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Pitfall in the Design and Analysis of Comparative Oncology Trials With a Time-to-Event Endpoint and Recommendations

Zachary R. McCaw, Dae Hyun Kim, L. J. Wei

2022JNCI Cancer Spectrum12 citationsDOIOpen Access PDF

Abstract

When designing a comparative oncology trial for an overall or progression-free survival endpoint, investigators often quantify the treatment effect using a difference in median survival times. However, rather than directly designing the study to estimate this difference, it is almost always converted to a hazard ratio (HR) to determine the study size. At the analysis stage, the hazard ratio is utilized for formal analysis, yet because it may be difficult to interpret clinically, especially when the proportional hazards assumption is not met, the observed medians are also reported descriptively. The hazard ratio and median difference contrast different aspects of the survival curves. Whereas the hazard ratio places greater emphasis on late-occurring separation, the median difference focuses locally on the centers of the distributions and cannot capture either short- or long-term differences. Having 2 sets of summaries (a hazard ratio and the medians) may lead to incoherent conclusions regarding the treatment effect. For instance, the hazard ratio may suggest a treatment difference whereas the medians do not, or vice versa. In this commentary, we illustrate these commonly encountered issues using examples from recent oncology trials. We present a coherent alternative strategy that, unlike relying on the hazard ratio, does not require modeling assumptions and always results in clinically interpretable summaries of the treatment effect.

Topics & Concepts

MedicineEvent (particle physics)Endpoint DeterminationOncologyClinical endpointInternal medicineClinical trialMedical physicsIntensive care medicinePhysicsQuantum mechanicsStatistical Methods in Clinical TrialsAdvanced Causal Inference TechniquesHealth Systems, Economic Evaluations, Quality of Life
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