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A novel noninvasive algorithm for the assessment of liver fibrosis in patients with chronic hepatitis B virus infection
Author(s) -
Zhu M.Y.,
Zou X.,
Li Q.,
Yu D.M.,
Yang Z.T.,
Huang D.,
Chen J.,
Gong Q.M.,
Zhang D.H.,
Zhang Y.,
Chen L.,
Chen P.Z.,
Zhang X.X.
Publication year - 2017
Publication title -
journal of viral hepatitis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.329
H-Index - 100
eISSN - 1365-2893
pISSN - 1352-0504
DOI - 10.1111/jvh.12682
Subject(s) - medicine , hepatitis b virus , cohort , algorithm , receiver operating characteristic , biomarker , gastroenterology , liver biopsy , fibrosis , hepatitis b , prospective cohort study , red blood cell distribution width , biopsy , virus , immunology , biology , biochemistry , computer science
Summary 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.