Publications : 2023

Bean K, Miller B, Jensen I, Fields C, Pang F. Evaluating the face validity of health state utility values (HSUVS) for metachromatic leukodystrophy (MLD). Abstract EE285. ISPOR 2023.

Abstract

Objectives

MLD is an ultra-rare, rapidly progressive neurodegenerative disease, which leads to motor and cognitive decline, resulting in increasingly poor quality of life and premature death. This study evaluated the face validity of MLD specific utility values in relation to published utility values for other severe rare genetic diseases.

Methods

Health state vignettes grounded by the validated seven stage Gross Motor Function Classification for MLD (GMFC-MLD) measure were developed and valued by the UK general public using the time trade-off method to generate HSUVs. These values were subsequently calibrated using a simple algorithm involving the EQ-5D tariff specific to the country of interest to reflect the societal preferences for that country. Utilities by disease stage for other analogue diseases (i.e., rare, progressive, neuromuscular disorders) were systematically identified and extracted from published literature and compared to corresponding disease stages for MLD.

Results

EQ-5D-calibrated HSUVs from the MLD study were found to be similar to published utilities for health states of analogue rare progressive diseases. For example, the disease stages GMFC-MLD 1-3 are comparable to ALD-DRS I, II and III in X-linked adrenoleukodystrophy (ALD) in terms of motor progression. Mean utilities for the X-linked ALD disease stages using the UK EQ-5D tariff were reported to align with the mean utilities of the GMFC-MLD disease stages 1-3, respectively. For CLN-2, published UK EQ-5D derived utility values for the most severe stages of the disease were found to be comparable to the UK EQ-5D calibrated utility values for the more severe stages of MLD, GMFC-MLD 4-6.

Conclusions

This study demonstrates that GMFC-MLD HSUVs have face validity when compared to published values for other progressive rare genetic diseases, and provide a reliable basis for use in health technology assessments.