Pretreatment prediction of response to peginterferon plus ribavirin therapy in genotype 1 chronic hepatitis C using data mining analysis
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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.
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.
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.
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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- Pretreatment prediction of response to peginterferon plus ribavirin therapy in genotype 1 chronic hepatitis C using data mining analysis
Journal of Gastroenterology
Volume 46, Issue 3 , pp 401-409
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- Springer Japan
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- Data mining
- Decision tree
- Industry Sectors
- Author Affiliations
- 1. Division of Gastroenterology and Hepatology, Musashino Red Cross Hospital, 1-26-1 Kyonan-cho, Musashino, Tokyo, 180-8610, Japan
- 2. Department of Gastroenterology and Hepatology, Tokyo Medical and Dental University, Tokyo, Japan
- 3. Department of Computer and Information Science, Seikei University, Tokyo, Japan
- 4. First Department of Internal Medicine, University of Yamanashi, Yamanashi, Japan
- 5. Department of Hepatology, Toranomon Hospital, Tokyo, Japan
- 6. Department of Gastroenterology and Hepatology, Osaka University Graduate School of Medicine, Osaka, Japan
- 7. Department of Gastroenterology and Metabolism, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- 8. Clinical Research Center, National Nagasaki Medical Center, Nagasaki, Japan