Evidence map›Paper›PMID 40692819›Full record

ArticleGastro hep advances2025

Assessments of Health Utilities in Patients With Metabolic Dysfunction-Associated Steatohepatitis: Cross-Walk Between Disease-Specific Chronic Liver Disease Questionnaire, Short Form SF-6D, and EuroQol EQ-5D Instruments.

Zobair M Younossi, Maria Stepanova, Yestle Kim, Stephen Dodge, Dominic Labriola, Rebecca Taub, Fatema Nader

Abstract read
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Article in Gastro hep advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zobair M YounossiThe Global MASH Council, Washington, District of Columbia.
Maria StepanovaThe Global MASH Council, Washington, District of Columbia.
Yestle KimMadrigal Pharmaceuticals, Conshohocken, Pennsylvania.
Stephen DodgeMadrigal Pharmaceuticals, Conshohocken, Pennsylvania.
Dominic LabriolaMadrigal Pharmaceuticals, Conshohocken, Pennsylvania.
Rebecca TaubMadrigal Pharmaceuticals, Conshohocken, Pennsylvania.
Fatema NaderThe Global MASH Council, Washington, District of Columbia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: The EuroQol-5D (EQ-5D) is a commonly used measure of health utilities to calculate quality-adjusted life years. For the clinical trials that use Chronic Liver Disease Questionnaire-nonalcoholic fatty liver disease (CLDQ-NAFLD) or Short Form-36 (SF-36), ability to convert the health-related quality of life scores (CLDQ-NAFLD or SF-36) to EQ-5D scores provides a valuable method to estimate health utility. Methods: Baseline data of noncirrhotic metabolic dysfunction-associated steatohepatitis (MASH) patients were used in this study. We used 2 cross-walk algorithms to estimate EQ-5D scores. The first algorithm used 6 domains of CLDQ-NAFLD in a fractional logistic model to yield EQ-5D estimates. The other algorithm included calculation of SF-6D utility scores from SF-36 items, which were fed into a regression model that estimated EQ-5D scores from SF-6D scores. Results: There were 883 MASH patients with CLDQ-NAFLD and SF-36 data: 25% ≥65 years, 44% male, 80% obese (body mass index >30), 67% type 2 diabetes, 62% F3 fibrosis, and 38% F1B/F2 fibrosis. The mean estimated EQ-5D scores were 0.851 (standard deviation = 0.146) according to CLDQ-NAFLD-based algorithm and 0.853 (standard deviation = 0.097) according to the SF-36-based algorithm. The correlations between the 2 estimated EQ-5D scores were up to +0.74. Similar to the total sample, the differences between the mean EQ-5D estimates using either calculation method did not exceed 0.012 in all studied subgroups (by age, sex, obesity, type 2 diabetes, and fibrosis stage). Conclusion: Both cross-walk algorithms for the calculation of the EQ-5D utility scores in MASH patients were estimable with CLDQ-NAFLD or SF-36 instruments. A high positive correlation was seen between the total score and subgroup estimates using either method.

Indexed as

Cost-Utility AssessmentDisease BurdenHealth-Related Quality of LifeMASLDQALY

Identifiers

PMID40692819
PMCPMC12277723

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.