ArticleBMC gastroenterology2021
Nomogram for predicting advanced liver fibrosis and cirrhosis in patients with chronic liver disease.
Article in BMC gastroenterology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 15 citations in OpenAlex.
- A precision-constrained framework for evaluating noninvasive biomarkers in MASLD and beyond.Nature communications · 2026Article
- Article
- Performance of Blood-Based Indirect Scores Compared to Transient Elastography in Children with Chronic Liver Disease.Diagnostics (Basel, Switzerland) · 2026Article
- Efficacy of endoscopic therapy in patients with T1b gastric cancer and construction of a prognostic prediction model: a retrospective cohort study and multicenter validation study.Surgical endoscopy · 2026Article
- A Machine Learning-Based Model for Cirrhosis Risk Stratification Incorporating Noninvasive Markers and Clinical Variables.International journal of general medicine · 2026Article
- Article
- Development and validation of a nomogram for predicting advanced liver fibrosis in patients with chronic hepatitis B.Frontiers in molecular biosciences · 2024Article
- The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci.Open medicine (Warsaw, Poland) · 2024Article
- Development of a Novel Nomogram Incorporating Red Blood Cell Distribution Width-Albumin Ratio for the Prediction of 30-day Mortality in Acute Pancreatitis Patients.Emergency medicine international · 2022Article
- Computed Tomography Radiomics-Based Prediction of Microvascular Invasion in Hepatocellular Carcinoma.Frontiers in medicine · 2022Article
- A Generic Nomogram Predicting the Stage of Liver Fibrosis Based on Serum Biochemical Indicators Among Chronic Hepatitis B Patients.Frontiers in medicine · 2021Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
backgroundWe aimed to formulate a novel predictive nomogram to discriminate liver fibrosis stage in patients with chronic liver disease.
methodsNomograms were established based on the results of multivariate analysis. The predictive accuracy of the nomograms was assessed by ROC analysis and calibration. Decision curve analysis (DCA) was used to determine the clinical benefit of the nomograms.
resultsINR, platelets, and N-terminal propeptide type III collagen (PIIINP) were independent predictors for advanced liver fibrosis (≥ S3) and cirrhosis (S4) in patients with chronic liver disease in the training cohort. In the training set, the areas under the ROCs (AUROCs) of nomogram S3S4, APRI, FIB-4, and GPR for stage ≥ S3 were 0.83, 0.71, 0.68, and 0.74, respectively; the AUROCs of nomogram S4, APRI, FIB-4, and GPR for stage S4 were 0.88, 0.74, 0.78, and 0.79, respectively. The calibrations showed optimal agreement between the prediction by the established nomograms and actual observation. In the validation set, the AUROCs of nomogram S3S4, APRI, FIB-4, and GPR for stage ≥ S3 were 0.86, 0.79, 0.78, and 0.81, respectively; the AUROCs of nomogram S4, APRI, FIB-4, and GPR for stage S4 were 0.88, 0.77, 0.81, and 0.83, respectively. Furthermore, the decision curve analysis suggested that the nomograms represent better clinical benefits in both independent cohorts than APRI, FIB-4, and GPR.
conclusionThe constructed nomograms could be a superior tool for discriminating advanced fibrosis and cirrhosis in chronic liver disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.