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Frequentist and Bayesian meta‐regression of health state utilities for multiple myeloma incorporating systematic review and analysis of individual patient data

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  • Anthony J. Hatswell
  • Darren Burns
  • Gianluca Baio
  • Frances Wadelin

Abstract

This analysis presents the results of a systematic review for health state utilities in multiple myeloma, as well as analysis of over 9,000 observations taken from registry and trial data. The 27 values identified from 13 papers are then synthesised in a frequentist nonparametric bootstrap model and a Bayesian meta‐regression. Results were similar between the frequentist and Bayesian models with low utility on disease diagnosis (approximately 0.55), raising to approximately 0.65 on first line treatment and declining slightly with each subsequent line. Stem cell transplant was also found to be a significant predictor of health‐related quality of life in both individual patient data and meta‐regression, with an increased utility of approximately 0.06 across different models. The work presented demonstrates the feasibility of Bayesian methods for utility meta‐regression, whilst also presenting an internally consistent set of data from the analysis of registry data. To facilitate easy updating of the data and model, data extraction tables and model code are provided as Data S1. The main limitations of the model relate to the low number of studies available, particularly in highly pretreated patients.

Suggested Citation

  • Anthony J. Hatswell & Darren Burns & Gianluca Baio & Frances Wadelin, 2019. "Frequentist and Bayesian meta‐regression of health state utilities for multiple myeloma incorporating systematic review and analysis of individual patient data," Health Economics, John Wiley & Sons, Ltd., vol. 28(5), pages 653-665, May.
    • Handle: RePEc:wly:hlthec:v:28:y:2019:i:5:p:653-665
    DOI: 10.1002/hec.3871
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    References listed on IDEAS

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    1. Samer A. Kharroubi & Richard Edlin & David Meads & Chantelle Browne & Julia Brown & Christopher McCabe, 2015. "Use of Bayesian Markov Chain Monte Carlo Methods to Estimate EQ-5D Utility Scores from EORTC QLQ Data in Myeloma for Use in Cost-Effectiveness Analysis," Medical Decision Making, , vol. 35(3), pages 351-360, April.
    2. Tessa Peasgood & John Brazier, 2015. "Is Meta-Analysis for Utility Values Appropriate Given the Potential Impact Different Elicitation Methods Have on Values?," PharmacoEconomics, Springer, vol. 33(11), pages 1101-1105, November.
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