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Pretreatment prediction of response to peginterferon plus ribavirin therapy in genotype 1 chronic hepatitis C using data mining analysis

  • Original Article—Liver, Pancreas, and Biliary Tract
  • Published:
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Abstract

Background

This study aimed to develop a model for the pre-treatment prediction of sustained virological response (SVR) to peg-interferon plus ribavirin therapy in chronic hepatitis C.

Methods

Data from 800 genotype 1b chronic hepatitis C patients with high viral load (>100,000 IU/ml) treated by peg-interferon plus ribavirin at 6 hospitals in Japan were randomly assigned to a model building (n = 506) or an internal validation (n = 294). Data from 524 patients treated at 29 hospitals in Japan were used for an external validation. Factors predictive of SVR were explored using data mining analysis.

Results

Age (<50 years), alpha-fetoprotein (AFP) (<8 ng/mL), platelet count (≥120 × 109/l), gamma-glutamyltransferase (GGT) (<40 IU/l), and male gender were used to build the decision tree model, which divided patients into 7 subgroups with variable rates of SVR ranging from 22 to 77%. The reproducibility of the model was confirmed by the internal and external validation (r 2 = 0.92 and 0.93, respectively). When reconstructed into 3 groups, the rate of SVR was 75% for the high probability group, 44% for the intermediate probability group and 23% for the low probability group. Poor adherence to drugs lowered the rate of SVR in the low probability group, but not in the high probability group.

Conclusions

A decision tree model that includes age, gender, AFP, platelet counts, and GGT is useful for predicting the probability of response to therapy with peg-interferon plus ribavirin and has the potential to support clinical decisions regarding the selection of patients for therapy.

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Acknowledgments

This study was supported by a grant-in-aid from the Ministry of Health, Labor and Welfare, Japan.

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Authors and Affiliations

  1. Division of Gastroenterology and Hepatology, Musashino Red Cross Hospital, 1-26-1 Kyonan-cho, Musashino, Tokyo, 180-8610, Japan

    Masayuki Kurosaki & Namiki Izumi

  2. Department of Gastroenterology and Hepatology, Tokyo Medical and Dental University, Tokyo, Japan

    Naoya Sakamoto

  3. Department of Computer and Information Science, Seikei University, Tokyo, Japan

    Manabu Iwasaki

  4. First Department of Internal Medicine, University of Yamanashi, Yamanashi, Japan

    Minoru Sakamoto

  5. Department of Hepatology, Toranomon Hospital, Tokyo, Japan

    Yoshiyuki Suzuki

  6. Department of Gastroenterology and Hepatology, Osaka University Graduate School of Medicine, Osaka, Japan

    Naoki Hiramatsu

  7. Department of Gastroenterology and Metabolism, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan

    Fuminaka Sugauchi

  8. Clinical Research Center, National Nagasaki Medical Center, Nagasaki, Japan

    Hiroshi Yatsuhashi

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  1. Masayuki Kurosaki
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Correspondence to Namiki Izumi.

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Kurosaki, M., Sakamoto, N., Iwasaki, M. et al. Pretreatment prediction of response to peginterferon plus ribavirin therapy in genotype 1 chronic hepatitis C using data mining analysis. J Gastroenterol 46, 401–409 (2011). https://doi.org/10.1007/s00535-010-0322-5

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  • DOI: https://doi.org/10.1007/s00535-010-0322-5

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