RMST for Interval-Censored Data in Oncology Clinical Trials

In oncology studies, the assumption of proportional hazards is often questionable due to factors such as the presence of cured patients, a delayed treatment benefit, and possible treatment switching. The restricted mean survival time (RMST) has emerged as a valuable alternative summary measure to the hazard ratio (HR) in this scenario as it provides a clinically meaningful interpretation of treatment benefit without additional assumptions. As a commonly used primary endpoint, progression-free survival (PFS) is defined as the time from randomization to the first occurrence of death or progression of disease (PD). However, PFS involves dual observation processes where, in practice, the exact death time is typically recorded, but PD is interval-censored. This feature is also present in other commonly used primary endpoints, including event-free survival, disease-free survival, and relapse-free survival. The conventional approach imputes the PD time with the right boundary of the time interval during which the PD occurs. This paper presents alternative estimation and inference approaches to estimate RMST with a mixture of right-censored and interval-censored data. Different approaches are explored by simulation under various plausible scenarios for oncology clinical trials with regard to the assessment frequency, randomness in the actual assessment times, and size of treatment effect. The choice of the restricted time point in RMST is also explored. The simulation results indicate that the RMST estimators that take account of the interval censoring inherent in the data are unbiased and more accurate than the conventional estimators, while the performance for two-group comparisons is comparable. Furthermore, the performance of the proposed estimators is contingent on the scheduled assessment plan and patients' visit window.