Observational pilot study on non-invasive scores versus liver biopsy in the assessment of hepatic fibrosis: reflections in the context of current literature
Keywords:
„biomarkers”, „non-invasive scores”, „liver fibrosis”, „liver biopsy”Abstract
Serum biomarkers represent a key pillar in the non-invasive assessment of liver fibrosis. Although biopsy remains the gold standard, the APRI and FIB-4 scores have emerged as simple and accessible alternatives, particularly in healthcare systems with limited resources. The aim of the study was to evaluate the utility of the non-invasive diagnostic scores APRI and FIB-4 in identifying liver fibrosis, in comparison with histological findings from liver biopsy. The cross-sectional observational study included all patients with chronic liver disease who were hospitalized at the Republican Clinical Hospital (Chișinău) between 2019 and 2024 and underwent liver biopsy. APRI and FIB-4 scores were calculated based on clinical and biochemical data. Liver fibrosis was confirmed histologically. Results are expressed as mean ± standard error of the mean (M±SEM). The study sample included 22 patients, of whom 40.9% were male and 59.1% female, with a mean age of 44.5±2.7 years. The APRI score identified a high risk of liver fibrosis in 40.9% of patients (n=9), while the FIB-4 score indicated a high risk in 9.1% (n=2) and an intermediate risk in 22.7% (n=5). Liver fibrosis was histologically confirmed in 45.5% of patients (n=10). Discrepancies between non-invasive scores and biopsy findings may be attributed to their variable sensitivity and the characteristics of the study cohort. APRI and FIB-4 are useful tools for the initial evaluation of liver fibrosis. While APRI showed better alignment in excluding fibrosis, FIB-4 demonstrated higher accuracy in identifying advanced fibrosis and estimating intermediate risk.
References
AHMAD A., IMRAN M., AHSAN H. Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases. In: Pharmaceutics. Multidisciplinary Digital Publishing Institute (MDPI). 2023, vol.15, nr.1630, pp. 1-36. https://doi.org/10.3390/pharmaceutics15061630
BLANES-VIDAL V., LINDVIG KP., THIELE M., NADIMI ES., KRAG A. Artificial intelligence outperforms standard blood-based scores in identifying liver fibrosis patients in primary care. In: Sci Rep. 2022, vol.12, nr.11, pp. 1-11. https://doi.org/10.1038/s41598-022-06998-8
CEQUERA A., GARCIA DE LEON MENDEZ MC.. Biomarkers for liver fibrosis: Advances, advantages and disadvantages. In: Rev Gastroenterol México. 2014, vol.79, nr.3, pp.187-199. https://doi.org/10.1016/j.rgmx.2014.05.003
CHOWDHURY AB., MEHTA KJ. Liver biopsy for assessment of chronic liver diseases: a synopsis. In: Clinical and Experimental Medicine. Springer. 2023, vol.23, nr.2, pp. 273-285. https://doi.org/10.1007/s10238-022-00799-z
CUSI K., ABDELMALEK MF., APOVIAN CM., BALAPATTABI K., et al. Metabolic Dysfunction-Associated Stea totic Liver Disease (MASLD) in People With Diabetes: The Need for Screening and Early Intervention. A Consensus Report of the American Diabetes Association. In: Diabetes Care. 2025, pp.1-26. https://doi.org/10.2337/dci24-0094
FALLATAH HI. Noninvasive Biomarkers of Liver Fibrosis: An Overview. In: Adv Hepatol. 2014, vol.1, pp.1-15. https://doi.org/10.1155/2014/357287
GODFREY A., VANDENDRIESSCHE B., BAKKER JP., et al. Fit‐for‐Purpose Biometric Monitoring Technologies: Leveraging the Laboratory Biomarker Experience. In:Clin Transl Sci. 2020, vol.14, nr.1, pp.62-74. doi: 10.1111/CTS.12865.
https://doi.org/10.1111/cts.12865
JANG SY., YOON KT., CHO YY., JO HG., et al. Aspartate aminotransferase-to-platelet ratio index outperforms Fibrosis-4 in 2843 Korean patients with metabolic dysfunction-associated steatotic liver disease. In: Hepatol Res. 2024, vol.55, nr.4, pp.479-491. https://doi.org/10.1111/hepr.14143
LI Q., REN X., LU C., LI W., HUANG Y., CHEN L. Evaluation of APRI and FIB-4 for noninvasive assessment of significant fibrosis and cirrhosis in HBeAg-negative CHB patients with ALT≤2 ULN A retrospective cohort study. In: Medicine. 2017, vol.96, nr.12, pp.1-7. https://doi.org/10.1097/MD.0000000000006336
LIN ZH., XIN YN., DONG QJ., WANG Q., JIANG XJ., ZHAN SH., et al. Performance of the aspartate aminotransferase-to-platelet ratio index for the staging of hepatitis C-related fibrosis: An updated meta-analysis. In: Hepatology. 2011, vol. 53, nr.3, pp.726-736.
https://doi.org/10.1002/hep.24105
LUPAȘCO I., DUMBRAVA V.-T., VENGHER I., TARAN N., et al. Compendiul Repere esențiale în patologia hepato-biliară, cu elemente de nutriție. Ghid destinat medicilor de familie, medicilor generaliști și gastro-enterologilor care lucrează zi de zi cu pacienții cu diagnostic dificil. Chișinău: Garamont-Studio. 2022, 327 p. ISBN 978-9975-162-17-3.
MA S., ZHOU L., LIN S., LI M., LUO J., CHEN L. Noninvasive Models to Assess Liver Inflammation and Fibrosis in Chronic HBV Infected Patients with Normal or Mildly Elevated Alanine Transaminase Levels: Which One Is Most Suitable? In: Diagnostics. 2024, vol.14, nr.456, pp.1-19. https://doi.org/10.3390/diagnostics14050456
RATZIU V., MASSARD J., CHARLOTTE F., MESSOUS D., et al. Diagnostic value of biochemical markers (Fibro Test-FibroSURE) for the prediction of liver fibrosis in patients with non-alcoholic fatty liver disease. In: BMC Gastroenterol. 2006, vol.6, pp.1-13. https://doi.org/10.1186/1471-230X-6-6
SHAH AG., LYDECKER A., MURRAY K., TETRI BN., CONTOS MJ., et al. Comparison of noninvasive markers of fibrosis in patients with nonalcoholic fatty liver disease. In: Clin Gastroenterol Hepatol. 2009, vol.7, nr.10, pp.1104-1112. https://doi.org/10.1016/j.cgh.2009.05.033
SRIPONGPUN P., TANGKIJVANICH P., CHOTIYAPUTTA W., et al. Evaluation of aspartate aminotransferase to platelet ratio index and fibrosis 4 scores for hepatic fibrosis assessment compared with transient elastography in chronic hepatitis C patients. In: JGH Open. 2020, vol.4, nr.1, pp.69-74. https://doi.org/10.1002/jgh3.12219
SUGIYAMA A., KURISU A., BUNTHEN E., OUOBA S., et al. Distribution of FIB-4 index in the general population: analysis of 75,666 residents who underwent health checkups. In: BMC Gastroenterol. 2022, vol.22, nr.1, pp.1-10. https://doi.org/10.1186/s12876-022-02290-1
SUMIDA Y., YONEDA M., TOKUSHIGE K., KAWANAKA M., et al. FIB-4 first in the diagnostic algorithm of metabolic-dysfunction- associated fatty liver disease in the era of the global metabodemic. In: Life. 2021, vol.11, nr.2, pp.1-20. https://doi.org/10.3390/life11020143
TAGLIAFERRO M., MARINO M., BASILE V., POCINO K., et al. New Biomarkers in Liver Fibrosis: A Pass through the Quicksand? In: J Pers Med. 2024, vol 14, nr.798, pp.1-27. https://doi.org/10.3390/jpm14080798
UNALP-ARIDA A., RUHL CE. Liver fibrosis scores predict liver disease mortality in the United States population. In: Hepatology. 2017, vol.66, nr.1, pp.84-95. https://doi.org/10.1002/hep.29113
YANG R., GUI X., KE H., YU X., YAN Y., XIONG Y. Accuracy of FIB-4 and APRI scores compared to transient elastography for liver fibrosis in patients with HIV and HBV co-infection. In: Int J STD AIDS. 2023, vol.34, nr.1, pp.18-24. https://doi.org/10.1177/09564624221116530
21. YIN C., ZHANG H., DU J., ZHU Y., ZHU H., YUE H. Artificial intelligence in imaging for liver disease diagnosis. In: Frontiers in Medicine. 2025, vol.12, pp.1-10. doi: 10.3389/fmed.2025.1591523.22. Biopredictive. Paris, France. Disponibil pe: https://www.biopredictive.com/
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
