Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros

Bases de dados
Ano de publicação
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
Mol Clin Oncol ; 15(4): 215, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34476099

RESUMO

Advanced liver fibrosis is the most important risk factor for hepatocellular carcinoma (HCC) development after achieving sustained virological response (SVR) by direct-acting antiviral (DAA) treatment in patients with chronic hepatitis C. Wisteria floribunda agglutinin-positive Mac-2-binding protein (M2BPGi), enhanced liver fibrosis (ELF) score, type IV collagen and fibrosis-4 (FIB-4) index have been reported as non-invasive biomarkers for liver fibrosis. In the present study, the possibility of using fibrosis biomarkers and other parameters to predict the development of HCC was evaluated. A total of 743 patients infected with hepatitis C virus who achieved SVR by using DAA were retrospectively enrolled. Of these, 122 patients whose blood samples were stored were selected. The aforementioned four fibrosis biomarkers were analyzed at baseline, at the end of treatment (EOT) and at post-treatment week 24 (PTW24). Tumor markers and laboratory tests were also analyzed. The baseline/EOT/PTW24 values for each fibrosis biomarker were as follows: ELF score: 11.5±1.2/10.8±1.1/10.4±1.0; type IV collagen: 213±85/190±67/174±55 ng/ml; M2BPGi: 4.8±3.5/2.7±2.0/2.2±1.8; and FIB-4 index: 5.31±3.82/4.36± 2.79/4.24±3.09. Of the 122 patients, 23 developed HCC. A high baseline ELF score (P=0.0264), PTW24 ELF score (P=0.0003), PTW24 α-fetoprotein level (P=0.0133), baseline FIB-4 index (P=0.0451) and low baseline prothrombin time (P=0.0455) were risk factors for HCC development based on univariate analyses. Based on the multivariate analysis, a high PTW24 ELF score was the only risk factor for HCC development (P=0.0035). The ELF score after DAA therapy was strongly associated with HCC development; therefore, it may be a useful marker for predicting HCC.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA