PREFERENCES AND TRADE-OFFS FOR MASLD/MASH TESTING AMONG PATIENTS WITH TYPE 2 DIABETES: A DISCRETE CHOICE EXPERIMENT
Author(s)
Asmita Priyadarshini Khatiwada, MPharm1, Mesfin Genie, PhD2, Surachat Ngorsuraches, PhD1;
1Auburn University, Auburn, AL, USA, 2The University of Newcastle, Newcastle, Australia
1Auburn University, Auburn, AL, USA, 2The University of Newcastle, Newcastle, Australia
OBJECTIVES: To elicit and quantify the preferences of patients with type 2 diabetes (T2D) for metabolic dysfunction-associated steatotic liver disease (MASLD)/metabolic dysfunction-associated steatohepatitis (MASH) diagnostic tests, and to assess preference heterogeneity across test attributes.
METHODS: A cross-sectional, web-based discrete choice experiment (DCE) survey was conducted. Six test attributes, i.e., fasting time, invasiveness, sensitivity, specificity, prediction of liver-related events, and out-of-pocket cost, were obtained from the literature review and consultations with clinical experts and T2D patients. A D-efficient design was used to generate DCE choice tasks. Each choice task included two test alternatives, described by the test attributes with varying levels, plus an opt-out option. Data were collected from 226 T2D patients aged 18 years or above through the QualtricsXM panel. Preferences and preference heterogeneity were analysed using mixed logit and latent class models, and the relative importance of attributes was calculated.
RESULTS: The analytic sample comprised 218 patients. The preference weights of all attributes, except fasting time, were statistically significant and in the expected direction. The out-of-pocket cost was the most influential attribute (relative importance, 44.51%), followed by specificity (17.42%) and sensitivity (16.96%). Mixed logit estimates indicated significant preference heterogeneity for all attributes, except specificity and fasting time. Latent class analysis identified two preference groups: a 65.1% “pro-diagnostic test” class and a 34.9% “test-hesitant” class. In both classes, all attributes, except fasting time, remained statistically significant (p < 0.05) and in the expected direction, with greater dispersion in preference weights observed in the “test-hesitant” class.
CONCLUSIONS: T2D patients exhibited heterogeneity in preferences for MASLD/MASH tests, implying that a single “best” test may not align with all patients’ values. While the fasting time did not significantly influence preferences, the heterogeneity in how patients value other test attributes underscored the need to actively engage patients in clinical decision-making, ensuring that test choices align with patient priorities.
METHODS: A cross-sectional, web-based discrete choice experiment (DCE) survey was conducted. Six test attributes, i.e., fasting time, invasiveness, sensitivity, specificity, prediction of liver-related events, and out-of-pocket cost, were obtained from the literature review and consultations with clinical experts and T2D patients. A D-efficient design was used to generate DCE choice tasks. Each choice task included two test alternatives, described by the test attributes with varying levels, plus an opt-out option. Data were collected from 226 T2D patients aged 18 years or above through the QualtricsXM panel. Preferences and preference heterogeneity were analysed using mixed logit and latent class models, and the relative importance of attributes was calculated.
RESULTS: The analytic sample comprised 218 patients. The preference weights of all attributes, except fasting time, were statistically significant and in the expected direction. The out-of-pocket cost was the most influential attribute (relative importance, 44.51%), followed by specificity (17.42%) and sensitivity (16.96%). Mixed logit estimates indicated significant preference heterogeneity for all attributes, except specificity and fasting time. Latent class analysis identified two preference groups: a 65.1% “pro-diagnostic test” class and a 34.9% “test-hesitant” class. In both classes, all attributes, except fasting time, remained statistically significant (p < 0.05) and in the expected direction, with greater dispersion in preference weights observed in the “test-hesitant” class.
CONCLUSIONS: T2D patients exhibited heterogeneity in preferences for MASLD/MASH tests, implying that a single “best” test may not align with all patients’ values. While the fasting time did not significantly influence preferences, the heterogeneity in how patients value other test attributes underscored the need to actively engage patients in clinical decision-making, ensuring that test choices align with patient priorities.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
PCR82
Topic
Patient-Centered Research
Disease
SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity)