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
University of Medicine and Pharmacy of Craiova, Petru-Rareș Street No. 2, 200349 Craiova, Romania.
Department of Natural Sciences, National University of Science and Technology Politehnica Bucharest, Piteşti University Centre, 1st Targu din Vale Str., 110040 Pitesti, Romania.
Diagnostics (Basel). 2025 Jun 20;15(13):1575. doi: 10.3390/diagnostics15131575.
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). : 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. 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. 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.
用于肝纤维化评估的非侵入性检测的临床应用已引起越来越多的关注,尤其是在诊断晚期纤维化(≥F3)方面。这项观察性研究旨在评估九种直接生物标志物和七种间接生物标志物在四种病因中的分层准确性,这四种病因分别为:慢性乙型肝炎(CHB)、慢性丙型肝炎(CHC)、酒精性肝硬化(ALC)和非酒精性肝硬化(NALC)。我们的研究对116名参与者进行,其中包括96名慢性肝病患者(16名CHB、15名CHC、49名ALC和16名NALC)以及20名健康对照者。分析了直接生物标志物(天冬氨酸转氨酶、丙氨酸转氨酶、总胆红素、血清白蛋白、血小板计数、国际标准化比值、γ-谷氨酰转肽酶、CD5抗原样分子和转化生长因子-β1)和间接非血清学生物标志物(德瑞蒂斯比值、白蛋白-胆红素评分、γ-谷氨酰转肽酶与血小板比值、天冬氨酸转氨酶与血小板比值指数、纤维化-4指数、国际标准化比值与血小板比值以及纤维化商数)在纤维化分层中的判别能力。统计分析显示存在显著相关性(0.05水平;双侧),并且在所有病因中,直接和间接生物标志物值之间的AUC 95%置信区间在0.50至1.00范围内。在评估的生物标志物中,CHB中APRI的记录AUC为0.998,CHC中FIB-4的AUC为0.981,ALC和NALC中APRI和AST的AUC分别为1.000,而CD5L在所有病因中始终达到1.000的AUC。这些发现表明,与使用单个生物标志物相比,在肝脏病理学中采用多因素方法可能会提高诊断准确性,并可为临床适用的数学模型的开发提供参考数据。
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