Development of a microsimulation of melanoma mortality for evaluating the effectiveness of population-based skin cancer screening

Abstract

Background: A nationwide skin cancer screening (SCS) was implemented in Germany in 2008. It aims at improving early detection of melanoma in order to reduce melanoma mortality. While the idea of early detection is compelling, demonstrating the effectiveness of melanoma screening is crucial. Since it is not feasible to conduct epidemiological studies to investigate the impact of factors such as screening interval or targeted age groups, we developed a microsimulation model that is able to predict melanoma mortality in Germany under several SCS conditions.

Methods: Using German cancer registry data, population data, and other published data on melanoma progression and screening participation, we developed a stochastic microsimulation model. With this model, 10,000 populations of 100,000 persons and their melanoma-related life histories were simulated separately for women and for men and calibrated to observed melanoma incidence. In a second step, life histories of melanoma were changed by an SCS.

Results: Compared with a nonscreening scenario (age-standardized mortality rate: 1.6 and 2.9 per 100,000 for women and men), a biennial SCS of the 35- to 85-year-old population with a participation probability of 20% for each screening-eligible individual and a test sensitivity of 80% reduced mortality by up to 0.7 and 1.4 deaths per 100,000 person-years for women and men, respectively, corresponding to a relative reduction of melanoma mortality by 45% in women and men.

Conclusions: We developed a microsimulation model of melanoma mortality that can be used to evaluate the effectiveness of population-based skin cancer screening. The simulation provided plausible melanoma mortality predictions and is a tool for comparing different SCS scenarios. However, it does not provide estimates on total costs of SCS.

Keywords: Germany; melanoma; microsimulation; mortality; skin cancer screening.