Projecting cancer incidence rates and case numbers: a probabilistic approach using data from German cancer registries (1999 – 2013)

Projections of cancer incidence rates and case numbers, either stratified or standardized according to age and sex, are of great interest for healthcare planning and research. Historically, these projections have often been based on age-period-cohort and joinpoint regression models assuming Poisson distributed outcomes. A drawback in applications of these two approaches has been that the projections were usually deterministic, i. e. they did not allow statements of uncertainty, which would be desirable for communicating results to health policy decision makers. Although Bayesian age-period-cohort (APC) approache…