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Mapping EQ-5D-3L to EQ-5D-5L.

Ben A van Hout1, James W Shaw2

  • 1University of Sheffield.

Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research
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Summary
This summary is machine-generated.

This study developed new algorithms to map the EQ-5D-3L to EQ-5D-5L value sets. The recommended method uses ordinal logistic regression with a latent factor for improved prediction accuracy.

Keywords:
EQ-5D-3LEQ-5D-5Lalgorithmsmapping

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Area of Science:

  • Health Economics
  • Psychometrics
  • Health Outcomes Research

Background:

  • The EQ-5D-3L and EQ-5D-5L are widely used health status questionnaires.
  • Population value sets exist for both EQ-5D-3L and EQ-5D-5L.
  • A method to link responses between the two versions is needed.

Purpose of the Study:

  • To develop and validate algorithms for mapping EQ-5D-3L responses to EQ-5D-5L value sets.
  • To improve the accuracy of health state valuations when using different EQ-5D versions.

Main Methods:

  • Utilized data from 3580 participants who completed both EQ-5D-3L and EQ-5D-5L.
  • Developed and compared various algorithms, including nonparametric and ordinal logistic regression.
  • Evaluated models using Akaike's Information Criterion (AIC) and prediction error metrics.

Main Results:

  • Models incorporating EQ-5D-3L dimension indicators showed the highest prediction accuracy.
  • Including a latent factor improved predictive accuracy and lowered AIC.
  • The developed mapping approach outperformed an alternative copula-based method.

Conclusions:

  • Novel algorithms for mapping EQ-5D-3L to EQ-5D-5L value sets were developed.
  • The recommended approach uses ordinal logistic regression with a latent factor.
  • This method offers accurate predictions for health state valuations.