Estimating the world cancer burden: Globocan 2000

Describing the distribution of disease between different populations and over time has been ahighly successfu l way of devising hypothese s about causation and for quantifying the potential for preventive activities.1 Statistical data are also essentia l componentsof diseasesurveillanceprograms. Theseplay acritical role in the developmen t and implementation of health policy, through identification of health problems, decisions on priorities for preventive and curative programs and evaluation of outcomes of programs of prevention, early detection/screenin g and treatment in relation to resource inputs. Over the last 12 years, aseries of estimates of the global burden of cancer have been published in the International Journal of Cancer. 2–6 The methods have evolved and been refined, but basically they rely upon the best availabl e data on cancer incidence and/or mortality at country level to build up theglobal picture. The results are more or less accurat e for different countries, depending on the extent and accuracy of locally availabl e data. This “databased” approach is rather different from themodeling method used in other estimates. 7–10 Essentially, these use sets of regression models, which predict cause-specifi c mortality rates of different populations from the correspondin g all-cause mortality.11 The constant s of the regression equations derive from dataset s with different overal mortality rates (often including historic data from wester n countries) . Cancer deaths are then subdivided into the different cancer types, according to the best availabl e information on relative frequencies. GLOBOCAN 2000 updates thepreviousl y published data-based global estimates of incidence, mortality and prevalence to the year 2000.12