Mapping the NASH-CHECK to the EQ-5D-5L in a MASLD population in seven European countries

Abstract

Abstract Background Metabolic-dysfunction associated steatotic liver disease (MASLD) is a progressive chronic liver condition characterised by substantial inter-patient variation in disease severity, with the probability of progressing to hepatic fibrosis, cirrhosis or hepatocellular carcinoma. The prevalence of MASLD is increasing rapidly and may have a significant impact on health-related quality of life (HRQoL). A novel non-preference-based Patient-Reported Outcome Measure (PROM) called NASH-CHECK has been developed to assess outcomes in metabolic dysfunction-associated steatohepatitis (MASH), previously called non-alcoholic steatohepatitis (NASH). Preference-based outcome measures are needed to generate quality adjusted life years (QALYs) for economic evaluation. The aim of this study was to generate mapping algorithms to predict EQ-5D-5L utility scores from the NASH-CHECK in a MASLD population. Method A large dataset comprising 1,971 MASLD cases from seven European countries (France, Italy, Portugal, Netherlands, Spain, Sweden and UK) was used to generate the mapping algorithms. Regression results from a number of popular candidate models were compared against each other in terms of statistical and visual fit, including more conventional models (OLS, Tobit, Two-Part) and the more recently developed Adjusted Limited Dependent Variable Mixture Model (ALDVMM). Mapping was conducted separately for each of the seven countries. Results The ALDVMM with higher numbers of components provided the best visual fit across all samples, especially at the low end (representing very poor health states and worse-than-death health states) and high end (representing fairly good health states and full health) of the EQ-5D-5L distributions. The ALDVMM also produced predicted estimates which had the best statistical fit (in terms of mean absolute error, root mean square error and information criteria where applicable) for samples with relatively large number of observations. Conclusions Using an ALDVMM with higher numbers of components provides estimates across the whole distribution for the prediction of EQ-5D-5L as a function of NASH-CHECK scores for people with MASLD in several European countries. This enables QALYs to be indirectly calculated in this patient population when a preference-based measure such as the EQ-5D-5L has not been collected.