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September 2, 2026Medical Decision MakingOpen Access

A Framework for the Estimation of Quality-Adjusted Life-Years Using Joint Models of Longitudinal and Survival Data

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Authors

MCMichael J. CrowtherAGAlessandro GaspariniSESara Ekberg

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Overview

Simulation study reveals unbiased estimation of quality-adjusted life-years in patient-level cohorts, highlighting improved accuracy for health technology assessments.

Key Points

  • To develop and evaluate a unified continuous-time framework for estimating quality-adjusted life-years (QALYs) that jointly models longitudinal health utility and overall survival data.
  • Constructed a continuous-time framework using joint longitudinal-survival models fitted via maximum likelihood with individual patient-level longitudinal health utility and survival data.
  • Evaluated the performance of the joint modelling framework against standard methods using Monte Carlo simulations under realistic data-generating mechanisms.
  • Joint longitudinal-survival modelling accurately recovered true quality-adjusted life-years without statistical bias across simulation scenarios.
  • Calculating quality-adjusted life-years directly from longitudinal health utility trajectories while omitting survival processes resulted in biased estimates under most evaluated scenarios.

Cite This Study

Crowther et al. (2026) studied this question.

synapsesocial.com/papers/6a97e29ec562ede874ec6ccdhttps://doi.org/10.1177/0272989x261477224
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