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Converting Parkinson-Specific Scores into Health State Utilities to Assess Cost-Utility Analysis

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Abstract

Objectives

The aim of this study was to compare the Parkinson’s Disease Questionnaire-8 (PDQ-8) with three multi-attribute utility (MAU) instruments (EQ-5D-3L, EQ-5D-5L, and 15D) and to develop mapping algorithms that could be used to transform PDQ-8 scores into MAU scores.

Methods

A cross-sectional study was conducted. A final sample of 228 evaluable patients was included in the analyses. Sociodemographic and clinical data were also collected. Two EQ-5D questionnaires were scored using Spanish tariffs. Two models and three statistical techniques were used to estimate each model in the direct mapping framework for all three MAU instruments, including the most widely used ordinary least squares (OLS), the robust MM-estimator, and the generalized linear model (GLM). For both EQ-5D-3L and EQ-5D-5L, indirect response mapping based on an ordered logit model was also conducted. Three goodness-of-fit tests were employed to compare the models: the mean absolute error (MAE), the root-mean-square error (RMSE), and the intra-class correlation coefficient (ICC) between the predicted and observed utilities.

Results

Health state utility scores ranged from 0.61 (EQ-5D-3L) to 0.74 (15D). The mean PDQ-8 score was 27.51. The correlation between overall PDQ-8 score and each MAU instrument ranged from − 0.729 (EQ-5D-5L) to − 0.752 (EQ-5D-3L). A mapping algorithm based on PDQ-8 items had better performance than using the overall score. For the two EQ-5D questionnaires, in general, the indirect mapping approach had comparable or even better performance than direct mapping based on MAE.

Conclusions

Mapping algorithms developed in this study enable the estimation of utility values from the PDQ-8. The indirect mapping equations reported for two EQ-5D questionnaires will further facilitate the calculation of EQ-5D utility scores using other country-specific tariffs.

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Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

JMAP, FISM, MAGG, and JCA conceived and designed the study. JMCF, MAGG, DCM, BPC, and JCA participated in the acquisition of the data. MAGG and JCA oversaw all stages of data collection and entry. GC, JMAP, and FISM contributed to interpretation of data and performed the statistical analyses. MAGG drafted the manuscript. JMCF and DCM provided critical reviews. GC and MJCF gave feedback on the manuscript and revised it critically for important intellectual content. DCM and MAGG reviewed the content of the manuscript. BPC and GC reviewed it in order to improve the grammar. All authors read and approved the first version sent and subsequent versions.

Author information

Authors and Affiliations

  1. College of Medicine and Public Health, Flinders University, Adelaide, Australia

    Gang Chen

  2. Facultad de Administración y Negocios, Universidad Autonoma de Chile, sede Talca, Chile

    Miguel A. Garcia-Gordillo

  3. Department of Applied Economics, Faculty of Economics and Business, University of Murcia, Murcia, Spain

    Miguel A. Garcia-Gordillo, José María Abellán-Perpiñán & Fernando Ignacio Sánchez-Martínez

  4. Faculty of Sport Sciences, University of Extremadura, Cáceres, Spain

    Daniel Collado-Mateo & José C. Adsuar

  5. Instituto de Calidad de Vida, Actividad Física y Salud, Universidad Autonoma de Chile, sede Talca, Chile

    Daniel Collado-Mateo

  6. Department of Sport and Exercise Science, University of Auckland, Auckland, New Zealand

    Borja del Pozo-Cruz

  7. Department of Economics, Faculty of Economics and Business, University of Extremadura, Badajoz, Spain

    José Manuel Cordero-Ferrera

Authors
  1. Gang Chen
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  2. Miguel A. Garcia-Gordillo
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  4. Borja del Pozo-Cruz
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Corresponding author

Correspondence to Miguel A. Garcia-Gordillo.

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None declared.

Conflicts of interest

GC has no conflicts of interest. MAGG has no conflicts of interest. DCM has no conflicts of interest. BPC has no conflicts of interest. JCA has no conflicts of interest. JMCF has no conflicts of interest. JMAP has no conflicts of interest. FISM has no conflicts of interest.

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Distributions of three multi-attribute utility instruments, N = 228 (DOC 175 kb)

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Chen, G., Garcia-Gordillo, M.A., Collado-Mateo, D. et al. Converting Parkinson-Specific Scores into Health State Utilities to Assess Cost-Utility Analysis. Patient 11, 665–675 (2018). https://doi.org/10.1007/s40271-018-0317-5

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