CBS 2019
CBSMD教育中心
English

推荐文献

科研文章

荐读文献

The Future of Cardiovascular Computed Tomography Advanced Analytics and Clinical Insights Sudden Cardiac Arrest Survivorship: A Scientific Statement From the American Heart Association Syncope After Percutaneous Coronary Intervention Management of Percutaneous Coronary Intervention Complications: Algorithms From the 2018 and 2019 Seattle Percutaneous Coronary Intervention Complications Conference The year in cardiovascular medicine 2020: interventional cardiology 2-Year Outcomes After Stenting of Lipid-Rich and Nonrich Coronary Plaques The spectrum of chronic coronary syndromes: genetics, imaging, and management after PCI and CABG Management of Patients With NSTE-ACS: A Comparison of the Recent AHA/ACC and ESC Guidelines Qualitative Methodology in Cardiovascular Outcomes Research: A Contemporary Look Improving the Design of Future PCI Trials for Stable Coronary Artery Disease: JACC State-of-the-Art Review

Volume 74, Issue 16, October 2019

JOURNAL:J Am Coll Cardiol. Article Link

Nonproportional Hazards for Time-to-Event Outcomes in Clinical Trials: JACC Review Topic of the Week

J Gregson, L Sharples, GW Stone et al. Keywords: clinical trials; Cox proportional hazards; nonproportional hazards; statistics; time-to-event outcomes; trial design

ABSTRACT


Most major clinical trials in cardiology report time-to-event outcomes using the Cox proportional hazards model so that a treatment effect is estimated as the hazard ratio between groups, accompanied by its 95% confidence interval and a log-rank p value. But nonproportionality of hazards (non-PH) over time occurs quite often, making alternative analysis strategies appropriate. This review presents real examples of cardiology trials with different types of non-PH: an early treatment effect, a late treatment effect, and a diminishing treatment effect. In such scenarios, the relative merits of a Cox model, an accelerated failure time model, a milestone analysis, and restricted mean survival time are examined. Some post hoc analyses for exploring any specific pattern of non-PH are also presented. Recommendations are made, particularly regarding how to handle non-PH in pre-defined Statistical Analysis Plans, trial publications, and regulatory submissions.