Development and Validation of the Steatotic Liver Disease Lab Data Index: A Refined Diagnostic Tool.

aimsSteatotic liver disease (SLD) is highly prevalent, yet large-scale identification remains challenging because imaging is not always available and existing noninvasive indices perform heterogeneously across subgroups. We developed and validated sex- and age-stratified laboratory-based indices for simplified SLD identification.

methodsWe analyzed 2085 adults from NHANES III (1988-1994). An exposure-wide association study (EWAS) of 119 clinical features informed sex- and age-stratified logistic models to derive two SLD lab data indices (SLDLD1-2) and simplified categorical versions (SSLDLD1-2). Discrimination (AUROC) was compared with FLI, HSI, NAFLD-LFS, and US-FLI using paired DeLong tests. Bootstrap internal validation, comparison with a pooled nonstratified model, and decision curve analysis were additionally performed. External validation was performed for SSLDLD1 in NHANES 2017-2018 and the Taiwan MJ Health database. SLDLD2/SSLDLD2 were not externally validated because C-peptide was unavailable in both datasets.

resultsCentral adiposity and insulin-resistance markers were key predictors, whereas β-carotene showed an inverse association and contributed to discrimination, particularly in men. Across strata, SLDLD1 achieved AUROCs of 0.71-0.79 in derivation. The stratified framework outperformed a pooled nonstratified model in the overall cohort, in men, and in women aged < 55 years. SLDLD1 also outperformed FLI and HSI across strata and showed superior or comparable performance versus NAFLD-LFS and US-FLI, with stratum-dependent differences. External validation of SSLDLD1 yielded AUROCs of 0.71-0.80 across datasets. Feature-reduction analysis and an MJ-variables-only implementation of SSLDLD1 showed only small absolute AUROC changes overall, supporting simplified implementation when nonroutine biomarkers such as β-carotene and insulin are unavailable, although fixed NHANES III-derived thresholds were not fully transferable to the MJ cohort.

conclusionThe stratified SLDLD framework provides a practical toolbox for SLD identification, supporting high-throughput research and implementation in settings where advanced imaging is not readily available. SSLDLD1 showed acceptable external discrimination across U.S. and Taiwanese datasets and may be more feasible for settings without nonroutine biomarkers, although local recalibration and validation of decision thresholds are needed before implementation across populations. ABBREVIATIONS: AASLD, American Association for the Study of Liver Diseases; AIC, Akaike information criterion; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; AUROC, area under the receiver-operating. characteristic curve; BMI, body mass index; CAP, controlled attenuation parameter; CI, confidence interval; CMRF, cardiometabolic risk factor; DM, diabetes mellitus; EWAS, exposure-wide association study; FLI, fatty liver index; FSI, Framingham steatosis index; FPG, fasting plasma glucose; GGT, gamma-glutamyl transferase; HbA1c, glycated hemoglobin; HCC, hepatocellular carcinoma; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; HSI, hepatic steatosis index; IR, insulin resistance; LDL, low-density lipoprotein; MCHC, mean corpuscular hemoglobin concentration; MJ, MJ Health (Taiwan); NAFLD, nonalcoholic fatty liver disease; NAFLD-LFS, nonalcoholic fatty liver disease liver fat score; NHANES, National Health and Nutrition Examination Survey; NPV, negative predictive value; PPV, positive predictive value; SLD, steatotic liver disease; SLDLD, steatotic liver disease lab data; SLDLD1/SLDLD2, steatotic liver disease lab data indices 1/2; SSLDLD, simplified steatotic liver disease lab data; SSLDLD1/SSLDLD2, simplified steatotic liver disease lab data indices 1/2; TG, triglyceride; US-FLI, US fatty liver index; VCTE, vibration-controlled transient elastography; WC, waist circumference; WHR, waist-to-hip ratio.