Alan Moore1, Carolyn A Young2, Dyfrig A Hughes3. 1. Centre for Health Economics and Medicines Evaluation, Bangor University, Bangor, UK. 2. The Walton Centre NHS Trust, Liverpool, UK. 3. Centre for Health Economics and Medicines Evaluation, Bangor University, Bangor, UK. Electronic address: d.a.hughes@bangor.ac.uk.
Abstract
BACKGROUND: The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) is the preferred measure of health outcome in clinical trials in motor neuron disease (MND). It, however, does not provide a preference-based health utility score required for estimating quality-adjusted life-years in economic evaluations for health technology assessments. OBJECTIVES: To develop algorithms for mapping from measures used in MND clinical studies to allow for future prediction of the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) utility in populations of patients with MND when utility data have not been collected. METHODS: Direct mapping models were developed using ordinary least squares and Tobit regression analyses to estimate EQ-5D-5L utilities (based on English tariffs), with ALSFRS-R total, domain, and item scores used as explanatory variables, using patient-level data from a UK cohort study. Indirect mapping models were also used to map EQ-5D-5L domains, using the same variables, along with the Neuropathic Pain Scale and the Hospital and Anxiety Depression Scale for MND using multinomial logistic regression analysis. Goodness of fit was assessed along with predicted values for each mapping model. RESULTS: The best-performing model predicting EQ-5D-5L utilities used five items of the ALSFRS-R items as explanatory variables in a stepwise ordinary least squares regression. The mean squared error was 0.0228, and the mean absolute error was 0.1173. Prediction was good, with 55.4% of estimated values within 0.1 and 91.4% within 0.25 of the observed EQ-5D-5L utility value. Indirect mapping using the Neuropathic Pain Scale and the Hospital and Anxiety Depression Scale for MND provided less predictive power than direct mapping models. CONCLUSIONS: This is the first study to present mapping algorithms to crosswalk between ALSFRS-R and EQ-5D-5L. This analysis demonstrates that the ALSFRS-R can be used to estimate EQ-5D-5L utilities when they have not been collected directly within a trial.
BACKGROUND: The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) is the preferred measure of health outcome in clinical trials in motor neuron disease (MND). It, however, does not provide a preference-based health utility score required for estimating quality-adjusted life-years in economic evaluations for health technology assessments. OBJECTIVES: To develop algorithms for mapping from measures used in MND clinical studies to allow for future prediction of the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) utility in populations of patients with MND when utility data have not been collected. METHODS: Direct mapping models were developed using ordinary least squares and Tobit regression analyses to estimate EQ-5D-5L utilities (based on English tariffs), with ALSFRS-R total, domain, and item scores used as explanatory variables, using patient-level data from a UK cohort study. Indirect mapping models were also used to map EQ-5D-5L domains, using the same variables, along with the Neuropathic Pain Scale and the Hospital and Anxiety Depression Scale for MND using multinomial logistic regression analysis. Goodness of fit was assessed along with predicted values for each mapping model. RESULTS: The best-performing model predicting EQ-5D-5L utilities used five items of the ALSFRS-R items as explanatory variables in a stepwise ordinary least squares regression. The mean squared error was 0.0228, and the mean absolute error was 0.1173. Prediction was good, with 55.4% of estimated values within 0.1 and 91.4% within 0.25 of the observed EQ-5D-5L utility value. Indirect mapping using the Neuropathic Pain Scale and the Hospital and Anxiety Depression Scale for MND provided less predictive power than direct mapping models. CONCLUSIONS: This is the first study to present mapping algorithms to crosswalk between ALSFRS-R and EQ-5D-5L. This analysis demonstrates that the ALSFRS-R can be used to estimate EQ-5D-5L utilities when they have not been collected directly within a trial.