Author + information
- Received June 13, 2019
- Revision received August 20, 2019
- Accepted August 26, 2019
- Published online October 14, 2019.
- John Gregson, PhDa,∗ (, )@GreggWStone,
- Linda Sharples, PhDa,
- Gregg W. Stone, MD, PhDb,c,
- Carl-Fredrik Burman, PhDd,
- Fredrik Öhrn, PhDd and
- Stuart Pocock, PhDa
- aDepartment of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom
- bPopulation Health Sciences and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- cThe Cardiovascular Research Foundation, New York, New York
- dStatistical Innovation, Data Science and Artificial Intelligence, Research and Development, AstraZeneca, Gothenburg, Sweden
- ↵∗Address for correspondence:
Dr. John Gregson, Department of Medical Statistics, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT, London, United Kingdom.
• Trials with time-to-event outcomes are usually analyzed using PH models, but with non-PH this may not be the best choice.
• Restricted mean survival time can be a useful alternative with an early treatment effect.
• Milestone analysis and RMST may be useful with an early effect that attenuates later. Accelerated failure time models are a further alternative.
• The design and analysis of trials should consider how to handle non-PH.
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.
- clinical trials
- Cox proportional hazards
- nonproportional hazards
- time-to-event outcomes
- trial design
Drs. Burman and Öhrn are employees of and hold stock in AstraZeneca. Dr. Pocock has served on the Data and Safety Monitoring Boards of the ASCOT and CHARM trials. Drs. Gregson, Stone, and Pocock are authors of the EXCEL trial. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Received June 13, 2019.
- Revision received August 20, 2019.
- Accepted August 26, 2019.
- 2019 American College of Cardiology Foundation
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