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TCR TUMOUR MATCHING TCR TUMOUR MATCHING ALGORITHMALGORITHM

The structure of the algorithm - Heather Bourne

Using the algorithm - Jason Hiscox

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CURRENT METHOD OF TUMOUR CURRENT METHOD OF TUMOUR MATCHINGMATCHING

The UKACR multiple primary rules are interpreted by the registry staff entering the data.

Usually…Usually…In general...In general...

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AUTOMATING TUMOUR MATCHINGAUTOMATING TUMOUR MATCHING

In order to carry out tumour matching automatically the computer must be

able to make the value judgements once made by cancer registry staff-

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THE TCR TUMOUR MATCHING THE TCR TUMOUR MATCHING ALGORITHM (1)ALGORITHM (1)

• In order to automate the registration of patients with multiple records the decision making process had to be reduced to a series of “yes/no/don’t know” questions covering all eventualities.

• Two comprehensive reference tables were produced with entries

for all values between:

- M8000 and M9989 for morphology and

- 140.0 and 199.9 (ICDO-1) or C00.0-C80.9 (ICDO-2) for

topography

• An algorithm was then written to allow all conceivable topography and morphology pairs to be processed appropriately.

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THE TCR TUMOUR MATCHING ALGORITHM (2)THE TCR TUMOUR MATCHING ALGORITHM (2)

• The algorithm looks at: 1. MORPHOLOGY

2. TOPOGRAPHY

3. BEHAVIOUR

4. SIDE

to see if they are: 1. THE SAME

2. DIFFERENT

3. QUERY - manual check required

• The morphology and topography codes are assigned to groups in the morphology and topography tables and the algorithm then carries out a number of tests to establish whether or not the values should match or be checked manually.

• Any values that have not been matched or sent for checking are treated as being different.

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TCR TUMOUR MATCHING ALGORITHM (3)TCR TUMOUR MATCHING ALGORITHM (3)

Morphologiesdefined as equal?

NO ?Query formanual

resolution

YES

Topographiesdefined as equal?NO2 registrations ?

Query formanual

resolution

YES

Behaviourthe same?NO

Query formanual

resolution

Laterality thesame?

NOQuery for manual

resolution

YES

Records match, make one registration only

There were found to be too many errors in the source data to allow records with different values for behaviour and laterality to be processed automatically.

YES

2 registrations

Pre-match validation is carried out to ensure that all records entering the matching process are as accurate as possible.

The algorithm has 4 basic steps, each of which attempts to prove that the 2 tumours are different. If, after the 4th step, no differences have been identified one registration only is made.

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STEP 1STEP 1MORPHOLOGY (a)MORPHOLOGY (a)

The morphology matching table assigns each morphology code to a group of codes considered to be “the same”. e.g.

Some lines from the morphology table:

8000-8004 = 1A (= Neoplasm NOS )

8010-8011 = 1B (= Carcinoma NOS). . . .

. . . .

8149-8157 = 6A (= Specific digestive adenocarcinomas (neuroendocrine))

8160-8180 = 6B (= Specific liver and bile duct carcinomas). . . .

. . . .

9591-9592 = 36B (= Non-Hodgkin’s lymphoma NOS)

9601-9601 = 36B “ “ “

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STEP 1STEP 1MORPHOLOGY (b)MORPHOLOGY (b)

The algorithm treats all morphologies in the same group as being “the same”,

but 3 types of processing are carried out:

1 Certain automatic inter-group MATCHES are allowed, e.g.

- Carcinoma NOS (group 1B) matches with:

any other epithelial malignancy (groups 1-15)

- Myeloid leukaemia NOS (group 50) matches with:

specified types of myeloid leukaemia (groups 50A-50C)

2 Some morphology group pairs are sent for MANUAL RESOLUTION, e.g.

- Germ cell neoplasms (group 21) are checked against trophoblastic tumours (group 22)

- Germ cell neoplasms (group 21) are checked against carcinoma NOS

(group 1B)

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STEP 1STEP 1MORPHOLOGY (c)MORPHOLOGY (c)

3 A series of steps has been added to the algorithm to cope with

POORLY CODED SOURCE DATA, e.g.

• One type of sarcoma is checked against any other type of sarcoma,

spindle cell or pseudosarcomatous carcinoma or tumour.

• Any case where the morphologies have not matched, but where:

. the dates of diagnosis are within 100 days, or where

. the tumour site is the same

are sent for checking.

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STEP 2STEP 2TOPOGRAPHY(a)TOPOGRAPHY(a)

• The topography matching table assigns each topography code to a value for processing.

• The values used correspond with ICD10 values, e.g. rectosigmoid junction, rectum and anus are allocated separate values.

• Any other topography codes with which a code should match, and any site combinations that require checking are given in separate columns in the table.

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STEP 2STEP 2(b) TOPOGRAPHY TABLE(b) TOPOGRAPHY TABLE

Some lines from the topography table:

Site Morphology Query with Match with Group(Caecum) 153.4 - 020,022+025 031 023

(Rectum) 154.1 - 031+032 - 033.X

(Connective 171.3 <M949 058.2-3,059.X - 060.2

tissue, leg) 061.2,061.X,062.7

(Peripheral 171.3 M949-956 058.2-3,059.X - 061.2

nerve, leg) 060.2,060.X,062.7

Key:

020 = Ileum 058.2 = Long bone of leg 062.7 = skin of leg

022 = small intestine NOS 058.3 = Short bone of leg

025 = Ascending colon 059.X = Bone NOS Other parts of the table also connect

031 = Colon NOS 060.2 = Connective tissue of leg caecum & rectum to gastrointestinal tract NOS,

032 = Rectosigmoid junction 060.X = Connective tissue NOS & all the sites listed to primary site not known.

033.X = Rectum 061.2 = Peripheral nerve of leg

061.X = Peripheral nerve NOS

In order to reduce the amount of work involved in producing the table there is only one entry for each match or query. Therefore the table must be accessed for both the tumour sites being compared.

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STEP 2STEP 2 TOPOGRAPHY (c) TOPOGRAPHY (c)

Most of the processing of the topography codes is carried out within the topography

table. Two topographies are regarded as being equal if:

• The internal values to which they have been assigned are equal, or• One is a more general term for the other.

A series of processes has been added to deal with special cases and poorly

coded data, e.g.:• If one or both morphologies are site specific and the appropriate site code does

not appear in either record the case is checked.

When the 2 tumours appear to be at different sites a series of tests is carried out

to avoid duplicate registrations e.g.:• To check that one is not a metastasis from the other.• Records for non-melanoma skin cancers are merged according to UKACR rules.

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STEP 3STEP 3TUMOUR BEHAVIOURTUMOUR BEHAVIOUR

• Two records are matched only if the behaviour code recorded for each is the same.

• Any pair of records where the behaviour codes are different is resolved manually.

We found that differences in behaviour code were just as likely to be the result

of error as to be genuine.

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STEP 4STEP 4LATERALITYLATERALITY

• Two records are matched only if the laterality recorded for each is the same.

• Any pair of records where the laterality recorded is different is resolved manually.

We found that differences in laterality were just as likely to be the result of

error as to be genuine.

Notes:

• Not known, and either right, left or bilateral are considered to be the same.

• Bilateral, and either right or left are not considered to be the same.

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USING THE TUMOUR MATCHING USING THE TUMOUR MATCHING ALGORITHMALGORITHM

The algorithm has been used for:

• Processing electronic data from a number of sources

• A nightly QA check for duplicate registrations in all data entered at the registry on the previous day.

The basic algorithm seems to be stable and working well. Most of the

amendments made now are to cope with poorly coded source data.

However, there are some cases that could be termed “casualties” of electronic

tumour matching, where the coding of the source data defies logic. To cope

with these:

• Some cases fail the nightly consistency checks, but

• The standard site/histology consistency checks need to be tightened up.

To do this a table of unusual diagnoses is being prepared.

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TCR TUMOUR MATCHING TCR TUMOUR MATCHING ALGORITHMALGORITHM

The structure of the algorithm - Heather Bourne

Using the algorithm - Jason Hiscox

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Source Information ManualPatient Tumour Source Site ICD-O-2 T SnomedICD-10 MorphologyDate Laterality Merge?

1 a Hosp Oesophagus C15.9 22.08.1993 Definite Match1 b Hosp Oesophagus C15.9 09.04.19992 a Hosp Nasal Cavity C30.0 25.05.1999 Definite Match2 b Path Nasal Cavity C30.0 T2X120 M87203 05.06.19993 a Path Stomach Cardia C16.0 T63300 M80103 12.07.1999 Definite Match3 b Path Stomach NOS C16.9 T63000 M81403 15.07.19994 a Hosp Colon C18.9 01.09.1999 Definite Match4 b Path Caecum C18.0 T67100 M81403 02.09.19995 a Path UOQ Breast C50.4 T04004 M85203 11.03.1996 Left5 b Path Breast C50.9 T04020 M85003 12.11.1999 Right6 a Path Rectum C20.9 T68000 M81403 15.07.1998 New Tumour6 b Path Ascending Colon C18.2 T67200 M81403 15.07.19987 a Hosp Chronic Lymphoid Leukaemia C91.1 15.06.1995 Definite Match7 b Haem Bone Marrow C42.1 T06000 M98233 21.06.19958 a Path Skin NOS C44.9 T01000 M80703 24.07.1999 Definite Match8 b Hosp Skin of Scalp C44.4 23.07.19999 a Path Breast C50.9 T04030 M85002 12.05.1997 Left New Tumour9 b Path UIQ Breast C50.2 T04032 M85003 31.05.1999 Left10 a Hosp Low er Lobe Lung C34.3 18.04.1999 Left Definite Match10 b Cyt Pleural Cavity C38.4 T2Y700 M80006 19.04.199911 a Path Breast C50.9 T04000 M85003 21.11.199711 b Cyt Pleural Cavity C38.4 T2Y700 M80106 04.06.199912 a Path Skin NOS C44.9 T01000 M87203 03.09.1999 Definite Match12 b Path Skin of Trunk C44.5 T02400 M87423 27.10.199913 a Path Transverse Colon C18.4 T67400 M84803 09.03.199813 b Path Splenic Flexure of Colon C18.5 T67500 M81403 25.12.199914 a Cyt Peritoneal Fluid C48.2 T6X930 M81406 24.03.1999 Definite Match14 b Path Ovary C56.9 T87010 M84403 30.03.1999 Right15 a Hosp Non Hodgkin's Lymphoma NOS C85.9 13.08.199815 b Hosp Hodgkin's Disease Mixed cellularity C81.2 29.01.199916 a Path Bladderneck of C67.5 T74400 M81211 15.05.1990 Definite Match16 b Path Bladder NOS C67.9 T74000 M80001 03.03.200017 a Haem Bone Marrow C42.1 T06000 M98233 31.03.1991 Definite Match17 b Haem Bone Marrow C42.1 T06000 M98213 16.11.199918 a Cyt Cervix Uteri C53.9 T8X310 M74008 15.02.2000 Definite Match18 b Path Cervix Uteri C53.9 TP1148 M80772 02.03.2000

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Source Information Manual TCR HistoryPatient Tumour Merge? TCRmult2 TCRmult3 1st July 2000 29th Aug 2000 31st Aug 2000 31st Aug 2000 1st Sept 2000

1 a Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match1 b2 a Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match2 b3 a Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match3 b4 a Definite Match New Tumour Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match4 b5 a New Tumour New Tumour New Tumour New Tumour New Tumour New Tumour5 b6 a New Tumour New Tumour New Tumour New Tumour New Tumour New Tumour New Tumour New Tumour6 b7 a Definite Match New Tumour Definite Match Definite Match Definite Match Definite Match7 b8 a Definite Match Definite Match New Tumour New Tumour Definite Match Definite Match Definite Match Definite Match8 b9 a New Tumour9 b10 a Definite Match10 b11 a11 b12 a Definite Match New Tumour Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match12 b13 a New Tumour13 b14 a Definite Match14 b15 a Definite Match Definite Match Definite Match Definite Match15 b16 a Definite Match New Tumour New Tumour Definite Match Definite Match Definite Match Definite Match Definite Match16 b17 a Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match Definite Match17 b18 a Definite Match18 b

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Outcomes (TCR v4.0)Outcomes (TCR v4.0)

No Match Query MatchExclude 14%Morphology 14% 17%Topography 10% 13% 1%Behaviour 4%Laterality 1% 26%Totals 24% 49% 27%

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Outcomes (TCR v5.1)Outcomes (TCR v5.1)

No Match Query MatchExclude 14%Morphology 4% 28%Topography 2% 21% 1%Behaviour 4%Laterality 1% 25%Totals 6% 68% 26%

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Differences (v4.0 vs. v5.1)Differences (v4.0 vs. v5.1)

• Fewer definitive decisions in later algorithm• but ENCR test cases are designed to be difficult /

awkward!!!

• Are these results the same with real-life data?

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Outcomes (Cancer Deaths)Outcomes (Cancer Deaths)

No Match Query MatchExclude 5%Morphology 5% 2%Topography 7% 12%Behaviour 2%Laterality 68%Totals 12% 20% 68%

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Outcomes (Tertiary Centre)Outcomes (Tertiary Centre)

No Match Query MatchExclude 8%Morphology 11% 5%Topography 2.5% 10% 0.3%Behaviour 4%Laterality 2.5% 56%Totals 13.5% 29.5% 56%

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Differences (Dths vs. Hospital)Differences (Dths vs. Hospital)

• Quality of behaviour coding• More metastatic behaviour (Hospital) -> more

excluded / queried

• Quality of topography coding• More inappropriately coded (e.g. site=blood)

records (Hospital) -> more excluded / queried

• Quality of morphology coding• more specific codes (Hospital) -> more rejected as

‘no match’ at morphology comparison stage

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SummarySummary

• Acceptable performance depends on• Quality of incoming diagnosis data

• 100% definitive decision making is not possible

• Matching algorithms need• continual assessment vs. real life (70-80% definite

decisions made on real life data compared to 30-40% on test data)

• to be flexible

• to be conservative

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Thank you!Thank you!

Any Questions?Any Questions?