S2504 Predicting MASLD in People Living With HIV Using Anthropometric Measures: A Multicenter Cross-Sectional Study

Introduction: Metabolic dysfunction-associated steatotic liver disease (MASLD) is prevalent among HIV patients. Currently, diagnostic methods depend on costly imaging or invasive biopsy. Clinic-based anthropometric measures are easily accessible and may provide an alternative for early identification of individuals at risk. This study aimed to determine which anthropometric indicators best predict clinically significant hepatic steatosis in people living with HIV. Methods: A multicenter, cross-sectional study was conducted at 3 HIV clinics across the United States. Adults with virologically suppressed HIV (viral load <200 copies/mL) and without chronic hepatitis B/C or excessive alcohol use (AUDIT >5) underwent liver elastography. Controlled attenuation parameter (CAP) values were used to classify participants into 2 groups: low (S0–S1) and moderate-to-severe (S2–S3) steatosis. Anthropometric data, demographic information, and comorbidities were recorded. Area under the curve (AUC) was calculated to evaluate the predictive performance of BMI, weight, waist circumference, and waist-to-hip ratio. Results: Of 305 enrolled participants, 249 met inclusion criteria. The sample was predominantly man (68%), with a median age of 57. Among all anthropometric measures, waist circumference demonstrated the highest predictive accuracy for steatosis (AUC 0.78), followed by BMI (AUC 0.74), weight (AUC 0.71), and waist-to-hip ratio (AUC 0.68). Subgroup analyses confirmed that waist circumference was the most consistent predictor across sex, ethnicity, and age groups, with the highest accuracy in women (AUC 0.80) and non-Hispanic individuals (AUC 0.79). Conclusion: Waist circumference is a simple, reliable, and cost-effective predictor of MASLD in people living with HIV, outperforming BMI and other anthropometric measures. Its consistent performance across diverse subgroups underscores its potential utility in routine HIV care settings to identify patients at risk for steatosis and prompt further evaluation or early intervention.