Newly developed prostate cancer biomarker tests have the potential for early detection; however, optimal use of these biomarkers and their impact on long-term health outcomes is unclear. A partially observable Markov chain was validated and used to simulate patients progression through prostate cancer states to all-cause mortality. Patients periodically received one or more biomarker tests according to predefined screening strategies that use combinations of prostate specific antigen (PSA), prostate cancer antigen 3 (PCA3), TMPRSS2:ERG (T2:ERG), and the Mi-Prostate Score (MiPS) models for all cancer and high grade cancer. Monte Carlo simulation was used to estimate quality-adjusted survival and the number of screening biopsies and metastatic cases per 1,000 men. We analyzed how best to use new biomarker tests during screening to tradeoff the benefits of additional life years gained with the harms of new biomarkers.
