Optimization of PSA Screening Policies: A Comparison of the Patient and Societal Perspectives

Objective. To estimate the benefit of PSA-based screening for prostate cancer from the patient and societal perspec-tives. Method. A partially observable Markov decision pro-cess model was used to optimize PSA screening decisions. Age-specific prostate cancer incidence rates and the mortal-ity rates from prostate cancer and competing causes were considered. The model trades off the potential benefit of early detection with the cost of screening and loss of patient quality of life due to screening and treatment. PSA testing and biopsy decisions are made based on the patient’s proba-bility of having prostate cancer. Probabilities are inferred based on the patient’s complete PSA history using Bayesian updating. Data Sources. The results of all PSA tests and biopsies done in Olmsted County, Minnesota, from 1993 to 2005 (11,872 men and 50,589 PSA test results). Outcom