A novel noninvasive algorithm for the assessment of liver fibrosis in patients with chronic hepatitis B virus infection |
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| Authors: | Q. Li D.‐M. Yu Z.‐T. Yang D. Huang J. Chen Q.‐M. Gong D.‐H. Zhang Y. Zhang L. Chen P.‐Z. Chen X.‐X. Zhang |
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| Affiliation: | 1. Department of Hepatitis, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China;2. Department of Infectious Diseases, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China;3. P?le Sino‐Fran?ais de Recherches en Science du Vivant et Génomique, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China;4. Ministry of Education Key Laboratory of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China;5. Collaborative Innovation Center of Systems Biomedicine, Shanghai, China;6. Translational Medicine Research Center, Ruijin Hospital North, School of Medicine, Shanghai Jiao Tong University, Shanghai, China |
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| Abstract: | Several noninvasive blood biomarkers have been established for the assessment of liver fibrosis in patients with chronic hepatitis B virus (HBV) infection, but their clinical performance remains inconclusive. Here, we compared the diagnostic performance of these biomarkers and developed a novel algorithm for assessing liver fibrosis. Six hundred and sixteen chronically HBV‐infected and treatment‐naïve patients who underwent liver biopsy were enrolled and randomly divided into training (N=410) and internal validation cohorts (N=206). One hundred and fifty‐nine patients from another centre were recruited as an external validation cohort. Receiver operating characteristic (ROC) curves were used to analyse the performance of the gamma‐glutamyltransferase‐to‐platelet ratio (GPR), red cell volume distribution width‐to‐platelet ratio (RPR), FIB‐4 index, aspartate aminotransferase‐to‐platelet ratio index (APRI) and HBV DNA level against liver histology, and a novel algorithm was developed using the recursive partitioning and regression tree (RPART) method. In the training cohort, the area under the ROC curve of FIB‐4 was significantly higher than that of APRI (P=.038) but was comparable to those of GPR, RPR and HBV DNA; however, the performance of the biomarkers was similar among the validation cohort. The established RPR‐HBV DNA algorithm performed better in the training cohort than any individual blood biomarker, and the corresponding sensitivity, specificity, positive predictive value and negative predictive value were 63%, 90%, 72% and 80%, respectively. In the internal and external validation cohorts, the performance of the algorithm in assessing liver fibrosis was also superior to that of other biomarkers. These results suggest that the established RPR‐HBV DNA algorithm might improve the diagnostic accuracy of liver fibrosis in treatment‐naïve patients with chronic HBV infection, although additional studies are warranted to confirm these findings. |
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| Keywords: | blood biomarkers chronic hepatitis B virus infection diagnosis liver fibrosis |
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