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Journal of Gastroenterology

, Volume 46, Issue 4, pp 545–555 | Cite as

Factors predictive of sustained virological response following 72 weeks of combination therapy for genotype 1b hepatitis C

  • Kazuaki ChayamaEmail author
  • C. Nelson Hayes
  • Kentaro Yoshioka
  • Hisataka Moriwaki
  • Takashi Okanoue
  • Shotaro Sakisaka
  • Tetsuo Takehara
  • Makoto Oketani
  • Joji Toyota
  • Namiki Izumi
  • Yoichi Hiasa
  • Akihiro Matsumoto
  • Hideyuki Nomura
  • Masataka Seike
  • Yoshiyuki Ueno
  • Hiroshi Yotsuyanagi
  • Hiromitsu Kumada
Original Article—Liver, Pancreas, and Biliary Tract

Abstract

Background

Treatment of genotype 1b chronic hepatitis C virus (HCV) infection has been improved by extending peg-interferon plus ribavirin combination therapy to 72 weeks, but predictive factors are needed to identify those patients who are likely to respond to long-term therapy.

Methods

We analyzed amino acid (aa) substitutions in the core protein and the interferon sensitivity determining region (ISDR) of nonstructural protein (NS) 5A in 840 genotype 1b chronic hepatitis C patients with high viral load. We used logistic regression and classification and regression tree (CART) analysis to identify predictive factors for sustained virological response (SVR) for patients undergoing 72 weeks of treatment.

Results

When patients were separately analyzed by treatment duration using multivariate logistic regression, several factors, including sex, age, viral load, and core aa70 and ISDR substitutions (P = 0.0003, P = 0.02, P = 0.01, P = 0.0001, and P = 0.0004, respectively) were significant predictive factors for SVR with 48 weeks of treatment, whereas age, previous interferon treatment history, and ISDR substitutions (P = 0.03, P = 0.01, and P = 0.02, respectively) were the only significant predictive factors with 72 weeks of treatment. Using CART analysis, a decision tree was generated that identified age, cholesterol, sex, treatment length, and aa70 and ISDR substitutions as the most important predictive factors. The CART model had a sensitivity of 69.2% and specificity of 60%, with a positive predictive value of 68.4%.

Conclusions

Complementary statistical and data mining approaches were used to identify a subgroup of patients likely to benefit from 72 weeks of therapy.

Keywords

CART analysis Core protein Decision tree ISDR LDL cholesterol 

Abbreviations

HCV

Hepatitis C virus

ISDR

Interferon sensitivity determining region

CART

Classification and regression tree analysis

SVR

Sustained virological response

NR

Non-viral response

Notes

Acknowledgments

This work was supported in part by Grants-in-Aid for scientific research and development from the Ministry of Health, Labor and Welfare and Ministry of Education, Culture, Sports, Science and Technology, Government of Japan. We thank Sakura Akamatsu and Mika Tsuzuno for their assistance.

Conflict of interest

None of the authors have conflicts of interest to declare.

Supplementary material

535_2010_358_MOESM1_ESM.ppt (124 kb)
Figure S1. Selection of patients. 840 patients were selected out of 1,425 patients who were treated with PEG-IFN plus ribavirin combination therapy. Patients were divided into two groups based on the duration of treatment, 48 weeks (619) and 72 weeks (221) (PPT 27 kb)
535_2010_358_MOESM2_ESM.ppt (195 kb)
Figure S2. Receiver operating characteristic curve for CART analysis and multivariate logistic regression. The area under the curve is 0.677 for the CART analysis and 0.696 for the logistic regression analysis (PPT 249 kb)

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Copyright information

© Springer 2011

Authors and Affiliations

  • Kazuaki Chayama
    • 1
    Email author
  • C. Nelson Hayes
    • 1
  • Kentaro Yoshioka
    • 2
  • Hisataka Moriwaki
    • 3
  • Takashi Okanoue
    • 4
  • Shotaro Sakisaka
    • 5
  • Tetsuo Takehara
    • 6
  • Makoto Oketani
    • 7
  • Joji Toyota
    • 8
  • Namiki Izumi
    • 9
  • Yoichi Hiasa
    • 10
  • Akihiro Matsumoto
    • 11
  • Hideyuki Nomura
    • 12
  • Masataka Seike
    • 13
  • Yoshiyuki Ueno
    • 14
  • Hiroshi Yotsuyanagi
    • 15
  • Hiromitsu Kumada
    • 16
  1. 1.Department of Medical and Molecular Science, Division of Frontier Medical Science, Programs for Biomedical Research, Graduate School of Biomedical SciencesHiroshima UniversityHiroshimaJapan
  2. 2.Division of Liver, Biliary Tract and Pancreas Diseases, Department of Internal MedicineFujita Health UniversityNagoyaJapan
  3. 3.Department of GastroenterologyGifu University Graduate School of MedicineGifuJapan
  4. 4.Department of Gastroenterology and HepatologySaiseikai Suita HospitalSuitaJapan
  5. 5.Department of Gastroenterology and MedicineFukuoka University School of MedicineFukuokaJapan
  6. 6.Department of Gastroenterology and HepatologyOsaka University Graduate School of MedicineOsakaJapan
  7. 7.Department of Digestive and Life-Style Related Disease, Health Research Course, Human and Environmental SciencesKagoshima University Graduate School of Medical and Dental SciencesKagoshimaJapan
  8. 8.Department of GastroenterologySapporo Kosei General HospitalSapporoJapan
  9. 9.Division of Gastroenterology and HepatologyMusashino Red Cross HospitalMusashinoJapan
  10. 10.Department of Gastroenterology and MetabologyEhime University Graduate School of MedicineMatsuyamaJapan
  11. 11.Department of MedicineShinshu University School of MedicineMatsumotoJapan
  12. 12.The Center for Liver DiseasesShin-Kokura HospitalKokuraJapan
  13. 13.Department of Internal Medicine 1, Faculty of MedicineOita UniversityOitaJapan
  14. 14.Division of GastroenterologyTohoku University Graduate School of MedicineSendaiJapan
  15. 15.Department of Internal Medicine, Graduate School of MedicineUniversity of TokyoTokyoJapan
  16. 16.Department of HepatologyToranomon HospitalTokyoJapan

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