Mapping ALSFRS-R and ALSUI to EQ-5D in patients with motor neurone disease

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Mapping ALSFRS-R and ALSUI to EQ-5D in patients with motor neurone disease. / Moore, Alan; Young, Carolyn A.; Hughes, Dyfrig.
In: Value in Health, Vol. 21, No. 11, 11.2018, p. 1322-1329.

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Moore A, Young CA, Hughes D. Mapping ALSFRS-R and ALSUI to EQ-5D in patients with motor neurone disease. Value in Health. 2018 Nov;21(11):1322-1329. Epub 2018 Jul 25. doi: 10.1016/j.jval.2018.05.005

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Moore, Alan ; Young, Carolyn A. ; Hughes, Dyfrig. / Mapping ALSFRS-R and ALSUI to EQ-5D in patients with motor neurone disease. In: Value in Health. 2018 ; Vol. 21, No. 11. pp. 1322-1329.

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TY - JOUR

T1 - Mapping ALSFRS-R and ALSUI to EQ-5D in patients with motor neurone disease

AU - Moore, Alan

AU - Young, Carolyn A.

AU - Hughes, Dyfrig

PY - 2018/11

Y1 - 2018/11

N2 - BackgroundThe 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.ObjectivesTo 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.MethodsDirect 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.ResultsThe 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.ConclusionsThis 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.

AB - BackgroundThe 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.ObjectivesTo 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.MethodsDirect 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.ResultsThe 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.ConclusionsThis 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.

U2 - 10.1016/j.jval.2018.05.005

DO - 10.1016/j.jval.2018.05.005

M3 - Article

VL - 21

SP - 1322

EP - 1329

JO - Value in Health

JF - Value in Health

SN - 1524-4733

IS - 11

ER -