Challenges, Complexities, and Considerations in the Design and Interpretation of Late-Phase Oncology Trials

Optimal management of cancer patients relies heavily on late-phase oncology randomized controlled trials. A comprehensive understanding of the key considerations in designing and interpreting late-phase trials is crucial for improving subsequent trial design, execu-tion, and clinical decision-making. In this review, we explore important aspects of late-phase oncology trial design. We begin by examining the selection of primary endpoints, including the advantages and disadvantages of using surrogate endpoints. We address the challenges involved in assessing tumor progression and discuss strategies to mitigate bias. We define informative censoring bias and its impact on trial results, including illustra-tive examples of scenarios that may lead to informative censoring. We highlight the tradi-tional roles of the log-rank test and hazard ratio in survival analyses, along with their limitations in the presence of nonproportional hazards as well as an introduction to alter-native survival estimands, such as restricted mean survival time or MaxCombo. We emphasize the distinctions between the design and interpretation of superiority and non-inferiority trials, and compare Bayesian and frequentist statistical approaches. Finally, we discuss appropriate utilization of phase II and phase III trial results in shaping clinical man-agement recommendations and evaluate the inherent risks and benefits associated with relying on phase II data for treatment decisions. Semin Radiat Oncol 33:429-437 (c) 2023 Elsevier Inc. All rights reserved.

Automated summary

Optimal management of cancer patients relies on late-phase oncology randomized controlled trials, and understanding key considerations in trial design and interpretation is crucial. This review explores important aspects of late-phase oncology trial design, including selection of primary endpoints, challenges in tumor progression assessment, informative censoring bias, survival analysis methods, design and interpretation differences in superiority and non-inferiority trials, statistical approaches, and utilization of trial results in clinical management recommendations.