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©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved.
Proton nuclear magnetic resonance-based metabonomic models for non-invasive diagnosis of liver fibrosis in chronic hepatitis C: Optimizing the classification of intermediate fibrosis
Andrea Dória Batista, Carlos Jonnatan Pimentel Barros, Tássia Brena Barroso Carneiro Costa, Michele Maria Gonçalves de Godoy, Ronaldo Dionísio Silva, Joelma Carvalho Santos, Mariana Montenegro de Melo Lira, Norma Thomé Jucá, Edmundo Pessoa de Almeida Lopes, Ricardo Oliveira Silva
Andrea Dória Batista, Joelma Carvalho Santos, Edmundo Pessoa de Almeida Lopes, Postgraduate Program in Tropical Medicine, Center for Health Sciences, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901, Brazil
Andrea Dória Batista, Edmundo Pessoa de Almeida Lopes, Department of Gastroenterology and Hepatology, Hospital das Clínicas, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901, Brazil
Carlos Jonnatan Pimentel Barros, Tássia Brena Barroso Carneiro Costa, Ronaldo Dionísio Silva, Ricardo Oliveira Silva, Department of Fundamental Chemistry, Center for Exact and Nature Sciences, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901, Brazil
Michele Maria Gonçalves de Godoy, Intensive Care Unit, Hospital das Clínicas, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901, Brazil
Mariana Montenegro de Melo Lira, Norma Thomé Jucá, Department of Pathology, Hospital das Clínicas, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901, Brazil
Author contributions: Batista AD, Barros CJP, Lopes EPA and Silva RO contributed to the concept; Batista AD, Godoy MMG and Santos JC contributed to the patient selection and clinical procedures; Barros CJP, Silva RD and Costa TBBC contributed to the optimization of the spectral parameters, obtaining the NMR spectra and construction of the metabonomics models; Jucá NT and de Melo Lira MM contributed to the histopathological analysis; Batista AD, Barros CJP, Costa TBBC, Silva RO, Santos JC, Godoy MMG, Lopes EPA, Silva RO, Jucá NT and de Melo Lira MM contributed to the analysis and discussion of the results; Batista AD, Barros CJP and Costa TBBC contributed to writing of article; Batista AD, Costa TBBC, Santos JC, Godoy MMG, Lopes EPA and Silva RO contributed to revision of article.
Institutional review board statement: This study was approved by the Ethics Committee on Research Involving Human Subjects of the Health Sciences Center - Universidade Federal de Pernambuco (CCS-UFPE), Recife, Brazil (Approval no. 93.127/2012).
Informed consent statement: All study participants provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All authors have no conflict of interest to declare.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Andrea Dória Batista, PhD, Postgraduate Program in Tropical Medicine, Center for Health Sciences, Universidade Federal de Pernambuco, Avenida Professor Moraes Rego 135, Recife, Pernambuco 50670-901, Brazil.
adoria04@globo.com
Telephone: +55-81-21268527
Received: September 22, 2017
Peer-review started: September 23, 2017
First decision: October 30, 2017
Revised: November 16, 2017
Accepted: January 15, 2018
Article in press: January 15, 2018
Published online: January 27, 2018
Processing time: 126 Days and 5.9 Hours
AIM
To develop metabonomic models (MMs), using 1H nuclear magnetic resonance (NMR) spectra of serum, to predict significant liver fibrosis (SF: Metavir ≥ F2), advanced liver fibrosis (AF: METAVIR ≥ F3) and cirrhosis (C: METAVIR = F4 or clinical cirrhosis) in chronic hepatitis C (CHC) patients. Additionally, to compare the accuracy of the MMs with the aspartate aminotransferase to platelet ratio index (APRI) and fibrosis index based on four factors (FIB-4).
METHODS
Sixty-nine patients who had undergone biopsy in the previous 12 mo or had clinical cirrhosis were included. The presence of any other liver disease was a criterion for exclusion. The MMs, constructed using partial least squares discriminant analysis and linear discriminant analysis formalisms, were tested by cross-validation, considering SF, AF and C.
RESULTS
Results showed that forty-two patients (61%) presented SF, 28 (40%) AF and 18 (26%) C. The MMs showed sensitivity and specificity of 97.6% and 92.6% to predict SF; 96.4% and 95.1% to predict AF; and 100% and 98.0% to predict C. Besides that, the MMs correctly classified all 27 (39.7%) and 25 (38.8%) patients with intermediate values of APRI and FIB-4, respectively.
CONCLUSION
The metabonomic strategy performed excellently in predicting significant and advanced liver fibrosis in CHC patients, including those in the gray zone of APRI and FIB-4, which may contribute to reducing the need for these patients to undergo liver biopsy.
Core tip: The assessment of liver fibrosis in chronic hepatitis C patients is important to make therapeutic decisions and predict clinical outcomes. Due to various drawbacks related to the use of liver biopsy, individual markers and scores have been validated with feeble accuracy to assess intermediate stages of fibrosis. Our study showed promising results for the metabonomics strategy as a non-invasive tool to distinguish patients with significant fibrosis, advanced fibrosis, and cirrhosis, with sensitivity and specificity values above 95% and high accuracy in the gray zone of aspartate aminotransferase to platelet ratio index and fibrosis index based on four factors, which could avoid a large number of biopsies in these patients.
