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PharmacoEconomics

, Volume 35, Issue 5, pp 549–559 | Cite as

Can Mapping Algorithms Based on Raw Scores Overestimate QALYs Gained by Treatment? A Comparison of Mappings Between the Roland–Morris Disability Questionnaire and the EQ-5D-3L Based on Raw and Differenced Score Data

  • Jason MadanEmail author
  • Kamran A. Khan
  • Stavros Petrou
  • Sarah E. Lamb
Original Research Article

Abstract

Introduction

Mapping algorithms are increasingly being used to predict health-utility values based on responses or scores from non-preference-based measures, thereby informing economic evaluations.

Objectives

We explored whether predictions in the EuroQol 5-dimension 3-level instrument (EQ-5D-3L) health-utility gains from mapping algorithms might differ if estimated using differenced versus raw scores, using the Roland–Morris Disability Questionnaire (RMQ), a widely used health status measure for low back pain, as an example.

Methods

We estimated algorithms mapping within-person changes in RMQ scores to changes in EQ-5D-3L health utilities using data from two clinical trials with repeated observations. We also used logistic regression models to estimate response mapping algorithms from these data to predict within-person changes in responses to each EQ-5D-3L dimension from changes in RMQ scores. Predicted health-utility gains from these mappings were compared with predictions based on raw RMQ data.

Results

Using differenced scores reduced the predicted health-utility gain from a unit decrease in RMQ score from 0.037 (standard error [SE] 0.001) to 0.020 (SE 0.002). Analysis of response mapping data suggests that the use of differenced data reduces the predicted impact of reducing RMQ scores across EQ-5D-3L dimensions and that patients can experience health-utility gains on the EQ-5D-3L ‘usual activity’ dimension independent from improvements captured by the RMQ.

Conclusion

Mappings based on raw RMQ data overestimate the EQ-5D-3L health utility gains from interventions that reduce RMQ scores. Where possible, mapping algorithms should reflect within-person changes in health outcome and be estimated from datasets containing repeated observations if they are to be used to estimate incremental health-utility gains.

Notes

Acknowledgements

The authors thank all study investigators and participants for their role in collecting the primary data.

Author contributions

JM, KAK, SP: study concept and design. SP, SEL: acquisition of data. All authors participated in the analysis and interpretation of the data and the preparation of the manuscript.

Compliance with Ethical Standards

Although no funding directly supported this study, the authors benefitted from facilities funded through the Birmingham Science City Translational Medicine Clinical Research and Infrastructure Trials Platform, with support from Advantage West Midlands (AWM) and the Wolfson Foundation.

Conflict of interest

J Madan, KA Khan, S Petrou and SE Lamb have no conflicts of interest.

Data availability statement

This study uses data from two published clinical trials. For access to these data, please contact the corresponding authors of the relevant publications. The models used to analyse these data and generate the results reported in this study are available from the corresponding author on request.

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Warwick Clinical Trials Unit, Division of Health SciencesWarwick Medical School, University of WarwickCoventryUK
  2. 2.Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Medical Science DivisionUniversity of OxfordOxfordUK

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