Nomogram model-based clinical prediction of advanced hepatic fibrosis in patients with chronic hepatitis B complicated by hepatic steatosis
Objective To identify the independent risk factors associated with advanced fibrosis(S3-S4)in patients suffering from chronic hepatitis B(CHB)complicated with hepatic steatosis,and to develop and validate a nomogram risk prediction model.Methods A total of 439 treatment-naïve CHB patients who had hepatic steatosis and underwent liver biopsy in the Third Affiliated Hospital of Sun Yat-sen University between August 2008 and December 2020 were recruited as research objects.These patients were then randomly allocated at a 2∶1 ratio into the training set(n=293)and the validation set(n=146).Logistic regression was used to identify the risk factors of advanced fibrosis.A nomogram prediction model was subsequently created.Results Logistic regression analysis revealed that platelet(OR=0.987,P=0.003),prothrombin time(OR=1.952,P=0.011),and globulin(OR=1.260,P=0.001)were the independent risk factors for advanced fibrosis.The area under the receiver operating characteristic(ROC)curve for the proposed nomogram model in the training group,which predicted advanced fibrosis,was noted to be 0.866.This was considerably higher than the aspartate aminotransferase-to-platelet ratio index(0.782,P=0.017),gamma-glutamyl transpeptidase-to-platelet ratio(0.753,P=0.004),fibrosis-4 score(0.780,P=0.024),non-alcoholic fatty liver disease fibrosis score(0.737,P<0.001),and BARD score(0.595,P<0.001)models;similar findings were observed in the validation set(P<0.05).Calibration curve and decision curve demonstrated that the nomogram model had high consistency and clinical net benefit.Conclusion A nomogram risk prediction model based on independent risk factors of advanced liver fibrosis patients with CHB combined with hepatic steatosis is constructed in this study.After verification,the model has high predictive efficiency,consistency,and clinical net gain.
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