We need to shift our treatment strategy to one that treats patients at the optimal time, thereby maximizing the treatment’s effectiveness and controlling costs for payers.
Hepatitis C is caused by the Hepatitis C virus (HCV), which infects the liver causing problems that range in severity from patient to patient. Many patients remain asymptomatic and unaware of the disease, while other patients develop more serious symptoms including cirrhosis, liver disease or death. Currently, Hepatitis C impacts roughly 2.7 million Americans [Klevens, et al., 2002; Denniston, et al., 2014; Dinah et al., 2014] and related liver complications represent a substantial public health burden.
Until 2014, the treatment for Hepatitis C was invasive, ineffective and often avoided by patients. Standard therapy required 24 to 48 weeks of injections that often resulted in severe side effects such as: fatigue, flu-like symptoms and depression. [P McHutchinson, et al., 1998; Fried, et al., 2002; Manns, et al., 2001]. Because of the unpleasant nature of the treatment, few patients initiated treatment and of those that did, adherence rates proved low. An HCV infection is considered cured if a patient experiences a sustained viral response (SVR) (i.e., the virus remains undetectable for a sustained period). However, in a recent study using data from the VA, Schaeffer Center researcher Jeff McCombs and his colleagues found that “only 24.3% of VA patients received treatment at any time following diagnosis, [and] only 16.4% of treated patients achieved an undetectable viral load post-treatment.” [McCombs, et al., 2015]. In the VA system, the reluctance to seek treatment and the limited effectiveness of the older therapies resulted in a significant pool of Hepatitis C patients who experienced progression in their disease state.
New Specialty Drugs Call into Question Treatment Strategies
In 2014, the FDA approved a new set of oral treatments for Hepatitis C that greatly reduce the undesirable side effects and increase the rate of SVR achieved in clinical trials. Unfortunately, the high cost of these drugs and the significant pool of patients with advanced disease has created an “affordability challenge and a ‘value for money’ dilemma.” [Fox, McCombs, 2016]. Fox and McCombs state “treating every HCV positive patient in the U.S. would cost on the order of $200 billion [compared to] total annual U.S spending on all prescription drugs of around $300 billion.” [Fox, McCombs, 2016]. At the end of the day, it is too expensive to immediately treat all patients with the new treatments, and increased demand for treatment has forced drug payers and providers to limit treatment to those with the greatest need. While this is an appropriate rationing strategy from an ethical perspective, late treatment is less effective in reducing the patients’ risk of future adverse events.
In a second study using VA data, Schaeffer Center researcher Jeff McCombs and his coauthors examined the effects of delaying treatment with the older medications until a patient exhibits one or more abnormal test results that are predictive of future liver complications. The researchers found that starting treatment prior to any abnormal results significantly reduces the risk of future liver complications, which is consistent with prior research. They also determined that delaying standard treatment until after a patient exhibited one or more abnormal test results “significantly degrades the effectiveness of treatment” [Tonnu-Mihara, et al., 2015] This finding calls into question the current HCV treatment strategy rationing the new drugs to those patients who already have some complications. If delaying treatment greatly reduces its effectiveness, we are now tasked with finding an optimal treatment strategy that defers treatment for those patients that need it least without reducing the treatment’s effectiveness at some future treatment date. That is, if health care systems must pursue a strategy of ‘watchful waiting’, what do we watch and how long do we wait?
An Optimal Strategy to Treatment
Schaeffer Center researchers Dr. Steven Fox and Jeff McCombs address this question in a 2016 article that searches for an optimal treatment strategy based on the characteristics of Hepatitis C and the new treatment. The authors argue that it does not make sense to immediately treat all individuals infected with HCV, since many will not show any symptoms or face liver complications for many years. But for those whom it does make sense to treat, “achieving SVR significantly reduces the risk of serious and costly HCV related events and deaths, especially for patients that have already demonstrated early disease progression, [but this] treatment and initial viral response can come too late“[Fox, McCombs, 2016]. The authors’ conclusions were based on a third VA study that identifies a simple index, FIB4, which can be used to monitor patient progression and is determined by common blood tests rather than more invasive methods, such as liver biopsy [Matsuda, et al., 2016]. Using this index, McCombs and Fox propose that an optimal treatment strategy can be developed that prioritizes treatment for patients with evidence of significant disease progression measured by an appropriate FIB4 value, starting with the sickest patients and lowering requirements over a number of years until all patients with disease progression have been treated. Once these high risk individuals have been treated, all known and newly diagnosed HCV cases should be monitored and treated once a minimum FIB4 value has been exceeded. The proposed strategy does not specify an appropriate FIB4 level to initiate treatment, but does provide guidance on how to manage the affordability and timing challenge created by the costly new Hepatitis C drugs.
The new Hepatitis C treatments provide mixed incentives for patients and their insurers. Patient demand for treatment has increased due to the reduced side effects and increased effectiveness of the new medications while payer’s face a ‘cash-flow’ crisis if all patients are treated immediately. These conflicting interests mean that we need an optimal strategy to treat patients to reduce costs and maximize treatment benefits. Schaeffer Center researchers Dr. Steven Fox and Jeff McCombs summarize, “put most succinctly, the approach is this: treat everyone who needs treatment, as soon as they need treatment, but not before they need it.” [Fox, McCombs, 2016]. While this may seem like an oversimplification, we still have a long way to go in implementing an optimal strategy that maximizes the value of these highly effective, but also high cost treatments. Fortunately, several additional medications in this class of drugs have entered the market, significantly reducing the prices paid by the VA and other managed health care systems. These reductions in price will shorten the time needed for the health care system to rationally treat all Hepatitis C patients, reducing patient’s risk of progression toward liver damage. In the meantime, we need to shift our treatment strategy to one that treats patients at the optimal time, thereby maximizing the treatment’s effectiveness and controlling costs for payers.
McCombs JS, Matsuda T, Mihara I, Saab S, Hines P, L’Italien G, Juday T, Yuan Y. THE RISK OF LONG-TERM MORBIDITY AND MORTALITY IN CHRONIC HEPATITIS C PATIENTS: Results from an Analysis of Data from the Veterans Administration HCV Clinical Registry. JAMA Inter Med. Doi:10.1001/jamainternmed.2013.12505. Nov. 5 2014.
Tonnu-Mihara I, Matsuda T, McCombs JS, Saab S, Hines P, L’Italien G, Juday T, Yuan Y. Five Laboratory Tests Predict Patient Risk and Treatment Response in Hepatitis C: Veterans Affairs Data from 1999-2010. 2015 Universal Journal of Medical Science 4:10-20. doi: 10.13189/ujmsj.2016.040102
Matsuda, T, McCombs JS, Tonnu-Mihara I, McGinnis JJ and Fox DS. The impact of delayed hepatitis C viral load suppression on patient risk: Historical Evidence from the Veterans Administration. Health Economics and Policy, forthcoming.
Fox DS and McCombs JS. Optimizing HCV Treatment – Moving Beyond the Cost Conundrum. Invited editorial. J Hepatology. doi:10.1016/j.jhep.2016.02.010