A Markov-based mathematical model estimates that transplanting hepatitis C virus (HCV)-positive livers into HCV-negative patients who have received direct-acting antiviral (DAA) agents would be cost effective and improve outcomes, researchers report in the March issue of Clinical Gastroenterology and Hepatology.
There has been a steady increase in the number of patients with end-stage liver disease in need of transplants, but no increase in the number of livers available. HCV-infected donor organs might be an underutilized resource. Due to the efficacy of DAA agents in curing HCV infection, the number of patients in need of transplants as a result of HCV-related liver disease is expected to decrease, with an increase in the number of HCV-uninfected patients on the waitlist.
Guidelines do not recommend use of HCV-positive donor livers for transplantation into HCV-negative recipients. This is because of the risk of HCV transmission and its complications, including graft failure. HCV-positive donor livers have therefore been reserved for HCV-infected waitlist patients. However, if allograft HCV infection can be cured successfully with DAA therapy, it might be time to revisit HCV-positive organ allocation policies.
The cost of DAA therapy poses a barrier. Emily D. Bethea et al conducted a model-based analysis to estimate the cost effectiveness of providing DAA therapy to HCV-negative patients on the liver waitlist and then HCV-infected donor livers.
To estimate disease progression and MELD score fluctuations, they used a previous study based on UNOS data to estimate weekly changes in MELD score.
They found that for patients with a model for end-stage liver disease (MELD) score of 22 or higher (see figure), accepting any liver vs waiting for only HCV-negative livers was cost effective, with incremental cost-effectiveness ratios ranging from $56,100 to $91,700/quality-adjusted life-year (QALY). For perspective, at the median MELD score at time of transplantation in the United States (MELD score 28), accepting any liver was deemed cost effective, with an ICER of $62,600 per additional QALY.
For patients with poor quality of life, for whom low MELD scores might not accurately indicate disease severity, accepting any liver was clinically beneficial (QALYs were higher, irrespective of MELD score). The ICER of accepting any liver for these patients ranged from $57,000 to $66,000, below the willingness-to-pay threshold of 100,000/QALY.
Results for each individual UNOS region, accounting for differences in HCV-positive donor organ rates as well as regional variations in transplant wait times and waitlist mortalities, showed that at MELD scores of 22 or 24 and higher, accepting any liver was a cost-effective strategy in all regions .
For patients with a MELD score of 28, the model parameters that most affected the cost effectiveness of accepting any liver were the cost of liver transplantation and post-transplant care. For patients with a MELD score of 22, the cost of liver transplantation and post-transplant care, DAA price, and the QoL on the waiting list could affect cost effectiveness.
Bethea et al conclude that DAAs have provided us the opportunity to consider previously discarded HCV-positive livers for use and expand the static liver donor pool. Although there are benefits to accepting HCV-positive organs, concerns surrounding the additional risks, including cost associated with preemptive DAA therapy, could impede clinical implementation.
Their model shows that for the median MELD score at time of transplantation, it is not only clinically beneficial but also cost effective for HCV-negative waitlist patients to accept HCV-positive donor livers. As the MELD score increases, it becomes increasingly cost effective to use this strategy, provided the efficacy of DAAs in transplanted livers.
Findings from this analysis can be used to inform policy and support coverage of DAA costs for this form of treatment. Although this strategy will result in an increase in initial spending, it is an investment that can improve long-term health outcomes.