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 Madan (), Kamran A. Khan, Stavros Petrou and Sarah E. Lamb
Additional contact information
Jason Madan: Warwick Medical School, University of Warwick
Kamran A. Khan: Warwick Medical School, University of Warwick
Stavros Petrou: Warwick Medical School, University of Warwick
Sarah E. Lamb: University of Oxford

PharmacoEconomics, 2017, vol. 35, issue 5, No 5, 549-559

Abstract: 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.

Date: 2017
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s40273-016-0483-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:pharme:v:35:y:2017:i:5:d:10.1007_s40273-016-0483-z

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40273

DOI: 10.1007/s40273-016-0483-z

Access Statistics for this article

PharmacoEconomics is currently edited by Timothy Wrightson and Christopher I. Carswell

More articles in PharmacoEconomics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().