Pre-treatment prediction of response to pegylated-interferon plus ribavirin for chronic hepatitis C using genetic polymorphism in IL28B and viral factors.
OBJECTIVE
Pegylated interferon and ribavirin (PEG-IFN/RBV) therapy for chronic hepatitis C virus (HCV) genotype 1 infection is effective in 50% of patients. Recent studies revealed an association between the IL28B genotype and treatment response. We aimed to develop a model for the pre-treatment prediction of response using host and viral factors.


METHODS
Data were collected from 496 patients with HCV genotype 1 treated with PEG-IFN/RBV at five hospitals and universities in Japan. IL28B genotype and mutations in the core and IFN sensitivity determining region (ISDR) of HCV were analyzed to predict response to therapy. The decision model was generated by data mining analysis.


RESULTS
The IL28B polymorphism correlated with early virological response and predicted null virological response (NVR) (odds ratio=20.83, p<0.0001) and sustained virological response (SVR) (odds ratio=7.41, p<0.0001) independent of other covariates. Mutations in the ISDR predicted relapse and SVR independent of IL28B. The decision model revealed that patients with the minor IL28B allele and low platelet counts had the highest NVR (84%) and lowest SVR (7%), whereas those with the major IL28B allele and mutations in the ISDR or high platelet counts had the lowest NVR (0-17%) and highest SVR (61-90%). The model had high reproducibility and predicted SVR with 78% specificity and 70% sensitivity.


CONCLUSIONS
The IL28B polymorphism and mutations in the ISDR of HCV were significant pre-treatment predictors of response to PEG-IFN/RBV. The decision model, including these host and viral factors may support selection of optimum treatment strategy for individual patients.
Division of Gastroenterology and Hepatology, Musashino Red Cross Hospital, Musashino-shi, Tokyo, Japan.
Masayuki
M
Kurosaki
Yasuhito
Y
Tanaka
Nao
N
Nishida
Naoya
N
Sakamoto
Nobuyuki
N
Enomoto
Masao
M
Honda
Masaya
M
Sugiyama
Kentaro
K
Matsuura
Fuminaka
F
Sugauchi
Yasuhiro
Y
Asahina
Mina
M
Nakagawa
Mamoru
M
Watanabe
Minoru
M
Sakamoto
Shinya
S
Maekawa
Akito
A
Sakai
Shuichi
S
Kaneko
Kiyoaki
K
Ito
Naohiko
N
Masaki
Katsushi
K
Tokunaga
Namiki
N
Izumi
Masashi
M
Mizokami
D000368:Aged; D000483:Alleles; D000998:Antiviral Agents / Q000627:therapeutic use; D057225:Data Mining; D003663:Decision Trees; D024882:Drug Resistance, Viral / Q000235:genetics; D005260:Female; D005814:Genes, Viral; D005838:Genotype; D016174:Hepacivirus / Q000187:drug effects / Q000235:genetics*; D019698:Hepatitis C, Chronic / Q000188:drug therapy* / Q000235:genetics* / Q000276:immunology / Q000821:virology; D006801:Humans; D007370:Interferon Type I / Q000627:therapeutic use*; D007372:Interferons; D007378:Interleukins / Q000235:genetics*; D007564:Japan; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009154:Mutation; D020641:Polymorphism, Single Nucleotide; D011379:Prognosis; D012367:RNA, Viral / Q000097:blood / Q000235:genetics; D011994:Recombinant Proteins; D012189:Retrospective Studies; D012254:Ribavirin / Q000627:therapeutic use*; D016896:Treatment Outcome; D014758:Viral Core Proteins / Q000235:genetics; D019562:Viral Load; D000095022:Interferon Lambda
D000998:Antiviral Agents; D007370:Interferon Type I; D007372:Interferons; D007378:Interleukins; D012367:RNA, Viral; D011994:Recombinant Proteins; D012254:Ribavirin; D014758:Viral Core Proteins; C000624353:interferon-lambda, human; D000095022:Interferon Lambda