Development and internal validation of a diagnostic prediction model for advanced liver fibrosis based on routine laboratory indicators

Clicks: 13
ID: 331996
2026
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Abstract
Abstract Introduction Advanced liver fibrosis is a clinically important stage of chronic liver disease. We developed and internally validated an interpretable model based on routine laboratory tests and benchmarked it against the aspartate aminotransferase to platelet ratio index (APRI) and 4-factor fibrosis index (FIB-4). Methods This single-center, retrospective, diagnostic prediction study included 1853 inpatients, of whom 988 had report-defined F3 to F4 fibrosis. Primary validation used 10 repeated, stratified 7:3 outer resamples, with preprocessing, least absolute shrinkage and selection operator selection, and model refitting restricted to each development subset. Discrimination, calibration, decision curves, precision recall performance, and linear SHapley Additive exPlanations values were evaluated. Results The leakage-aware pipeline achieved a mean (SD) validation area under the curve of 0.800 (0.015), accuracy of 0.753, sensitivity of 0.775, and specificity of 0.729. The final logistic model included platelet count, total bile acids, C3 and C4, red blood cell count, lymphocyte count, and albumin level. In the representative test set, its area under the curve was 0.809 (95% CI, 0.772-0.845) compared with 0.815 for APRI and 0.821 for FIB-4; neither paired difference was statistically significant after Holm adjustment. Discussion The model showed moderate discrimination and interpretable output but was not superior to APRI or FIB-4. External validation is required before clinical implementation.
Reference Key
openalex_W7221112388 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Junjie Deng, Wen Song, Yuyu Ma, Bin Fan, Xiumin Ma, Yumei Liu
Journal Clinical chemistry and laboratory medicine
Year 2026
DOI
10.1093/labmed/lmag053
URL
https://doi.org/10.1093/labmed/lmag053
Keywords Keywords not found

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