Evaluating the Discriminative Performance of Noninvasive Biomarkers in Chronic Hepatitis B/C, Alcoholic Cirrhosis, and Nonalcoholic Cirrhosis: A Comparative Analysis.

阅读:31
作者:Dumitrache Păunescu Alina, Ionescu Șuțan Nicoleta Anca, Țânțu Monica Marilena, Ponepal Maria Cristina, Soare Liliana Cristina, Țânțu Ana Cătălina, Atamanalp Muhammed, Baniță Ileana Monica, Pisoschi Cătălina Gabriela
Introduction: The clinical implementation of noninvasive tests for liver fibrosis assessment has attracted increasing attention, particularly for diagnosing advanced fibrosis (≥F3). This observational study aimed to evaluate the stratification accuracy of nine direct and seven indirect biomarkers across four etiologies: chronic hepatitis B (CHB), chronic hepatitis C (CHC), alcoholic liver cirrhosis (ALC), and nonalcoholic liver cirrhosis (NALC). Materials and Methods: Our study was conducted on 116 participants, including 96 with chronic liver disease (16 CHB, 15 CHC, 49 ALC, and 16 NALC) and 20 healthy controls. The values of direct (aspartate aminotransferase, alanine aminotransferase, total bilirubin, serum albumin, platelet count, international normalized ratio, gamma-glutamyl transpeptidase, CD5 antigen-like, and transforming growth factor-beta 1) and indirect non-serological biomarkers (De Ritis ratio, albumin-bilirubin score, gamma-glutamyl transpeptidase-to-platelet ratio, aspartate aminotransferase-to-platelet-ratio index, fibrosis-4 index, INR-to-platelet ratio, and fibrosis quotient) were analyzed for their discriminative power in fibrosis stratification. Results: Statistical analyses revealed a significant correlation (0.05 level; two-tailed), and AUC 95% CI ranged within 0.50-1.00 between the direct and indirect biomarker values across all etiologies. Among the evaluated biomarkers, the recorded AUC was 0.998 in CHB for APRI, 0.981 in CHC for FIB-4, and 1.000 in ALC and NALC for APRI and AST, respectively, while CD5L consistently achieved an AUC of 1.000 across all etiologies. Conclusions: These findings suggest that applying a multifactorial approach in liver pathology may improve diagnosis accuracy compared to the use of individual biomarkers and can provide data that may inform the development of clinically applicable mathematical models.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。