A new method of estimating prevalence of childhood cancer survivors (POCCS): example of the 20-year prevalence in The Netherlands
International journal of epidemiology(2023)
摘要
Background Estimating the number of childhood cancer survivors is crucial for cancer control, including clinical guidelines. To compare estimates across countries despite data sharing restrictions, we propose a new method of computing limited-duration prevalence of childhood cancer survivors (POCCS) using aggregated data.Methods We developed a Markov model that simulates, for each calendar year and birth cohort in a population, the proportion of individuals in the following health states: healthy, newly diagnosed with cancer, surviving with cancer, and deceased. Transitions between health states were informed using annual sex- and age-specific incidence rates, conditional 1-year net survival probabilities from the Netherlands Cancer Registry (1989-2011), and annual mortality probability by sex and age group for The Netherlands from the Human Mortality Database. Applying a Markov model, we computed 20-year prevalence of childhood cancer survivors. The resulting POCCS estimates, stratified by sex, were compared with SEER*Stat estimates derived from individual cancer records from the same registry.Results In 2011, POCCS predicted 654 males [95% confidence interval (95% CI): 637-672] and 539 females (95% CI: 523-555) per million persons living in The Netherlands after childhood cancer diagnosed within the previous 20 years. Using SEER*Stat, the 20-year prevalence was 665 males (95% CI: 647-683) and 544 females (95% CI: 529-560) per million persons on 1 July 2011.Conclusions Using the POCCS model and aggregated cancer data, our estimates of childhood cancer survivors limited-duration prevalence were consistent with those computed by a standard method requiring individual cancer records. The POCCS method provides relevant information for planning follow-up and care for childhood cancer survivors.
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关键词
Childhood cancer survivors,prevalence,Markov models
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