Estimating the world cancer burden: GLOBOCAN 2000

Describing the distribution of disease between different populations and ov er time has been a highly successful way of devising hypotheses about causa tion and for quantifying the potential for preventive activities.' Statisti cal data are also essential components of disease surveillance programs. Th ese play a critical role in the development and implementation of health po licy, through identification of health problems, decisions on priorities fo r preventive and curative programs and evaluation of outcomes of programs o f prevention, early detection/screening and treatment in relation to resour ce inputs. Over the last 12 years, a series of estimates of the global burden of cance r have been published in the International Journal of Cancer.(2-6) The meth ods have evolved and been refined, but basically they rely upon the best av ailable data on cancer incidence and/or mortality at country level to build up the global picture. The results are more or less accurate for different countries, depending on the extent and accuracy of locally available data. This "databased" approach is rather different from the modeling method use d in other estimates.(7-10) Essentially, these use sets of regression model s, which predict cause-specific mortality rates of different populations fr om the corresponding all-cause mortality." The constants of the regression equations derive from datasets with different overall mortality rates (ofte n including historic data from western countries). Cancer deaths are then s ubdivided into the different cancer types, according to the best available information on relative frequencies. GLOBOCAN 2000 updates the previously published data-based global estimates of incidence, mortality and prevalence to the year 2000.(12)