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Case selection for interferon treatment of hepatitis C
Author(s) -
Zeniya Mikio,
Toda Gotaro
Publication year - 2000
Publication title -
journal of gastroenterology and hepatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.214
H-Index - 130
eISSN - 1440-1746
pISSN - 0815-9319
DOI - 10.1046/j.1440-1746.2000.02111.x
Subject(s) - medicine , selection (genetic algorithm) , hepatitis c , regimen , viral load , interferon , genotype , logistic regression , antiviral treatment , immunology , gastroenterology , chronic hepatitis , virology , human immunodeficiency virus (hiv) , virus , machine learning , gene , biology , biochemistry , computer science
To establish a case selection algorithm for the treatment of hepatitis C, predictive factors were studied and reported articles were reviewed and analysed. Because of the relatively poor efficacy of interferon (IFN) monotherapy, which is ineffective in 60–70% of patients, case selection at present is determined by the likelihood of attaining a sustained response (SR; defined by normalizing serum ALT and eliminating serum HCV RNA after treatment) to therapy. According to the present study, viral load and genotype, and IL‐10 and IL‐1ra serum levels, are the most predictive of achieving SR after IFN monotherapy given in a comparatively high dose regimen for 6 months. In addition, reported studies with logistic analyses were carefully reviewed and analysed for the most effective predictive factors of case selection. The results again indicated that viral load and HCV‐genotype (serotype) were closely related to SR. Age, gender, and histological changes at treatment were also considered for case selection. These results, however, relate solely to IFN‐monotherapy. Future development of more effective strategies for treating hepatitis C could alter the exclusion criteria for IFN treatment and will negate the need for the case selection algorithm discussed here.