Estimating EQ-5D-5L Utility Scores from the KDQoL-36 in Patients Undergoing Haemodialysis: A Mapping Algorithm for Economic Evaluation

Research Square (Research Square)(2023)

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摘要
Abstract Background The Kidney Disease Quality of Life Questionnaire (KDQoL-36) is used to capture meaningful changes in quality of life for patients with end stage kidney disease (ESKD). The KDQoL-36 scores highly in psychometric properties and is widely accepted by patients as it focuses directly on the specific symptoms ESKD patients suffer from. The KDQoL-36 is not a preference-based measure and therefore to-date cannot be used in cost-utility analyses for new health technologies. Aim To develop a mapping algorithm between the KDQoL-36 and EQ-5D-5L utility, based on the validated US value set, for patients with ESKD undergoing haemodialysis. Methods We mapped the KDQoL-36 onto the EQ-5D-5L using two direct mapping methods; linear regression with fixed effects and an adjusted limited dependent variable mixture model (ALDVMM). The KDQOL-36 subscale scores (physical component summary (PCS), mental component summary (MCS)), three disease-specific subscales or their average, and age and sex were included as explanatory variables. Predictive performance was assessed by; mean absolute error, root mean square error, AIC, BIC, and visual inspection of the predicted vs observed means and cumulative density function. Results The ALDVMM outperformed the linear model in all aspects of predictive performance. The preferred ALDVMM was the 3-component model that used the PCS, MCS, burden, symptom, effects, age, and sex as explanatory variables. Conclusions This study has bridged this gap by developing a mapping algorithm to allow EQ-5D-5L utility predictions from KDQoL-36 responses which can then be used in cost-utility analysis. We add to the current literature demonstrating the superiority of mixture models compared with linear regression in the prediction of EQ-5D-5L utility. The proposed algorithm to map the KDQOL-36 onto the EQ-5D-5L enables researchers to directly estimate an individual’s utility from KDQoL-36 responses. This study has a significant clinical impact as it allows any clinical trial that uses the KDQoL-36, to perform an economic evaluation alongside the trial.
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haemodialysis,economic evaluation
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