摘要
To compare the performance of four common methods of applying propensity scores： covariate adjustment, stratification, matching, and inverse probability of treatment weighting, in addressing issues of selection bias. The linked Surveillance, Epidemiology, and End Results Medicare database was used in this study. We compared mortality of patients with localized prostate cancer, in two different scenarios. In Scenario 1, treatment effect on non-prostate cancer mortality were compared between patients with localized prostate cancer receiving active treatment （radical prostatectomy or radiation） and those only being observed. In Scenario 2, prostate cancer specific mortality was compared between localized prostate cancer patients with and without primary androgen deprivation therapy （ADT）. The known confounding factors of comorbidity （Scenario 1） or tumor grade （Scenario 2） were removed to evaluate the ability of each propensity score method to control for the selection bias caused by the presence of the factors. Matching yields slightly better control than the three other methods. None of the propensity score methods can eliminate bias caused by removing a known confounder.
