Finding the Right Comparison

Recently, I had the opportunity to work with two strong pharmacoeconomics researchers (Daniel Mullins and Julia Slejko) to develop a cost-effectiveness analysis (CEA) for chronic hepatitis C virus (HCV) treatment (Link to publication).  In CEA, researchers attempt to aid decision-making by directly comparing the costs and health outcomes of different treatment options for a specific disease.  This allows us to examine the scenario of a new medication versus an older (often cheaper and possibly less effective) standard of care.  In the case of HCV, several new medications have entered the market since 2013 essentially transforming the landscape of treatment and guidelines for care.(1)  As we point out in our paper, many models have been developed in the past few years for HCV with a wide range of methods and no consistency with regards to the selection of treatment comparators.  In this blog post, I wanted to explore 2 possible issues with treatment selection in a CEA study.

New Drug vs. No Treatment

First thing to consider is whether or not the decision to “not treat” is a viable option.  From a clinician or patient perspective, this may not always be reasonable when an effective treatment does exist and the clinical benefits definitely outweigh the risk of side effects.  When we compare a new treatment to no treatment, it is all about the downstream costs avoided against the upfront investment in treatment today.  Several economic models have shown that treating HCV now appears to be cost-effective over the life of the patient who would be less likely to experience progression to cirrhosis.(2–5)

New Drug vs. VERY Old Drug

With HCV, several drugs in the class of direct acting antivirals now exist that are all significantly more effective than the regimens available before 2013.  When the patient and provider evaluate options to begin HCV therapy, using an interferon-based regimen may no longer enter the conversation.  So when we decide to build an economic model, does it make sense to include these old options in the analysis?  We felt it was important to focus on all 1st line treatments, but there may be some rationale to also include 2nd line options – if the 2nd line options are cheap enough and effective enough for some patients it might not be bad to see at what point they would be viable options.  We began in the two genotypes (1 & 4) where the most 1st line options exist, but as more pan-genotypic agents enter the market it would make sense to update this model for all genotypes.

Future Directions

We hope this paper helps advance the conversation for cost-effectiveness decisions in HCV, but we know much more work needs to be done.  Are we able to extend this to incorporate more patient preferences?  Are we able to build a model that is more flexible for a wide variety of patients and account for the heterogeneity we see in practice?  Are we able to develop better estimates for the true cost of the drug product, net all of the rebates and discounts observed by most payers?

One thing I’ve discovered in my relatively short academic career: Every answer I find usually spawns more questions.


  1. Recommendations for testing, managing, and treating hepatitis C. AASLD/ISDA: HCV Guidance: Recommendations for testing, managing, and treating hepatitis C. 2016. Available from:
  2. Chidi AP, Rogal S, Bryce CL, Fine MJ, Good CB, Myaskovsky L, et al. Cost-effectiveness of new antiviral regimens for treatment-naïve U.S. veterans with hepatitis C. Hepatology. 2016;428–36.
  3. Chidi AP, Bryce CL, Donohue JM, Fine MJ, Landsittel DP, Myaskovsky L, et al. Economic and Public Health Impacts of Policies Restricting Access to Hepatitis C Treatment for Medicaid Patients. Value Heal. 2016;19:326–34.
  4. Najafzadeh M, Andersson K, Shrank WH, Krumme AA, Matlin OS, Brennan T, et al. Cost-effectiveness of novel regimens for the treatment of hepatitis C virus. Ann Intern Med. 2015;162(6):407–19.
  5. Chhatwal J, Kanwal F, Roberts MS, Dunn MA. Cost-effectiveness and budget impact of hepatitis C virus treatment with sofosbuvir and ledipasvir in the United States. Ann Intern Med. 2015;162(6).
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Joey Mattingly, PharmD, MBA is an assistant professor at the University of Maryland School of Pharmacy located in Baltimore, Maryland. Joey has managed retail and long-term care pharmacy operations in Kentucky, Illinois and Indiana. Leading Over The Counter is a blog of Joey's views and opinions on the topics of pharmacy leadership and management and do not represent the University of Maryland, Baltimore. Joey can be followed on Twitter @joeymattingly.

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