CBS 2019
CBSMD教育中心
中 文

Other Relevant Articles

Abstract

Recommended Article

Utilization and programming of an automatic MRI recognition feature for cardiac rhythm management devices Development and validation of a simple risk score to predict 30-day readmission after percutaneous coronary intervention in a cohort of medicare patients Randomized Trial Evaluating Percutaneous Coronary Intervention for the Treatment of Chronic Total Occlusion: The DECISION-CTO Trial The HACD4 haplotype as a risk factor for atherosclerosis in males Cholesterol-Lowering Agents From Nonclinical Research to Clinical Trials and Patient-registries: Challenges and Opportunities in Biomedical Research Percutaneous Recanalization of Chronic Total Occlusions: 2019 Consensus Document from the EuroCTO Club Outcomes in Women and Minorities Compared With White Men 1 Year After Everolimus-Eluting Stent Implantation: Insights and Results From the PLATINUM Diversity and PROMUS Element Plus Post-Approval Study Pooled Analysis

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.