ArticleHepatology international2017
Noninvasive serum models to predict significant liver related events in chronic hepatitis C.
Article in Hepatology international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Accurate prediction of HCC risk after SVR in patients with hepatitis C cirrhosis based on longitudinal data.BMC cancer · 2023Article
- Repeated Measurement of FIB-4 to Predict Long-Term Risk of HCC Development Up to 10 Years After SVR.Journal of hepatocellular carcinoma · 2022Article
- Non-invasive tests for predicting liver outcomes in chronic hepatitis C patients: A systematic review and meta-analysis.World journal of hepatology · 2021Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimWe aim to compare 20 noninvasive fibrosis scores (NIFS), derived from routine blood tests, for predicting significant liver-related adverse events (SLRE) in patients with chronic hepatitis C (CHC) after anti-viral treatment (AVT) with the goal to identify independent predictors for these outcomes.
methodsFrom 1605 patients who received AVT (pegylated interferon and ribavirin) from January 2002 to June 2014, 20 NIFS were calculated from routine blood tests prior to AVT. Areas under the receiver-operating characteristic curve (AUROC) were calculated for each of these NIFS for predicting non-response to AVT and development of SLRE on follow-up.
resultsMean age was 41.9 ± 9.7 years, and patients were predominantly genotype 4 (65%). After AVT, there were 1089 (67.8%) responders, 482 (30%) non-responders and 34 (2.1%) relapsers. After median follow-up of 6580.5 patient-years, 60 (3.8%) had SLRE, 52 (3.2%) had decompensation, and 11 (0.7%) had hepatocellular carcinoma (HCC). The predictive accuracy of NIFS and liver biopsy (LB) for non-response to AVT was low. FIB-4, FibroQ and King score showed high accuracy for predicting adverse events. For predicting decompensation, HCC and SLRE, FibroQ (0.881), King score (0.905) and FibroQ (0.877) had the highest AUROC, respectively. On multivariate analysis, independent predictors for treatment non-response (age, ALT, GGT, platelet count), HCC (albumin, GGT) and SLRE (albumin, GGT, platelet count) were identified.
conclusionsSome simple pretreatment blood parameters and NIFS showed high accuracy for predicting development of SLRE post treatment. Application of these simple scores can improve assessment of long-term liver prognosis for CHC.
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