Objective: To establish a novel nomogram for diagnosing liver fibrosis in patients with chronic hepatitis B virus (HBV) infection and verify the diagnostic performance of the established nomogram.
Methods: Patients with chronic HBV infection who met the inclusion and exclusion criteria were enrolled in this retrospective study; 70% and 30% of patients were randomly assigned to training dataset and validation dataset, respectively. The risk factors for liver fibrosis were screened using the univariate and multivariate logistic regression analyses. Based on the results, a nomogram was established and verified.
Results: 508 patients with chronic HBV infection were included in this study ( = 355 for training dataset and = 153 for validation dataset). The logistic regression analysis showed that liver stiffness measurement (LSM), platelet (PLT) count, and prothrombin time (PT) were independent risk factors for liver fibrosis ( < 0.01), which were used to establish the nomogram. The consistency index (C-index) of the nomogram established for diagnosing liver fibrosis was 0.875. The calibration line and the ideal line were consistent, which indicated that diagnosis of liver fibrosis by the established model was accurate. The values of area under the receiver operator characteristic (ROC) curve (AUROC) for diagnosing liver fibrosis by the nomogram were 0.857 and 0.862 in the training dataset and validation dataset, respectively, which were noticeably higher than those in the well-known serological models, including the aspartate aminotransferase- (AST-) to-platelet ratio index (APRI) scoring model, fibrosis-4 (FIB-4) scoring model, APAG model (including age, PT, albumin, and -glutamyl transferase), and S-index model (all < 0.05).
Conclusion: LSM, PT, and PLT were found as independent risk factors for liver fibrosis. The established nomogram exhibited an excellent diagnostic performance, and it can more visually and individually evaluate the probability of liver fibrosis in patients with chronic HBV infection.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290880 | PMC |
| http://dx.doi.org/10.1155/2020/5218930 | DOI Listing |
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