26: Assessing Bias in Kaplan-Meier Estimates Under Informative Censoring in Phase II Cancer Trials

Music City Center 

Objective: Informative censoring challenges survival analysis, particularly in estimating Progression-Free Survival at six months (PFS6). This study evaluates the impact of informative censoring and the effectiveness of Inverse Probability of Censoring Weighting (IPCW)-adjusted Kaplan-Meier (KM) estimates in reducing bias.

Methods: We conducted simulations using Piecewise Exponential Models to generate survival times under different censoring mechanisms. Simulation 1 examines two informative censoring scenarios: one where censored patients have a higher progression risk and another where they have a lower risk, assessing their respective biases and implications. Simulation 2 compares traditional KM estimates, IPCW-adjusted KM estimates, and true PFS6 across varying censoring rates and sample sizes.

Results: KM estimates overestimated survival when high-risk patients were censored, introducing bias. IPCW adjustment reduced bias but did not fully eliminate it, particularly at later time points. IPCW improves PFS estimation under informative censoring but may leave residual bias. Appropriate censoring adjustments are essential for robust survival analysis in clinical trials.

Kaplan-Meier Estimation

Informative Censoring

Progression-Free Survival (PFS6)

Inverse Probability of Censoring Weighting (IPCW)

Survival Analysis

Phase II Clinical Trials 

Biopharmaceutical Section