Factors predictive of sustained virological response following 72 weeks of combination therapy for genotype 1b hepatitis C
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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.
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.
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%.
Complementary statistical and data mining approaches were used to identify a subgroup of patients likely to benefit from 72 weeks of therapy.
KeywordsCART analysis Core protein Decision tree ISDR LDL cholesterol
Hepatitis C virus
Interferon sensitivity determining region
Classification and regression tree analysis
Sustained virological response
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.
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