CBS 2019
CBSMD教育中心
中 文

Other Relevant Articles

Abstract

Recommended Article

Percutaneous coronary intervention in stable angina (ORBITA): a double-blind, randomised controlled trial LOX-1 in Atherosclerosis and Myocardial Ischemia: Biology, Genetics, and Modulation Defining High Bleeding Risk in Patients Undergoing Percutaneous Coronary Intervention: A Consensus Document From the Academic Research Consortium for High Bleeding Risk Impact of Artificial Intelligence on Interventional Cardiology: From Decision-Making Aid to Advanced Interventional Procedure Assistance The Year in Cardiovascular Medicine 2020: Coronary Intervention Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices Overall and Cause-Specific Mortality in Randomized Clinical Trials Comparing Percutaneous Interventions With Coronary Bypass Surgery: A Meta-analysis Timing and Causes of Unplanned Readmissions After Percutaneous Coronary Intervention: Insights From the Nationwide Readmission Database

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.