Keywords: Simulation modeling, prostate cancer screening, model calibration, racial disparities, personalized medicine, randomized trials, cancer surveillance
PSA screening for prostate cancer has been a part of clinical practice for 30 years, yet many critical questions remain. Many questions cannot be addressed by randomized studies and evidence gaps persist. I will present some recent applications of a simulation model of prostate cancer screening that we have developed with the support of NCI’s Cancer Intervention and Surveillance Modeling Network. After reviewing the statistical basis for the model, I will show how we have used it to (a) reconcile apparently conflicting results of the two largest prostate cancer screening trials; (b) develop recommendations for how screening should be different in high-risk populations like black men and (c) project risks of overdiagnosis that are personalized according to age, grade, PSA, and comorbidity at diagnosis. I will show that the screening trials are not as different as they seem and combine to indicate a strongly beneficial screening test. Further, it makes sense to begin screening African-American men up to ten years earlier than the general population. Finally, the chance of being overdiagnosed can range from 3 to 80 percent depending on a patient’s characteristics at diagnosis.