ArticlePloS one2021
A novel noninvasive formula for predicting cirrhosis in patients with chronic hepatitis C.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Association of small intestinal bacterial overgrowth with portal hypertension in HCV-related cirrhosis: a cross-sectional study.Clinical and experimental medicine · 2026Article
- Evaluation of soluble suppression of tumorigenicity 2 (sST2) as serum marker for liver fibrosis.BMC gastroenterology · 2024Article
- Non-Invasive Measurement of Hepatic Fibrosis by Transient Elastography: A Narrative Review.Viruses · 2023Review
- Machine Learning Approaches for the Prediction of Hepatitis B and C Seropositivity.International journal of environmental research and public health · 2023Article
- Article
- Dynamics of type IV collagen 7S fragment on eradication of HCV with direct antiviral agents: Prognostic and metabolomic impacts.PloS one · 2022Observational
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Authors and funding
28 authors at 13 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evaluating liver fibrosis is crucial for disease severity assessment, treatment decisions, and hepatocarcinogenic risk prediction among patients with chronic hepatitis C. In this retrospective multicenter study, we aimed to construct a novel model formula to predict cirrhosis. A total of 749 patients were randomly allocated to training and validation sets at a ratio of 2:1. Liver stiffness measurement (LSM) was made via transient elastography using FibroScan. Patients with LSM ≥12.5 kPa were regarded as having cirrhosis. The best model formula for predicting cirrhosis was constructed based on factors significantly and independently associated with LSM (≥12.5 kPa) using multivariate regression analysis. Among the 749 patients, 198 (26.4%) had LSM ≥12.5 kPa. In the training set, multivariate analysis identified logarithm natural (ln) type IV collagen 7S, ln hyaluronic acid, and ln Wisteria floribunda agglutinin positive Mac-2-binding protein (WFA+-Mac-2 BP) as the factors that were significantly and independently associated with LSM ≥12.5 kPa. Thus, the formula was constructed as follows: score = -6.154 + 1.166 × ln type IV collagen 7S + 0.526 × ln hyaluronic acid + 1.069 × WFA+-Mac-2 BP. The novel formula yielded the highest area under the curve (0.882; optimal cutoff, -0.381), specificity (81.5%), positive predictive values (62.6%), and predictive accuracy (81.6%) for predicting LSM ≥12.5 kPa among fibrosis markers and indices. These results were almost similar to those in the validated set, indicating the reproducibility and validity of the novel formula. The novel formula scores were significantly, strongly, and positively correlated with LSM values in both the training and validation data sets (correlation coefficient, 0.721 and 0.762; p = 2.67 × 10-81 and 1.88 × 10-48, respectively). In conclusion, the novel formula was highly capable of diagnosing cirrhosis in patients with chronic hepatitis C and exhibited better diagnostic performance compared to conventional fibrosis markers and indices.
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