Difficulties for the analysis of rare cancers

• Missing casesExample: angiosarcoma of liver

• Including false casesExample: malignant digestive endocrine

tumours

Difficulties for the technician

to record rare cancers

- Unusual morphology in pathologic records seems commonly easy to identify for technicians

- Pathologists themselves are not experts in these cancers the conclusion of their reports may often be not clear

It may be difficult to identify the morphologic code corresponding to these cases

IARC SCIENTIFIC PUBLICATIONS, 1997 Chapter 4. Histological groupsD.M. Parkin, J. Ferlay, K. Shanmugaratnam, L. Sobin, L. Teppo and S.L. Whelan

Example: angiosarcoma of liver: very rare and not well known

Various codes in the literature , ~ 200 annual new cases per year …?

Example : How to choose the good code for angiosarcoma of liver ?

Survival from rare cancer in adults: a population-based studyThe Lancet Oncology, 2006

Morphologic codes accepted whatever the topography Angiosarcoma ?

(8800/3) Sarcoma

(8804/3) Epithelioid sarcoma

(8850/3) Liposarcoma

(8860/3) Angio myoliposarcoma

(8890/3) Leiomyosarcoma

(8894/3) Angiomyosarcoma

(8895/3) Myosarcoma

(8900/3) Rhabdomyosarcoma

(9120/3) Hemangiosarcoma

(9124/3) Küpfer cell sarcoma (C22)

(9130/3) Hemangioendothelioma

(9133/3) Epithelioid hemangioendothelioma

(9140/3) Kaposi's sarcoma

(9161/3) Hemangioblastoma

Example : How to choose the good code for angiosarcoma of liver ?

Survival from rare cancer in adults: a population-based studyThe Lancet Oncology, 2006

Morphologic codes accepted whatever the topography Angiosarcoma ?

(8800/3) Sarcoma no

(8804/3) Epithelioid sarcoma no

(8850/3) Liposarcoma no

(8860/3) Angio myoliposarcoma no

(8890/3) Leiomyosarcoma no

(8894/3) Angiomyosarcoma no

(8895/3) Myosarcoma no

(8900/3) Rhabdomyosarcoma no

(9120/3) Hemangiosarcoma yes

(9124/3) Küpfer cell sarcoma (C22) yes

(9130/3) Hemangioendothelioma yes

(9133/3) Epithelioid hemangioendothelioma yes

(9140/3) Kaposi's sarcoma no

(9161/3) Hemangioblastoma yes ?

Proposal for rare cancers

• Identification in the database of rare cancers by a inedited specific code (XXXX)

• Precise codification of the morphologic code in a second variable after validation by a pathologist and/or a clinician

This aims in an:

- improvement in the identification and the extraction of rare cancers- improvement in the quality of data

Malignant digestive endocrine tumours (mdet)

• Not so rare (~ 0.8/100 000)

• But difficulties with the rules of codification :

– Heterogeneity of this group of cancer arising from diverse sites

– How to distinguish between benign and malignant tumours

– Changes in the classification over time

Well differentiated

benign ET

Well differentiatedborderline ET

Well differentiatedendocrine carcinoma

undifferentiated endocrine

carcinoma

Differenciation Well differentiated Well differentiated Well differentiated Undifferentiated

Angioinvasion No Possible Possible Possible

Size Stomach, Small intestine: < 1cm Appendix, colon, rectum : < 2 cm Pancreas : < 2 cm

Stomach, Small intestine : >1 cm

Appendix, colon, rectum : > 2 cm Pancreas : > 2cm

Stomach, Small intestine : >1 cm

Appendix, colon, rectum : > 2 cm

Pancreas : >3 cmo

 

Mitotic Index < 2 Pancreas > 2 2 to 10 > 10

Proliferation Index (Ki67)

< 2 % often > 2 % 2 to 15 % > 15 %

local invasion Digestive tumour :mucosae/submucosae Pancreas : intra-pancreatic

Digestive tumour :mucosae/muscularis propria Pancreas : intra-pancreatic

Digestive tumour (out appendix):> Muscularis propria  Appendix : invasion of the visceral peritoneumPancreas : extra-pancreatic extension

 

Metastases no no Possible Possible/ 3Behaviour : / 2

Mdet : difficulties with the rules of codification

Example : colon cancers. High frequency of appendix mdet, usually benign

country

hepatic

flexure transverse lef t colon caecum appendix ascending nos Total

AUSTRI A 0 0 2 5 11 1 18 37

CZECH REPUBLI C 1 0 2 1 0 2 1 7

DENMARK 1 7 26 78 64 26 8 210

ENGLAND 13 19 41 204 259 29 100 665

ESTONI A 0 5 2 15 6 8 9 45

FI NLAND 0 0 14 0 0 0 11 25

FRANCE 3 1 11 18 8 13 3 57

GERMANY 0 2 3 10 12 0 15 42

I CELAND 0 0 3 5 0 3 1 12

I TALY 2 4 13 32 29 12 12 104

MALTA 0 0 0 1 0 1 0 2

NORWAY 104 8 14 0 0 66 4 196

POLAND 1 0 2 1 4 0 3 11

PORTUGAL 0 0 1 1 0 0 1 3

SCOTLAND 2 1 12 46 55 7 15 138

SLOVAKI A 1 5 10 29 27 6 0 78

SLOVENI A 16 2 1 0 0 0 1 20

SPAI N 1 0 4 12 17 4 3 41

SWEDEN 0 24 35 0 0 284 76 419

SWI TZERLAND 0 0 1 6 6 2 0 15

THE NETHERLANDS 1 1 10 23 177 6 2 220

WALES 0 0 0 12 17 1 13 43

Eurocare, 1985-1994

Example : colon cancers. High frequency of appendix mdet, usually benign

country

hepatic

flexure transverse lef t colon caecum appendix ascending nos Total

AUSTRI A 0 0 2 5 11 1 18 37

CZECH REPUBLI C 1 0 2 1 0 2 1 7

DENMARK 1 7 26 78 64 26 8 210

ENGLAND 13 19 41 204 259 29 100 665

ESTONI A 0 5 2 15 6 8 9 45

FI NLAND 0 0 14 0 0 0 11 25

FRANCE 3 1 11 18 8 13 3 57

GERMANY 0 2 3 10 12 0 15 42

I CELAND 0 0 3 5 0 3 1 12

I TALY 2 4 13 32 29 12 12 104

MALTA 0 0 0 1 0 1 0 2

NORWAY 104 8 14 0 0 66 4 196

POLAND 1 0 2 1 4 0 3 11

PORTUGAL 0 0 1 1 0 0 1 3

SCOTLAND 2 1 12 46 55 7 15 138

SLOVAKI A 1 5 10 29 27 6 0 78

SLOVENI A 16 2 1 0 0 0 1 20

SPAI N 1 0 4 12 17 4 3 41

SWEDEN 0 24 35 0 0 284 76 419

SWI TZERLAND 0 0 1 6 6 2 0 15

THE NETHERLANDS 1 1 10 23 177 6 2 220

WALES 0 0 0 12 17 1 13 43

30%

40%

80%

39%

Eurocare, 1985-1994

small cell mdet well- diff erentiated total

AUSTRI A 1 89 90

CZECH REPUBLI C 8 32 40

DENMARK 119 713 832

ENGLAND 757 1,955 2,712

ESTONI A 64 121 185

FI NLAND 0 1,56 1,56

FRANCE 8 332 340

GERMANY 35 168 203

I CELAND 8 105 113

I TALY 81 374 455

MALTA 1 12 13

NORWAY 32 923 955

POLAND 20 23 43

PORTUGAL 3 4 7

SCOTLAND 199 415 614

SLOVAKI A 54 204 258

SLOVENI A 19 63 82

SPAI N 40 131 171

SWEDEN 0 3,943 3,943

SWI TZERLAND 12 133 145

THE NETHERLANDS 42 419 461

WALES 42 122 164

Example : mdet Eurocare. Information on the differentiation, a major pronostic factor

small cell mdet well- diff erentiated total

AUSTRI A 1 89 90

CZECH REPUBLI C 8 32 40

DENMARK 119 713 832

ENGLAND 757 1,955 2,712

ESTONI A 64 121 185

FI NLAND 0 1,56 1,56

FRANCE 8 332 340

GERMANY 35 168 203

I CELAND 8 105 113

I TALY 81 374 455

MALTA 1 12 13

NORWAY 32 923 955

POLAND 20 23 43

PORTUGAL 3 4 7

SCOTLAND 199 415 614

SLOVAKI A 54 204 258

SLOVENI A 19 63 82

SPAI N 40 131 171

SWEDEN 0 3,943 3,943

SWI TZERLAND 12 133 145

THE NETHERLANDS 42 419 461

WALES 42 122 164

Example : mdet Eurocare. Information on the differentiation, a major prognostic factor

Proposal Before the final analysis:

•To ensure that homogenous rules are used between registries

•To compare incidence and relative survival ratesby subsite, by morphology, by period…

in order to mark possible disparities in the registration between countries and between registries in the same registry

conclusion

There is a need to ask each registry their rules of codification before analysing rare cancers cases