The Influence of handling censored data on estimating progression-free survival in cancer clinical trials (JCOG9913-A).

Abstract

Progression-free survival (PFS) is a common endpoint in cancer clinical trials. This study was undertaken to assess the impact of data errors and data handling on the statistical estimation of PFS. Data from four trials conducted by the Japan Clinical Oncology Group were examined. Three types of data handling methods were defined: (1) data handling method A (METHOD-A), the collected event data are used as much as possible, (2) METHOD-C, only reliable data with firm evidence are used, and (3) METHOD-B is intermediate between METHOD-A and METHOD-C. To assess the impact of each of the three methods, Kaplan-Meier survival curves, median PFS, proportion of PFS, log-rank p values and hazard ratios were estimated. In three trials that collected PFS data periodically, no remarkable differences in median PFS and the proportion of PFS were observed. In one trial with non-periodic data cleaning, however, the ratio of median PFS by METHOD-C to that by METHOD-B was 0.85, the maximum difference of proportion of PFS between METHOD-C and METHOD-B was 12.0% and the largest spread in PFS curves amongst the three methods was observed in this trial. In all trials, log-rank p values and hazard ratios for between arm comparisons did not differ between the three methods. Periodic data management can reduce errors in comparisons of PFS and is a critical requirement when using PFS as a major endpoint. Furthermore, proper data handling is essential in the estimation of patient benefit and caution is needed when making clinical decisions based on PFS.