Global and regional estimates of cancer mortality and incidence by site: I. Application of regional cancer survival model to estimate cancer mortality distribution by site

Colin D Mathers¹ , Kenji Shibuya¹ , Cynthia Boschi-Pinto² , Alan D Lopez¹ and Christopher JL Murray³

¹Global Programme on Evidence for Health Policy, World Health Organization, Geneva, Switzerland

²Family and Community Health/Child and Adolescent Health and Development, World Health Organization, Geneva, Switzerland

³Executive Director, Evidence and Information for Policy, World Health Organization, Geneva, Switzerland

author email corresponding author email

BMC Cancer 2002, 2:36doi:10.1186/1471-2407-2-36


Published:	26 December 2002

Abstract

Background

The Global Burden of Disease 2000 (GBD 2000) study starts from an analysis of the overall mortality envelope in order to ensure that the cause-specific estimates add to the total all cause mortality by age and sex. For regions where information on the distribution of cancer deaths is not available, a site-specific survival model was developed to estimate the distribution of cancer deaths by site.

Methods

An age-period-cohort model of cancer survival was developed based on data from the Surveillance, Epidemiology, and End Results (SEER). The model was further adjusted for the level of economic development in each region. Combined with the available incidence data, cancer death distributions were estimated and the model estimates were validated against vital registration data from regions other than the United States.

Results

Comparison with cancer mortality distribution from vital registration confirmed the validity of this approach. The model also yielded the cancer mortality distribution which is consistent with the estimates based on regional cancer registries. There was a significant variation in relative interval survival across regions, in particular for cancers of bladder, breast, melanoma of the skin, prostate and haematological malignancies. Moderate variations were observed among cancers of colon, rectum, and uterus. Cancers with very poor prognosis such as liver, lung, and pancreas cancers showed very small variations across the regions.

Conclusions

The survival model presented here offers a new approach to the calculation of the distribution of deaths for areas where mortality data are either scarce or unavailable.