Abstract

BackgroundThe EQ-5D-5 L is a quality-of-life questionnaire based on individuals’ preferences that is widely employed for cost-effectiveness analysis. Given the current demand for mapping algorithms to directly assign “utilities”, this study aimed to generate different mapping models for predicting EQ-5D-5 L utility values based on scores of the Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires provided by patients suffering from hip and knee osteoarthritis (OA), respectively, and to assess the predictive capability of these functions.MethodsThis was a prospective, observational study. Following the criteria of the American Rheumatism Association, 361 patients with hip OA and 397 with knee OA from three regions in Spain were included. Health-related quality of life (HRQoL) was assessed through the EQ-5D-5 L general questionnaire and the OHS and OKS specifically for lower limb OA.Based on the scores on the OHS and OKS questionnaires, EQ-5D-5 L utilities were estimated using 4 models: ordinary least squares (OLS), Tobit, generalized linear model (GLM), and beta regression (Breg).The models were validated on the same patients after 6 months: the mean absolute error (MAE) and mean squared error (MSE) with their 95% confidence intervals (CI), mean values of standard errors (SE), intraclass correlation coefficients (ICC), and Bland-Altman plots were obtained.ResultsThe lowest MAEs were obtained using GLM and Breg models, with values of 0.1103 (0.0993–0.1214) and 0.1229 (0.1102–0.1335) for hip OA, and values of 0.1127 (0.1014–0.1239) and 0.1141 (0.1031–0.1251) for knee OA. MSE values were also lower using GLM and Breg. ICCs between predicted and observed values were around or over the 0.8 cut-off point. Bland-Altman plots showed an acceptable correlation, but precision was lower for subjects with worse HRQoL, which was also evident when comparing MAEs of the bottom and top halves of the utilities scale. Predictive equations for utilities based on OHS/OKS scores were proposed.ConclusionsThe OHS and OKS scores allow for estimating EQ-5D-5 L utility indexes for patients with hip and knee OA, respectively, with adequate validity and precision. GLM and Breg produce the best predictions. The predictive power of proposed equations is more consistent for subjects in better health condition.

Highlights

  • The EQ-5D-5 L is a quality-of-life questionnaire based on individuals’ preferences that is widely employed for cost-effectiveness analysis

  • The Oxford Hip Score (OHS) and Oxford Knee Score (OKS) scores allow for estimating EQ-5D-5 L utility indexes for patients with hip and knee OA, respectively, with adequate validity and precision

  • This study aims to assess different mapping models that employ OHS and OKS scores reported by patients with hip and knee OA, respectively, for predicting utility values assigned by the EQ-5D-5 L questionnaire to particular health conditions, as well as assessing the predictive capability of these utility indexes

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Summary

Introduction

The EQ-5D-5 L is a quality-of-life questionnaire based on individuals’ preferences that is widely employed for cost-effectiveness analysis. Given the current demand for mapping algorithms to directly assign “utilities”, this study aimed to generate different mapping models for predicting EQ-5D-5 L utility values based on scores of the Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires provided by patients suffering from hip and knee osteoarthritis (OA), respectively, and to assess the predictive capability of these functions. Tools that measure HRQoL based on patient preferences are indispensable [1]. These tools allow individuals to express the impact of poor health on their lives and their preferences for certain health states. These preferences can be characterized as “utilities”, a measure of the strength of a person’s preference for a specific health state in relation to alternative health states. Health state preference scores can be transformed into quality-adjusted life years (QALYs), which are an outcome metric for health benefit used in many health economic evaluations [2]

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