International Journal of Epidemiology 2000;29:197-207
© International Epidemiological Association 2000
Cancer prevalence estimates based on tumour registry data in the Surveillance, Epidemiology, and End Results (SEER) Program
a Department of Health Science, College of Health and Human Performance, Brigham Young University, 213 Richards Building, Provo, UT 84602; Division of Epidemiology, Department of Family and Preventive Medicine, University of Utah College of Medicine, UT 84132, USA.
b Laboratory of Epidemiology and Biostatistic, Istituto Superiore di Sanita, Viale Regina Elena, 299, 00161, Roma, Italy.
c Applied Research Branch, Cancer Control Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, EPN 313, 9000 Rockville Pike, Bethesda, MD 20892, USA.
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 data generally provided reasonable estimates of cancer prevalence. These estimates are useful because they are more representative of cancer prevalence than previously obtained and reported in the US.
Keywords Cancer, prevalence, burden, cohort, cross-sectional, life table
Accepted 8 September 1999
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