Health and quality of life outcomes · 2023
Cross-walk of the Chronic Liver Disease Questionnaire for Nonalcoholic Steatohepatitis (CLDQ-NASH) and the EuroQol EQ-5D-5L in patients with NASH.
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Fishman Jesse, Higgins Victoria, Piercy James, Pike James
Аннотация
BACKGROUND: Nonalcoholic steatohepatitis (NASH) is a chronic progression of nonalcoholic fatty liver disease, which can negatively impact the health-related quality of life (HRQoL) of affected individuals. HRQoL in NASH has been assessed using the disease-specific Chronic Liver Disease Questionnaire for NASH (CLDQ-NASH) and the generic EuroQol EQ-5D-5L. As the performance of these instruments relative to each other is unknown, we performed a cross-walk analysis of CLDQ-NASH to EQ-5D-5L using data from a real-world NASH population.
METHODS: Data were drawn from the Adelphi Real World 2019 NASH Disease Specific Programme, a cross-sectional survey of physicians and their patients in the United States. Patients with physician-diagnosed NASH completed a questionnaire that included the CLDQ-NASH and EQ-5D-5L. Mapping from CLDQ-NASH to EQ-5D-5L was done using tenfold cross-validation; performance was assessed using root-mean squared error as accuracy measure. Subgroup analyses compared performance of the models in obese versus non-obese patients and patients with versus without type 2 diabetes (T2D).
RESULTS: Data from 347 patients were included in this analysis. Overall, 2172 models were tested for predicting EQ-5D-5L index score from CLDQ-NASH score. The best model for this mapping was a generalized linear model using Gaussian distribution and a power link. The best model for mapping from CLDQ-NASH domains to the EQ-5D-5L was a fractional logistic model. Models performed better at predicting upper versus lower values of EQ-5D-5L, for non-obese versus obese patients, and for patients without versus with T2D.
CONCLUSION: We describe a scoring algorithm for cross-walking the CLDQ-NASH to the EQ-5D-5L enabling health status comparisons of HRQoL across studies.
METHODS: Data were drawn from the Adelphi Real World 2019 NASH Disease Specific Programme, a cross-sectional survey of physicians and their patients in the United States. Patients with physician-diagnosed NASH completed a questionnaire that included the CLDQ-NASH and EQ-5D-5L. Mapping from CLDQ-NASH to EQ-5D-5L was done using tenfold cross-validation; performance was assessed using root-mean squared error as accuracy measure. Subgroup analyses compared performance of the models in obese versus non-obese patients and patients with versus without type 2 diabetes (T2D).
RESULTS: Data from 347 patients were included in this analysis. Overall, 2172 models were tested for predicting EQ-5D-5L index score from CLDQ-NASH score. The best model for this mapping was a generalized linear model using Gaussian distribution and a power link. The best model for mapping from CLDQ-NASH domains to the EQ-5D-5L was a fractional logistic model. Models performed better at predicting upper versus lower values of EQ-5D-5L, for non-obese versus obese patients, and for patients without versus with T2D.
CONCLUSION: We describe a scoring algorithm for cross-walking the CLDQ-NASH to the EQ-5D-5L enabling health status comparisons of HRQoL across studies.