Prediction of effect of pegylated interferon alpha-2b plus ribavirin combination therapy in patients with chronic hepatitis C infection

Tetsuro Takayama, Hirotoshi Ebinuma, Shinichiro Tada, Yoshiyuki Yamagishi, Kanji Wakabayashi, Keisuke Ojiro, Takanori Kanai, Hidetsugu Saito, Toshifumi Hibi

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Treatment with pegylated interferon alpha-2b (PEGIFN) plus ribavirin (RBV) is standard therapy for patients with chronic hepatitis C. Although the effectiveness, patients with high titres of group Ib hepatitis C virus (HCV) respond poorly compared to other genotypes. At present, we cannot predict the effect in an individual. Previous studies have used traditional statistical analysis by assuming a linear relationship between clinical features, but most phenomena in the clinical situation are not linearly related. The aim of this study is to predict the effect of PEG IFN plus RBV therapy on an individual patient level using an artificial neural network system (ANN). 156 patients with HCV group 1b from multiple centres were treated with PEGIFN (1.5 μg/kg) plus RBV (400-1000 mg) for 48 weeks. Data on the patients' demographics, laboratory tests, PEGIFN, and RBV doses, early viral responses (EVR), and sustained viral responses were collected. Clinical data were randomly divided into training data set and validation data set and analyzed using multiple logistic regression analysis (MLRs) and ANN to predict individual outcomes. The sensitivities of predictive expression were 0.45 for the MLRs models and 0.82 for the ANNs and specificities were 0.55 for the MLR and 0.88 for the ANN. Non-linear relation analysis showed that EVR, serum creatinine, initial dose of Ribavirin, gender and age were important predictive factors, suggesting non-linearly related to outcome. In conclusion, ANN was more accurate than MLRs in predicting the outcome of PEGIFN plus RBV therapy in patients with group 1b HCV.

Original languageEnglish
Article numbere27223
JournalPLoS One
Volume6
Issue number12
DOIs
Publication statusPublished - 2011 Dec 2

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chronic hepatitis C
interferon-alpha
Ribavirin
Chronic Hepatitis C
therapeutics
neural networks
Hepatitis C virus
prediction
Infection
Viruses
Hepacivirus
infection
Neural networks
Therapeutics
dosage
Regression analysis
creatinine
Polyethylene glycols
peginterferon alfa-2b
Logistics

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

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Prediction of effect of pegylated interferon alpha-2b plus ribavirin combination therapy in patients with chronic hepatitis C infection. / Takayama, Tetsuro; Ebinuma, Hirotoshi; Tada, Shinichiro; Yamagishi, Yoshiyuki; Wakabayashi, Kanji; Ojiro, Keisuke; Kanai, Takanori; Saito, Hidetsugu; Hibi, Toshifumi.

In: PLoS One, Vol. 6, No. 12, e27223, 02.12.2011.

Research output: Contribution to journalArticle

Takayama, Tetsuro ; Ebinuma, Hirotoshi ; Tada, Shinichiro ; Yamagishi, Yoshiyuki ; Wakabayashi, Kanji ; Ojiro, Keisuke ; Kanai, Takanori ; Saito, Hidetsugu ; Hibi, Toshifumi. / Prediction of effect of pegylated interferon alpha-2b plus ribavirin combination therapy in patients with chronic hepatitis C infection. In: PLoS One. 2011 ; Vol. 6, No. 12.
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