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Projecting effectiveness after ending a randomized controlled trial: a two-state Markov microsimulation model.

Fei Yuan1, Shrikant I Bangdiwala1,2, Wesley Tong1

  • 1Population Health Research Institute, DBCVSRI, 20 Copeland Avenue, Hamilton, ONL8L 2X2, Canada.

International Journal of Technology Assessment in Health Care
|August 4, 2020
PubMed
Summary
This summary is machine-generated.

This study found that annual projections, life table probabilities, in-trial events, and post-trial medication use are optimal for projecting life-year-gained in large trials. These factors significantly impact restricted mean survival time (RMST) estimations.

Keywords:
Clinical epidemiologyEpidemiologyHealth economics/economic evaluationModelingStatistics

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Area of Science:

  • Health Economics
  • Biostatistics
  • Clinical Trial Design

Background:

  • Estimating life-year-gained is crucial for assessing intervention effectiveness in clinical trials.
  • Microsimulation models are widely used, but their design parameters can influence outcomes.
  • Restricted mean survival time (RMST) is a key metric for comparing survival between groups.

Purpose of the Study:

  • To investigate the behavior of restricted mean survival time (RMST).
  • To evaluate different design choices for a two-state Markov microsimulation model.
  • To determine optimal parameters for projecting life-year-gained in large trials.

Main Methods:

  • A 2 × 4 × 2 full factorial experiment was conducted.
  • Patient-wise 15-year post-trial survival was projected using Cardiovascular Outcomes for People Using Anticoagulation Strategies Study (COMPASS) data.
  • Life-year-gained was compared based on probability of death, cycle length, and age correction, analyzed using ANOVA and Tukey's HSD test.

Main Results:

  • When considering both in-trial events and post-trial medications, annual projections yielded different life-year-gained compared to monthly, quarterly, or semiannual projections.
  • The choice of probability of death (REACH-based vs. USA life table) significantly impacted life-year-gained.
  • Half-a-cycle age correction had a smaller impact on life-year-gained.
  • When post-trial medications were excluded, only the probability of death choice affected life-year-gained.

Conclusions:

  • Annual projections are recommended for optimal life-year-gained estimation in large trials or cohorts.
  • Utilizing life table probabilities and considering both in-trial events and post-trial medication use are essential.
  • These findings inform the design of microsimulation models for more accurate health economic evaluations.