Comparisons of Propensity Score Methods for Time to Event Outcomes: Evaluation through Simulations and Oral Squamous Cell Carcinoma Case Study

Abstract

Introduction & Objective: In observational studies, it is recommended to use propensity score (PS) methods or covariate adjustment for confounding effect adjustment. However, few guidelines are available regarding the choice of PS approaches or covariate adjustment for the best performance in a particular data. In this study, we compared different PS methods and conventional covariate adjustment to investigate the treatment effect for the overall population on time-to-event outcomes. Methods: In the Monte Carlo simulations, we compared the hazard ratio (HR) and precision estimated using covariate adjustment and eight different PS approaches, including matching, stratification, and inverse probability of treatment weighting (IPTW). In the Oral Squamous-Cell Carcinoma Cancer case study, we applied the aforementioned PS approaches to compare the effect of receiving post-operative radiation therapy (PORT) and having engraftable tumors on different time-to-event clinical outcomes. Results: In the simulations, both IPTW and covariate adjustment produced unbiased HR estimates with small uncertainty. In the case study, covariate adjustment showed that patients with engraftable tumors were twice as likely to have local/regional recurrence (HR 1.98 [1.23, 3.18], p-value<0.005) and any recurrence or death (HR 2.02 [1.38, 2.96], p-value<0.001); patients received PORT were twice as likely to develop either local, regional, or distance recurrence (HR 2.12 [1.32, 3.41], p-value<0.005). Results produced by IPTW were consistent with covariate adjustment method (within ± 0.1 differences). Conclusion: Covariate adjustment and the IPTW method performed well across simulations and the case study. In practice, care should be taken to select the most suitable method when estimating the treatment, exposure or intervention effect on time-to-event outcomes.