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Inflammation response and liver stiffness: predictive model of regression of hepatic stiffness after sustained virological response in cirrhotics patients with chronic hepatitis C

dc.contributor.authorBraz, Aline Márcia Marques [UNESP]
dc.contributor.authorWinckler, Fernanda Cristina [UNESP]
dc.contributor.authorBinelli, Larissa Sarri [UNESP]
dc.contributor.authorChimeno, Luis Guilherme [UNESP]
dc.contributor.authorLopes, Lia Beatriz Mantovani [UNESP]
dc.contributor.authorLima, Rodrigo Santos [UNESP]
dc.contributor.authorSimões, Rafael Plana [UNESP]
dc.contributor.authorGrotto, Rejane Maria Tommasini [UNESP]
dc.contributor.authorGolim, Marjorie de Assis [UNESP]
dc.contributor.authorSilva, Giovanni Faria [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2021-06-25T10:57:55Z
dc.date.available2021-06-25T10:57:55Z
dc.date.issued2021-01-01
dc.description.abstractCirrhotic patients with chronic hepatitis C should be monitored for the evaluation of liver function and screening of hepatocellular carcinoma even after sustained virological response (SVR). The stage of inflammatory resolution and regression of fibrosis is likely to happen, once treatment and viral clearance are achieved. However, liver examinations by elastography show that 30–40% of patients do not exhibit a reduction of liver stiffness. This work was a cohort study in cirrhotic patients whose purpose was to identify immunological factors involved in the regression of liver stiffness in chronic hepatitis C and characterize possible serum biomarkers with prognostic value. The sample universe consisted of 31 cirrhotic patients who underwent leukocyte immunophenotyping, quantification of cytokines/chemokines and metalloproteinase inhibitors in the pretreatment (M1) and in the evaluation of SVR (M2). After exclusion criteria application, 16 patients included were once more evaluated in M3 (like M1) and classified into regressors (R) or non-regressors (NR), decrease or not ≥ 25% stiffness, respectively. The results from ROC curve, machine learning (ML) and linear discriminant analysis showed that TCD4 + lymphocytes (absolute) are the most important biomarkers for the prediction of the regression (AUC = 0.90). NR patients presented levels less than R of liver stiffness since baseline, whereas NK cells were increased in NR. Therefore, it was concluded that there is a difference in the profile of circulating immune cells in R and NR, thus allowing the development of a predictive model of regression of liver stiffness after SVR. These findings should be validated in greater numbers of patients.en
dc.description.affiliationGraduate Program in Pathophysiology in Clinical Medicine Department of Clinical Medicine São Paulo State University (UNESP) Botucatu Medical School
dc.description.affiliationFlow Cytometry Laboratory Applied Biotechnology Laboratory - LBA Clinical Hospital of Botucatu Medical School, Av. Prof. Mário Rubens Guimarães Montenegro, s/n
dc.description.affiliationGraduate Program in Research and Development (Medical Biotechnology São Paulo State University (UNESP) Botucatu Medical School
dc.description.affiliationGraduate Program in Pathology Department of Pathology São Paulo State University (UNESP) Botucatu Medical School
dc.description.affiliationDepartment of Biotechnology and Bioprocess Engineering São Paulo State University (UNESP) Faculty of Agronomic Sciences
dc.description.affiliationMolecular Biology Laboratory Applied Biotechnology Laboratory - LBA Clinical Hospital of Botucatu Medical School
dc.description.affiliationUnespGraduate Program in Pathophysiology in Clinical Medicine Department of Clinical Medicine São Paulo State University (UNESP) Botucatu Medical School
dc.description.affiliationUnespFlow Cytometry Laboratory Applied Biotechnology Laboratory - LBA Clinical Hospital of Botucatu Medical School, Av. Prof. Mário Rubens Guimarães Montenegro, s/n
dc.description.affiliationUnespGraduate Program in Research and Development (Medical Biotechnology São Paulo State University (UNESP) Botucatu Medical School
dc.description.affiliationUnespGraduate Program in Pathology Department of Pathology São Paulo State University (UNESP) Botucatu Medical School
dc.description.affiliationUnespDepartment of Biotechnology and Bioprocess Engineering São Paulo State University (UNESP) Faculty of Agronomic Sciences
dc.description.affiliationUnespMolecular Biology Laboratory Applied Biotechnology Laboratory - LBA Clinical Hospital of Botucatu Medical School
dc.identifierhttp://dx.doi.org/10.1007/s10238-021-00708-w
dc.identifier.citationClinical and Experimental Medicine.
dc.identifier.doi10.1007/s10238-021-00708-w
dc.identifier.issn1591-9528
dc.identifier.issn1591-8890
dc.identifier.scopus2-s2.0-85104141923
dc.identifier.urihttp://hdl.handle.net/11449/207601
dc.language.isoeng
dc.relation.ispartofClinical and Experimental Medicine
dc.sourceScopus
dc.subjectElastography
dc.subjectHepatitis C
dc.subjectLiver cirrhosis
dc.subjectStiffness regression
dc.titleInflammation response and liver stiffness: predictive model of regression of hepatic stiffness after sustained virological response in cirrhotics patients with chronic hepatitis Cen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.orcid0000-0002-4824-9441[9]
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Medicina, Botucatupt
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências, Botucatupt
unesp.departmentPatologia - FMBpt
unesp.departmentFisiologia - IBBpt

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