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In Silico Clinical Trials for Cardiovascular Disease
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Recurrent Events in Cardiovascular Trials: JACC State-of-the-Art Review.

John Gregson1, Gregg W Stone2, Deepak L Bhatt2

  • 1Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Journal of the American College of Cardiology
|September 27, 2023
PubMed
Summary
This summary is machine-generated.

Analyzing repeat cardiovascular events, not just the first, offers greater insight into treatment effects and disease burden. This approach can enhance statistical power and should be considered for primary trial analysis.

Keywords:
heart failurerecurrent eventsstatisticstrial design

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Area of Science:

  • Cardiovascular Medicine
  • Clinical Trials Methodology
  • Biostatistics

Background:

  • Randomized cardiovascular trials frequently observe recurrent nonfatal events during patient follow-up.
  • Current standard practice often focuses on the time to the first event as the primary outcome, potentially overlooking valuable information.

Purpose of the Study:

  • To evaluate the utility of analyses incorporating repeat events in cardiovascular trials.
  • To determine if repeat event analyses improve understanding of treatment effects and total disease burden.
  • To assess the impact of repeat event analyses on statistical power and their suitability as primary trial outcomes.

Main Methods:

  • Comparison of statistical methods for analyzing repeat events, including Lin Wei Yang Ying, negative binomial, joint frailty, win ratio, and area under the curve.
  • Illustration of method performance using data from five large cardiovascular trials.
  • Benchmarking against traditional time-to-first-event analyses.

Main Results:

  • Analyses including repeat events provide a more comprehensive understanding of treatment efficacy and disease progression.
  • These methods can offer increased statistical power compared to time-to-first-event analyses.
  • The study offers a guide to understanding and selecting appropriate statistical methods for repeat event data.

Conclusions:

  • Incorporating repeat events into the analysis of cardiovascular trials enhances the evaluation of treatment effects and disease burden.
  • The adoption of repeat event analyses as a primary outcome measure is recommended for future cardiovascular trials.
  • Guidance is provided to facilitate the selection and application of appropriate statistical methodologies for repeat event data.