Bayesian interpretation of immunotherapy trials with dynamic treatment effects

Dynamic nature of BRAF or KRAS p.G12C mutations in second-line therapy for advanced colorectal cancer patients: do early and late effects exist?

INTRODUCTION

The mitogen-activated protein kinase (MAPK) signalling network aberrations in metastatic colorectal cancer (mCRC) generate intrinsic dynamic effects and temporal variations that are crucial but often overlooked in clinical trial populations. Here, we investigate the time-varying impact of MAPK pathway mutation genotype on each treatment line's contribution to the overall clinical course.

METHODS

The PROMETEO study focused on mCRC patients undergoing second-line treatment at 20 hospitals. We evaluated genotypes and employed flexible models to analyse the dynamic effect of each mutation.

RESULTS

We examined data derived from 1160 patients. The effects of KRAS G12C or G12V, and BRAF V600E are clearly time-varying, with unexpected consequences such as the deleterious effect of BRAF V600E vs other genotypes dissipating over time when subjects receive antiangiogenics, or KRAS G12V and G12C showing increasing aggressiveness over time. Thus, contrary to expectations, the 12-month survival rate from the second line for those who survived >6 months was 49.9% (95% CI, 32.7-67.3) for KRAS G12C and 59% (95% CI, 38.5-80.6) for BRAF V600E.

CONCLUSIONS

The dynamic perspective is essential for understanding the behaviour of tumours with specific genotypes, especially from the second line onward. This may be relevant in patient monitoring and treatment decision-making, particularly in cases with distinct mutations.

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, execution, 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 illustrative examples of scenarios that may lead to informative censoring. We highlight the traditional 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 alternative survival estimands, such as restricted mean survival time or MaxCombo. We emphasize the distinctions between the design and interpretation of superiority and noninferiority trials, and compare Bayesian and frequentist statistical approaches. Finally, we discuss appropriate utilization of phase II and phase III trial results in shaping clinical management recommendations and evaluate the inherent risks and benefits associated with relying on phase II data for treatment decisions.

Medicine before and after David Cox

Herein we recount the legacy of Sir David Roxbee Cox (15 July 1924 - 18 January 2022) from the perspective of practicing clinicians. His-pioneering work in developing the logistic and Cox proportional hazard regression models revolutionized the analysis and interpretation of categorical and time-to-event survival outcomes in modern medicine. This legacy is an inspiration for all those who follow on Sir David Cox's path.