Platelet count as a predictor of advanced-stage liver cirrhosis: a comparative study with established fibrosis markers
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Accurate assessment of liver fibrosis is critical for the management of chronic liver disease. Noninvasive biomarkers are increasingly being investigated as alternatives to liver biopsy. Platelet count has emerged as a potential predictor of advanced fibrosis and may complement established indices such as the fibrosis-4 (FIB-4) score and the aspartate aminotransferase-to-platelet ratio index (APRI).Methods: This prospective analysis included 101 patients with histologically confirmed data obtained through liver biopsy or hepatic resection. Platelet count, APRI, FIB-4, Model for End-Stage Liver Disease score, Mac-2 binding protein glycosylation isomer (M2BPGi), and albumin-bilirubin score were measured and correlated with fibrosis stage using the METAVIR scoring system. Logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to assess the predictive performance of each marker.Results: Platelet count demonstrated an inverse correlation with fibrosis severity and was identified as the most reliable predictor of advanced fibrosis (METAVIR ≥3), with an area under the ROC curve of 0.822. Using a cutoff value of 184,000, platelet count yielded a sensitivity of 69.2% and a specificity of 87.8% for the detection of significant fibrosis.Conclusions: Platelet count is a simple, widely available, and robust predictor of liver fibrosis, outperforming APRI, FIB-4, and M2BPGi in multivariate analysis. Validation in larger, independent cohorts is warranted to confirm its clinical utility.
Source: Kosin Medical Journal
DOI: 10.7180/kmj.25.143
Authors: Hyung Hwan Moon, Kwang Il Seo, Hyunyong Hwang, Young Il Choi, Dong Hoon Shin, Myunghee Yoon, Bohyeon Kim, Yeha Joo
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7117310882