Author information

¹Infections and Immunoepidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States. Electronic address: obrient@mail.nih.gov.

²Kaiser Permanente San Rafael Medical Center, San Rafael, CA, United States. Electronic address: dwdw200@gmail.com.

³Kaiser Permanente South San Francisco Medical Center, South San Francisco, CA, United States; University of California San Francisco, San Francisco, CA, United States. Electronic address: Varun.Saxena@kp.org.

⁴Westat, Rockville, MD, United States. Electronic address: kerrygracemorrissey@westat.com.

⁵Information Management Services, Inc, Calverton, MD, United States. Electronic address: ChenS@imsweb.com.

⁶Infections and Immunoepidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States; Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States. Electronic address: frncnbaker@gmail.com.

⁷Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States. Electronic address: prokuninal@mail.nih.gov.

⁸Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States. Electronic address: pfeiffer@mail.nih.gov.

⁹Kaiser Permanente San Rafael Medical Center, San Rafael, CA, United States. Electronic address: jennifer.b.lai@kp.org.

Abstract

Background: Shorter duration therapy for hepatitis C virus (HCV) infection might reduce treatment costs and increase the number of patients treated and cured. We determined factors associated with treatment response after an 8-week sofosbuvir-based therapy and developed a simple model to predict an individual's likelihood of treatment success.

Methods: Among 2907 patients who received ledipasvir/sofosbuvir for 8 weeks, we determined failure rates by demographic and clinical characteristics, and IFNL4-?G/TT genotype. We estimated the average IFNL4 genotype-related treatment failure rate in major ancestry groups by applying our IFNL4 genotype results to genotype distributions from reference populations. We created a treatment response model based on three personal characteristics.

Results: Overall, 4.4% of the patients failed treatment. We observed significantly lower failure rates for persons <50 years (1.6%), females (2.6%), those carrying the IFNL4-TT/TT genotype (1.8%), those with HCV RNA <5.8 log₁₀ copies/mL (2.0%) or HCV genotype-1B infection (2.6%). In a model based on ancestry, age and sex, the predicted probability of treatment failure ranged from 0.5% among females of East Asian ancestry <50 years of age to 8.5% among males of African ancestry age ≥65 years.

Conclusion: Applying this algorithm at the point-of-care might facilitate HCV elimination, especially in low- and middle-income countries.