44.0 (13.3)a

No cancer 48.0 (11.7) 49.9 (10.5) 46.1 (12.5)Role-emotional

Cancer 47.2 (12.1)a 48.8 (11.4)a 45.5 (12.6)a

No cancer 48.3 (11.5) 50.1 (10.3) 46.4 (12.4)Mental health

Cancer 50.2 (10.6)a 50.8 (10.3)a 49.6 (10.8)a

No cancer 51.3 (10.2) 52.1 (9.7) 50.5 (10.5)

MOS SF-36: Medical Outcomes Study Short Form-36; MHOS: Medicare Health Outcomes Survey; SD:

standard deviation; PCS: Physical Component Summary; MCS: Mental Component Summary.a P � 0.001 for difference in mean scores between cancer and no-cancer patients.

TABLE 3Significant Variables from Multiple Linear Regression Analyses

VariableBetaestimate SE t P value

MOS SF-36 PCSAge (in single years) �0.350 0.010 �36.58 0.0001Education (less than high school

graduate) �1.571 0.140 �11.20 0.0001Household income (� $20,000/yr) �2.205 0.133 �16.56 0.0001Married �0.869 0.137 �6.35 0.0001Female �0.805 0.129 �6.23 0.0001Data collection via mail �0.550 0.221 �2.48 0.0131High blood pressure �1.451 0.121 �12.02 0.0001Angina or coronary artery disease �2.554 0.188 �13.57 0.0001Congestive heart failure �4.580 0.252 �18.20 0.0001Heart attack �0.516 0.228 �2.27 0.0233Stroke �3.880 0.221 �17.59 0.0001COPD, emphysema, or asthma �5.431 0.175 �31.08 0.0001Crohn disease, ulcerative colitis, or

irritable bowel disease �1.845 0.246 �7.50 0.0001Arthritis of the hand or wrist �2.015 0.137 �14.67 0.0001Arthritis of the hip or knee �5.296 0.136 �39.05 0.0001Sciatica �3.598 0.146 �24.62 0.0001Diabetes �2.504 0.164 �15.24 0.0001Cancer �1.979 0.117 �16.87 0.0001

MOS SF-36 MHAge (in single years) �0.062 0.009 �6.80 0.0001Education (less than high school) �2.663 0.134 �19.91 0.0001Household income (� $20,000/yr) �1.816 0.128 �14.23 0.0001Hispanic �1.661 0.303 �5.48 0.0001Female �0.896 0.124 �7.24 0.0001Data collection via mail �0.918 0.213 �4.30 0.0001High blood pressure �0.822 0.116 �7.10 0.0001Angina or coronary artery disease �0.941 0.180 �5.24 0.0001Congestive heart failure �2.305 0.240 �9.62 0.0001Stroke �3.375 0.210 �16.08 0.0001COPD, emphysema, or asthma �2.666 0.167 �15.95 0.0001Crohn disease, ulcerative colitis, or

irritable bowel disease �3.915 0.236 �16.61 0.0001Arthritis of the hand or wrist �1.376 0.132 �10.46 0.0001Arthritis of the hip or knee �0.998 0.130 �7.68 0.0001Sciatica �2.034 0.140 �14.53 0.0001Diabetes �1.049 0.157 �6.67 0.0001Cancer �0.777 0.112 �6.91 0.0001

MOS SF-36: Medical Outcomes Study Short Form-36; PCS: Physical Component Summary; MH: Mental

Health; COPD: Chronic obstructive pulmonary disease.

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cancer but not currently in treatment for breast, colo-rectal, lung, or prostate carcinoma (n � 10,930); cur-rently in treatment for prostate carcinoma only (n� 3,627); currently in treatment for breast carcinomaonly (n � 2,560); currently in treatment for colorectalcarcinoma only (n � 1,178); currently in treatment forlung carcinoma only (n � 651); and currently in treat-ment for more than one of these four cancers (n� 456). Means and post hoc testing results for the twosummary measures and eight subscales are shown inTable 4. Generally, mean scores are ordered fromhighest to lowest in the following sequence: no cancer;cancer not currently in treatment for breast, colorec-tal, lung, or prostate carcinoma; in treatment for pros-tate carcinoma only; in treatment for breast carci-noma only; in treatment for colorectal carcinomaonly; in treatment for more than one cancer; and intreatment for lung carcinoma only. For all 10 scales,those currently in treatment for lung carcinoma onlyor for more than one cancer had significantly lowermean scores than any of the other five groups. Thosewho had not been diagnosed with cancer had thehighest mean score on all 10 scales and their mean foreach scale was significantly higher than the means forany of the five in treatment groups except the group intreatment for prostate carcinoma only (which differedsignificantly from noncancer subjects on 5 of the 10scales). Mean scores for those in treatment for breastcarcinoma only or for colorectal carcinoma only wereconsistently lower than the means for those beingtreated for prostate carcinoma only and were consis-tently higher than means for those being treated for

lung carcinoma only or for more than one of the fourlisted cancers.

Although the effect sizes for the overall cancergroup compared with the noncancer group were smallor nonexistent, larger effect sizes were found whenusing the treatment groups described above for com-parison to the noncancer group. For example, theeffect size for GHS for those currently in treatment forcolorectal carcinoma was 0.55 (moderate) and the ef-fect size for PCS for those currently in treatment forlung carcinoma was 1.02 (large), corresponding toscore differences of 5.5 and 10.2 points. The effectsizes can be summarized as follows for each treatmentgroup compared with the noncancer group: currentlynot in treatment for breast, colorectal, prostate, orlung carcinoma; 0.03– 0.19 (no effect for all scales); intreatment for prostate carcinoma only, 0.05– 0.34 (noeffect except small effect for GHS and RPS); in treat-ment for breast carcinoma only, 0.17– 0.39 (small ef-fects for all except MCS and MHS); in treatment forcolorectal carcinoma only, 0.27– 0.55 (small effects forall except GHS and SFS, which were moderate); intreatment for more than one of the four cancers, 0.48 –0.90 (large effects for GHS and SFS, moderate for allothers except BPS, which was small); and in treatmentfor lung carcinoma only, 0.52–1.15 (large effects forPCS, PFS, RFS, GHS, VTS, and SFS, moderate for allothers).

DISCUSSIONThe central purpose of this article is to compare thequality of life of a large national sample of cancer

TABLE 4Mean MOS SF-36 Standardized Scores by Cancer/Treatment Status: MHOS 1998 Baseline Data

MOS SF-36 scaleNo cancer(n � 22,072)

Cancer but notin treatment(n � 10,930)a

Prostatecarcinoma intreatment(n � 3627)

Breast carcinomain treatment(n � 2560)

Colorectalcarcinoma intreatment(n � 1178)

In treatmentfor more thanone cancer(n � 456)b

Lung carcinomatreatment(n � 651)

PCSc 41.2d 39.3e 39.0e 37.3f 36.9f 34.1g 31.0h

MCSc 52.6d 52.1d,e 51.9d,e 50.9e 49.1f 46.2g 47.0g

Physical functioningc 40.5d 39.0d 40.0d 36.6e 36.5e 33.5f 30.4d

Role-physicalc 43.0d 41.5e 40.5e,f 39.9f 38.3g 35.3h 33.7f

Bodily painc 45.0d 43.8d 43.8d 41.8e 42.3e 40.2f 38.9f

General healthc 46.1d 44.2e 42.7f 42.6f 40.6g 37.1h 34.6i

Vitality scalec 47.9d 46.1e 46.2e 45.0e,f 43.9f 41.5g 38.8h

Social functioningc 48.0d 46.8d,e 46.1e,f 45.0f 42.9g 39.5h 37.4i

Role-emotionalc 48.3d 48.0d 47.7d 46.3b 44.6f 40.9h 43.0g

Mental healthc 51.3d 50.8d 51.1d 49.6b 48.5e 46.0f 46.1f

MOS SF-36: Medical Outcomes Study Short-Form 36; MHOS: Medicare Health Outcomes Survey; PCS: Physical Component Summary; MCS: Mental Component Summary.a Not currently in treatment for breast, colorectal, lung, or prostate carcinoma.b Currently in treatment for more than one of the following carcinoma: breast, colorectal, lung, prostate.c P � 0.001 for difference in mean scores across cancer/treatment groups in one-way analysis of variance.d–i Tukey groupings in post hoc testing; means within the same Tukey grouping are not significantly different from one another.

Quality of Life of Cancer Patients/Baker et al. 679

survivors who completed the MOS SF-36 as part of theMHOS with that of a frequency age-matched sampleof noncancer MHOS respondents. No claim is madethat this sample of managed care recipients in theMedicare program is representative of the Medicarepopulation. However, this data set provides informa-tion on a large sample of people 65 and older whohave access to care through Medicare, some of whomhave received a diagnosis of cancer at some point intheir lives, and on an age-comparable group who havenot been diagnosed with cancer.

As a basis for examining the quality of life ofcancer survivors, the MOS SF-36 has a number ofstrong practical advantages. Among its strengths is itsapplicability to many disease groups as well as thegeneral population, so that it can be used to makecomparisons between cancer patients and patientswith other diseases as well as healthy populations.Since most studies of the quality of life of cancersurvivors lack either a non-cancer control group orbroad normative data on non-cancer patients againstwhich to compare findings, this is a very importantadvantage in attempting to sort out the contributionof cancer and cancer treatment to differences in qual-ity of life versus the effects of comorbitidites and nat-ural aging.

Research documents the responsiveness of thescales and summary scores of the MOS SF-36 to vari-ous treatment interventions.16 Findings indicate thatsmall absolute differences in scores are clinicallymeaningful. For instance, a study documented thatuntreated asthmatics reported a PCS score 3.7 pointslower than asthmatics treated with drugs. Anothershowed that people suffering from a migraine head-aches reported an increase in PCS score of 2.09 pointswhen their headache was treated. Therefore, the dif-ference in mean physical functioning between cancersurvivors in our study (mean PCS score � 38.5) and inthe noncancer group (mean PCS score � 41.2) can belikened to the increase in physical limitations experi-enced when suffering from untreated migraine head-ache, which is clinically meaningful. Clinical signifi-cance of the differences found in our study is alsoevidenced by the effect sizes seen, especially withregard to the impact of treatment status on HRQOL.

Our data show that cancer patients have statisti-cally significantly poorer quality of life than noncancerrespondents as measured by all eight subscales of theMOS SF-36 and the two summary measures even afterconsidering the effects of other variables. These dif-ferences in HRQOL, however, represented small ef-fects for five of the eight MOS SF-36 subscales. Of thesummary measures, only the PCS showed a small ef-fect. The effect size for MCS did not indicate any

practical significance. These data support the viewthat cancer is a uniquely traumatizing event, produc-ing broad negative impact on a variety of dimensionsof a survivor’s HRQOL.

Secondary analysis of data collected for broaderpurposes can limit the questions one can ask of thesedata. One limitation of this data is the absence ofinformation on the time since cancer diagnosis. Al-though these data do not allow clear analysis by stageof recovery, there is evidence in these results thatpatients who have access to care through Medicaremanaged care continue to have serious biomedicaland psychosocial HRQOL problems. This should re-ceive further attention, particularly as these quality-of-life dimensions are significantly worse for the can-cer survivors than for same-age controls who have nothad to deal with the physical and psychosocial se-quelae of cancer.

These data also allow a comparison by type andnumber of cancers for which a subject is currentlybeing treated. Analyses were made across the condi-tion of having no cancer; having a cancer diagnosisbut not in treatment for breast, colorectal, lung, orprostate carcinoma; or in treatment for one or more ofthese four common types of cancer. As these analysesshow, those who had not been diagnosed with cancerhad statistically significantly higher HRQOL scores. Incontrast to the small effects found when comparingcancer survivors overall with the noncancer group,larger effects were found when the comparisons weremade across treatment status. Being in treatment forlung carcinoma only or in treatment for more thanone type of cancer had the most negative effect onquality of life. The general pattern showed the highestMOS SF-36 scores for individuals without cancer, fol-lowed by those not in treatment for breast, colorectal,lung, or prostate carcinoma; only prostate in treat-ment; only breast in treatment; only colorectal intreatment; treatment for more than one type of can-cer; and only lung in treatment. For all 10 MOS SF-36scales, being in treatment either for lung carcinomaonly or for more than one type of cancer resulted instatistically significantly poorer HRQOL. Moderate orlarge effects were found for all 10 MOS SF-36 scoreswhen comparing those in treatment for lung carci-noma only with the noncancer group. For those intreatment for more than one of the four cancers, mod-erate or large effects were found for all 10 MOS SF-36scales except for the BPS, which showed a small effect.These data show that the severity and range of effectsof particular types of cancer and the varied treatmentsoffered for various cancer sites produce different ef-fects on HRQOL. However, the development of severalmalignancies is particularly difficult for patients. Hav-

680 CANCER February 1, 2003 / Volume 97 / Number 3

ing to fight cancer on several different fronts poses acascade of complex HRQOL challenges.

Previous studies employing the MOS SF-36 havefound that older age groups (particularly 75 and older)show lower scores on the eight scales of the MOSSF-36.17,18 Consistent with these earlier findings, the75 and older group in this study had significantlylower scores than the 65–74 group on all 10 scales. It isnoteworthy that even in the 75 and above age group,those with a cancer history continued to have signifi-cantly lower scores than the noncancer group.

There are some limitations to using the MOSSF-36 to describe the HRQOL of cancer patients. Itsstrength in being a generic measure that can be usedto assess functional outcomes across many medicalconditions, both acute and chronic, as well as withhealthy populations, also provides a limitation. It doesnot include data on domains that measure the specificeffects of particular diseases such as cancer and itsvarious treatments. Therefore, it does not reveal asmuch as one might like in terms of well delineatedareas for intervention.

However, the MOS SF-36 as it is included in theMHOS offers important and relevant data for thoseconcerned with planning, evaluating, and improvingcancer policy and programs. Because the MHOS wasrepeated again after 2 years with this 1998 cohort,when data are available for analysis, changes in scoresmay also reveal patterns of interest to program plan-ners. Furthermore, the continued administration ofthe MHOS to new cohorts each year will provide datathat may be useful in tracking changes in HRQOLrelated to the efforts of the ACS and its partners toimprove the quality of life of cancer survivors over thenext 15 years.

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