Lifetime prevalence of cancer in Germany between 2010 and 2019: An analysis based on aggregated data - Kira Baginski; Dina Voeltz; Claudia Hornberg; Claudia Kohring; Annika Hoyer (PLoS ONE, 2025)
Background Many cancer survivors (i.e., individuals alive who have been diagnosed with cancer at some point in their lives) remain under surveillance by doctors and medical professionals regardless of the outcome of their treatment as they face the risk of recurrence and/or encounter symptoms and other health-related issues. With advancements in cancer early detection, diagnostics, and treatment strategies, along with an increasingly older population, the number of cancer survivors is steadily increasing. Since information on epidemiological indicators of cancer survivors is limited in Germany, the present study aims to estimate its prevalence between 2010 and 2019. Methods The annual age- and sex-specific lifetime prevalence of cancer was estimated using a partial differential equation. The calculation was based on comprehensive data obtained from the Centre for Cancer Registry Data (Zentrum für Krebsregisterdaten, ZfKD), the Central Research Institute of Ambulatory Health Care in Germany (Zentralinstitut für die kassenärztliche Versorgung, Zi), and the German Federal Statistical Office. Results Our estimates indicate a rise in lifetime prevalence of cancer between 2010 and 2019 across all ages up to 85, particularly pronounced among older individuals. By 2019, the highest prevalence was estimated to be 49% of males and 28% of females at age 85. In contrast, childhood cancer was relatively rare, affecting less than 0.3% of girls and boys until the age of 18. Generally, the prevalence of cancer was higher among males than females. Overall, the number of cancer survivors aged up to 85 was estimated to increase from 2.51 million in 2010 to over 5.07 million in 2019. Conclusions The findings indicate a substantial rise in the lifetime prevalence of cancer in 2019 compared to 2010. Considering a cancer patient as cured based on a specific timeframe may lead to an underestimation of the future demand for healthcare resources.