Inflammation response and liver stiffness: predictive model of regression of hepatic stiffness after sustained virological response in cirrhotics patients with chronic hepatitis C
Cirrhotic 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 vira...
| Autores: | , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Brasil |
| Institución: | Universidade Estadual Paulista (UNESP) |
| Repositorio: | Repositório Institucional da UNESP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unesp.br:11449/207601 |
| Acceso en línea: | http://dx.doi.org/10.1007/s10238-021-00708-w http://hdl.handle.net/11449/207601 |
| Access Level: | acceso abierto |
| Palabra clave: | Elastography Hepatitis C Liver cirrhosis Stiffness regression |
| Sumario: | Cirrhotic 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. |
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