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Keywords: Oncology, Treatment Switch, Overall Survival, Subsequent Therapies
Subsequent therapies especially crossover from the control group to receive experimental treatments in randomized clinical studies may confound the study results and potentially lead to underestimating treatment effect. Analyses to adjust the confounding impact of crossover on overall survival have been reported in many published oncology studies. Main statistical adjustment approaches include inverse probability of censoring weighting (IPCW), rank preserving structural failure time (RPSFT), and two-stage models. To better understand the application of these methods especially in immuno-oncology (IO) studies, we conduct a systematic review on the publications which report the crossover adjusted results for IO therapies in various cancers. Pro and cons of the three adjustment approaches are discussed, and suggestions to improve the quality of data reporting and interpretation are provided.