A comparison of methods for estimating survival probabilities in two stage phase III randomized clinical trials

As two stage randomized study designs gain increased recognition and popularity for oncology studies it remains a challenge to analyze and interpret clinical outcomes due to lack of sufficient research. In this study we investigated existing methodologies and explored novel means to estimate survival probabilities using this study design. First a Naive Approach was formulated and studied under the extended notion of Intent-to-Treat (ITT) analysis pertinent to two stage design. Secondly a bootstrap variance estimate was proposed for Inverse Probability Weighted (IPW) Estimator to simplify and improve the variance estimate. Thirdly we developed a Bootstrap Approach by creatively using a "hybrid" bootstrap process to handle artificial "dropouts" due to late stage randomization. Finally we conducted power analysis for a global test statistic based on log transformation.;Simulation results reveal that the Naive Estimator is prone to bias for ITT analysis. The IPW variance estimate underestimates the true variance of the estimator by 20-50% where a bootstrap variance provides a nearly unbiased estimate. Both the survival probability estimate and variance estimates using the Bootstrap Approach are nearly unbiased with comparable Mean Square Error (MSE) to IPW Estimator.;The application to two previously published Children's Oncology Group (COG) studies demonstrates that analytical results using proposed method are consistent with clinical findings. Finally the proposed global test has sufficient power for detecting heterogeneity due to late treatment or qualitative interaction.;KEYWORDS: Two stage design; Bootstrap process; Survival analysis; Randomized clinical trial; Induction therapy; Maintenance therapy; Oncology; Phase III; COG; IPW; Missing data...