The article by Thibault et al.Citation1 establishes the superiority of daclatasvir-sofosbuvir (DCV + SOF) over sofosbuvir-ribavirin (SOF + RBV) in the treatment of genotype 3 chronic hepatitis C infection (HCV) from a US payer perspective. However, a thorough review of the model assumptions and model parameters indicates that the relative cost-effectiveness of DCV + SOF may have been over-estimated.
First, the baseline population characteristics were derived from the US Centers for Disease Control and Prevention (CDC) Viral Hepatitis Statistics and surveillance data from 2011Citation2, despite data from 2014 being available at the time of the studyCitation3. Further, the baseline distribution of fibrosis and cirrhosis stages did not match with that in the referenced study by McGarry et al.Citation4. Second, for treatment-experienced patients with cirrhosis, a combination of SOF-velpatasvir or SOF–DCV plus RBV is recommendedCitation5. While the authors explicitly highlighted a lack of availability of data and a lack of head-to-head comparators as limitations, it should be noted that velpatasvir was approved in July 2016, and the findings from the ASTRAL-3 trial, a randomized, open label phase 3 trial that compared SOF-velpatasvir with SOF plus RBV, were published in late 2015Citation6. The authors could have provided a rationale for not including comparators in the study that are deemed relevant. Third, the assumption that patients who achieve sustained virological response (SVR) remain in that state until the end of the model time horizon or death does not reflect the true disease progression of HCV. The ALLY-3 trial reported that the post-treatment relapse rate was 8% in treatment-naïve patients and 13% in treatment-experienced patientsCitation7. This should have been taken into account, as it is not only a clinical, but also an economic concern that could potentially affect the study findings. Fourth, sensitivity analysis by varying the proportion of patients with non-structural protein 5A (NS5A) resistance-associated variants (RAVs) at baseline should have been conducted based on the data from the ALLY-3 trialCitation7. Several studies including ALLY-3 have shown that some of these RAVs (particularly Y93H) are associated with treatment failures and relapse, especially in patients with cirrhosisCitation6–8. Fifth, the transition probabilities for end stage liver disease and complications were derived from a study by Martin et al.Citation9, which was neither done in the US nor in genotype 3 patients. Transition probabilities from US studies have been reported in the literatureCitation10,Citation11, and it is not clear why the authors chose not to utilize these in the study. Moreover, the references given for some of the treatment-related monitoring and annual post-treatment monitoring costs were not listed in the references at the end of the article. Finally, incorporating adherence data for the treatments from the ALLY-3 trial would have improved the robustness of the study findings.
As mentioned above, if data for adherence, relapse, transition probabilities, relevant comparators, and additional population characteristics were considered, more precise cost-effectiveness of DCV-SOF could be obtained.
Transparency
Declaration of funding
This letter was not funded.
Declaration of financial/other relationships
Dr. Khalid Kamal received research funding from Novartis, Johnson & Johnson, College of Psychiatric and Neurologic Pharmacists, and Lynx Group (NJ). Dr. Kamal also receives an educational honorarium from the American Health System Pharmacy. Other authors have no financial/other relationships to disclose.
Acknowledgments
No assistance in the preparation of this letter is to be declared.
References
- Saint-Laurent Thibault C, Moorjaney D, Ganz ML, et al. Cost-effectiveness of combination daclatasvir-sofosbuvir for treatment of genotype 3 chronic hepatitis C infection in the United States. J Med Econ 2017:1-11. doi:10.1080/13696998.2017.1307204
- Centers for Disease Control and Prevention. U.S. 2011 surveillance data for viral hepatitis. Surveillance for viral hepatitis. Statistics and Surveillance; 2011. https://www.cdc.gov/hepatitis/statistics/2011surveillance/index.htm. [Last accessed May 12, 2017]
- Centers for Disease Control and Prevention. U.S. 2014 surveillance data for viral hepatitis. Surveillance for viral hepatitis. Statistics and Surveillance; 2014. https://www.cdc.gov/hepatitis/statistics/2014surveillance/index.htm. [Last accessed May 12, 2017]
- McGarry LJ, Pawar VS, Panchmatia HR, et al. Economic model of a birth cohort screening program for hepatitis C virus. Hepatology 2012;55:1344-55
- American Association for the Study of Liver Diseases (AASLD)/Infectious Diseases Society of America (IDSA). Retreatment of persons in whom prior therapy has failed. Recommendations for Testing, Managing, and Treating Hepatitis C. http://www.hcvguidelines.org/evaluate/monitoring. [Last accessed May 12, 2017]
- Foster GR, Afdhal N, Roberts SK, et al. Sofosbuvir and velpatasvir for HCV genotype 2 and 3 infection. N Engl J Med 2015;373:2608-17
- Nelson DR, Cooper JN, Lalezari JP, et al. All-oral 12-week treatment with daclatasvir plus sofosbuvir in patients with hepatitis C virus genotype 3 infection: ALLY-3 phase III study. Hepatology 2015;61:1127-35
- Dvory-Sobol H, Wyles D, Ouyang W, et al. Long-term persistence of HCV NS5A variants after treatment with NS5A inhibitor ledipasvir. J Hepatol 2015;62:S221
- Martin NK, Vickerman P, Miners A, et al. Cost-effectiveness of hepatitis C virus antiviral treatment for injection drug user populations. Hepatology 2012;55:49-57
- Rein DB, Wittenborn JS, Smith BD, et al. The cost-effectiveness, health benefits, and financial costs of new antiviral treatments for hepatitis C virus. Clin Infect Dis 2015;61:157-68
- Rein DB, Wittenborn JS, Weinbaum CM, et al. Forecasting the morbidity and mortality associated with prevalent cases of pre-cirrhotic chronic hepatitis C in the United States. Dig Liver Dis 2011;43:66-72