Background: There is a need for automated approaches to incorporate information on cancer recurrence events into population-based cancer registries.
Objective: The aim of this study is to determine the accuracy of a novel data mining algorithm to extract information from linked registry and medical claims data on the occurrence and timing of second breast cancer events (SBCE).
Methods: We used supervised data from 3092 stage I and II breast cancer cases (with 394 recurrences), diagnosed between 1993 and 2006 inclusive, of patients at Kaiser Permanente Washington and cases in the Puget Sound Cancer Surveillance System.
Background: Several prostate cancer (PCa) early-detection biomarkers are available for reflex testing in men with intermediate prostate-specific antigen (PSA) levels. Studies of these biomarkers typically provide information about diagnostic performance but not about overdiagnosis and lives saved, the primary drivers of associated harm and benefit.
Methods: We projected overdiagnoses and lives saved using an established microsimulation model of PCa incidence and mortality with screening and treatment efficacy based on randomized trials.