Cancer prevalence estimates based on tumour registry data in the Surveillance, Epidemiology, and End Results (SEER) Program

Background The Connecticut Tumor Registry (CTR) has collected cancer data for a sufficiently long period of time to capture essentially all prevalent cases of cancer, and to provide unbiased estimates of cancer prevalence. However, prevalence proportions estimated from Connecticut data may not be re...

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Bibliographic Details
Published in:International journal of epidemiology 2000-04, Vol.29 (2), p.197-207
Main Authors: Merrill, Ray M, Capocaccia, Riccardo, Feuer, Eric J, Mariotto, Angela
Format: Article
Language:English
Subjects:
Adult
Age Distribution
Aged
Aged, 80 and over
Biological and medical sciences
burden
Cancer
cohort
Connecticut - epidemiology
cross-sectional
Epidemiology
Female
Humans
Incidence
life table
Male
Medical sciences
Middle Aged
Neoplasms - epidemiology
Prevalence
Registries
Retrospective Studies
SEER Program - statistics & numerical data
Sex Distribution
Survival Rate
Tumors
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Summary:Background The Connecticut Tumor Registry (CTR) has collected cancer data for a sufficiently long period of time to capture essentially all prevalent cases of cancer, and to provide unbiased estimates of cancer prevalence. However, prevalence proportions estimated from Connecticut data may not be representative of the total US, particularly for racial/ethnic subgroups. The purpose of this study is to apply the modelling approach developed by Capocaccia and De Angelis to cancer data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute to obtain more representative US site-specific cancer prevalence proportion estimates for white and black patients. Methods Incidence and relative survival were modelled and used to obtain estimated completeness indices of SEER prevalence proportions for all cancer sites combined, stomach, cervix uteri, skin melanomas, non-Hodgkin's lymphomas, lung and bronchus, colon/rectum, female breast, and prostate. For validation purposes, modelled completeness indices were computed for Connecticut and compared with empirical completeness indices (the ratio of Connecticut based prevalence proportion estimates using 1973–1993 data to 1940–1993 data). The SEER-based modelled completeness indices were used to adjust SEER prevalence proportion estimates for white and black patients. Results Model validation showed that the adjusted SEER cancer prevalence proportions provided reasonably unbiased prevalence proportion estimates in general, although more complex modelling of the completeness indices is necessary for female cancers of the colon, melanoma, breast, cervix, and all cancers combined. The SEER-based cancer prevalence proportions are incomplete for most cancer sites, more so for women, whites, and at older ages. For all cancers combined, prevalence proportions tended to be higher for whites than blacks. For the site-specific cancers this was true for stomach, prostate, cervix uteri, and lung and bronchus (men only). For colon/rectal cancers the prevalence proportions were higher for blacks through ages 59 (men) and 64 (women), and then for the remaining ages they were higher for whites. Prevalence proportions were lowest for stomach cancer and highest for prostate and female breast cancers. Men experienced higher prevalence proportions than women for skin melanomas, non-Hodgkin's lymphomas, lung and bronchus, and colon/rectal cancers. Conclusion The modelling approach applied to SEER dat
ISSN:0300-5771
1464-3685
DOI:10.1093/ije/29.2.197