An IL28B genotype-based clinical prediction model for treatment of chronic hepatitis C

Abstract

Background: Genetic variation in IL28B and other factors are associated with sustained virological response (SVR) after pegylated-interferon/ribavirin treatment for chronic hepatitis C (CHC). Using data from the HALT-C Trial, we developed a model to predict a patient's probability of SVR based on IL28B genotype and clinical variables.

Methods: HALT-C enrolled patients with advanced CHC who had failed previous interferon-based treatment. Subjects were re-treated with pegylated-interferon/ribavirin during trial lead-in. We used step-wise logistic regression to calculate adjusted odds ratios (aOR) and create the predictive model. Leave-one-out cross-validation was used to predict a priori probabilities of SVR and determine area under the receiver operator characteristics curve (AUC).

Results: Among 646 HCV genotype 1-infected European American patients, 14.2% achieved SVR. IL28B rs12979860-CC genotype was the strongest predictor of SVR (aOR, 7.56; p<.0001); the model also included HCV RNA (log10 IU/ml), AST:ALT ratio, Ishak fibrosis score and prior ribavirin treatment. For this model AUC was 78.5%, compared to 73.0% for a model restricted to the four clinical predictors and 60.0% for a model restricted to IL28B genotype (p<0.001). Subjects with a predicted probability of SVR <10% had an observed SVR rate of 3.8%; subjects with a predicted probability >10% (43.3% of subjects) had an SVR rate of 27.9% and accounted for 84.8% of subjects actually achieving SVR. To verify that consideration of both IL28B genotype and clinical variables is required for treatment decisions, we calculated AUC values from published data for the IDEAL Study.

Conclusion: A clinical prediction model based on IL28B genotype and clinical variables can yield useful individualized predictions of the probability of treatment success that could increase SVR rates and decrease the frequency of futile treatment among patients with CHC.

Trial registration: ClinicalTrials.gov NCT00006164.

Conflict of interest statement

Competing Interests: The authors wish to report the following relationships that might appear to represent a potential conflict: John J. Sninsky is employed by Celera Corporation, Alameda. T. R. Morgan is on the speaker's bureau and receives research support from Hoffmann-La Roche, Inc.; is a consultant, serves on an advisory board, and receives research support from Vertex Pharmaceuticals; serves on an advisory board for Gilead Sciences; and receives research support from Merck, Schering Plough Corporation, and WAKO Diagnostics. A. S. Lok is a consultant for Hoffmann-La Roche, Inc., Abbott and Gilead; and receives research support from Schering-Plough Corporation, Bristol-Myers Squibb, Gilead and Eisai Pharmaceuticals. R. T. Chung receives research support from Hoffmann-La Roche, Inc.; receives research support from Schering-Plough, Novartis, and Romark; and is a consultant for Vertex Pharmaceuticals, Merck, Pfizer, Astellas, Novartis, and Gilead. M. L. Shiffman is a consultant for Celera Corporation, Hoffmann-La Roche, Inc., and National Genome Sciences; has attended advisor meetings with Anadys, Biolex, Bristol-Myers-Squibb, Conatus, Globeimmune, Human Genome Sciences, Novartis, Roche, Romark, Pfizer, Schering-Plough, Valeant, Vertex and Zymogenetics; is a speaker for Roche and Schering-Plough; is on the data safety monitoring boards with Abbott and Anadys; and has received research support from Biolex, Conatus, Glaxo SmithKline, Globeimmune, Human Genome Sciences, Idenix, Roche, Romark, Tibotec, Valeant, Vertex, Wyeth and Zymogenetics. J. J. Sninsky is an employee of Celera Corporation. H. L. Bonkovsky receives research support from Hoffmann-La Roche, Inc.; is a consultant for Boehringer-Ingelheim; is a consultant and on the advisory board for Clinuvel, Inc.; is a consultant, advisory board member and receives research support from Novartis Pharmaceuticals; is a consultant and on the speakers' bureau for Lundbeck Pharmaceuticals; and receives research support from Vertex Pharmaceuticals. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials. Authors with no financial relationships related to this project are: T. R. O'Brien, J. E. Everhart, Y. Shao, M. Dotrang, and R. M. Pfeiffer.

Figures

Figure 1. Distribution of IL28B rs12979860 genotypes, by response to treatment with pegylated-interferon-α2a plus ribavirin among European American subjects infected with HCV genotype 1, lead-in phase of the HALT-C Trial.

EVR, early virological response; BT, breakthrough; SVR, sustained virological response.

Figure 2. Area under the ‘receiver operating characteristic’ curve (AUC) for models predicting the probability of sustained virological response (SVR) - European American patients infected with HCV genotype 1, HALT-C Trial.

Full model: IL28B rs12979860 genotype plus four clinical variables. AUC was calculated using predicted probabilities of SVR based on a series of leave-one-out cross-validation logistic regression models.

Figure 3. Distributions of a priori predicted probability of sustained virological response (SVR) for 554 non-responders and 92 subjects who achieved SVR - European American patients infected with HCV genotype 1, HALT-C Trial.

Predicted probabilities are based on a series of leave-one-out cross-validation logistic regression models.

Figure 4. Observed and predicted probabilities of sustained virological response (SVR), by IL28B rs12979860 genotype, among European American patients infected with HCV genotype 1, HALT-C Trial.

‘Overall’ probabilities were directly observed. Probabilities for the selected clinical profiles were predicted from the model.