How Does Treating Chronic Hepatitis C Affect Individuals in Need of Organ Transplants in the United Kingdom?

OBJECTIVES: To estimate the impact of cures for chronic hepatitis C (CHC) infection on organ donation in the United Kingdom. Curing CHC infection reduces the need for liver transplants and enables cured individuals to donate organs of all types. METHODS: We adapted a double-queuing model of organ allocation to estimate the effects of CHC infection cures on liver, lung, heart, and kidney transplants in the United Kingdom. We assumed that cured individuals would donate organs at similar rates as the general population and no longer require liver transplants because of CHC infection. We estimated how curing CHC infection influences waitlist lengths for each organ and the annual net present value to society on the basis of quality-adjusted life-years gained through additional transplants under opt-in and opt-out organ donation policies. RESULTS: Curing CHC generates the most value for patients on the liver waitlist, because it increases the number of transplantable livers and reduces the need for transplants. Under the current opt-in policy, liver waitlist length falls by 24%, generating £34.3 million of annual net present value. Growth in the number of uninfected lungs, hearts, and kidneys generates an additional £19.2 million annually, with £18.7 million from kidneys. Implementing the opt-out policy, liver waitlist length would decrease by 75%, implying that treating CHC eliminates one-third of the excess liver waitlist due to an opt-in policy. CONCLUSIONS: Treating CHC has large positive spillovers to uninfected individuals by reducing the need for liver transplants and allowing cured individuals to donate organs. These spillovers have not been included in traditional value assessments of CHC treatment.

Value of Comprehensive HCV Treatment among Vulnerable, High-Risk Populations.

OBJECTIVES: The objective of this study was to explore the trade-offs society and payers make when expanding treatment access to patients with chronic hepatitis C virus (HCV) infection in early stages of disease as well as to vulnerable, high-risk populations, such as people who inject drugs (PWID) and HIV-infected men who have sex with men (MSM-HIV). METHODS: A discrete time Markov model simulated HCV progression and treatment over 20 years. Population cohorts were defined by behaviors that influence the risk of HCV exposure: PWID, MSM-HIV, an overlap cohort of individuals who are both PWID and MSM-HIV, and all other adults. Six different treatment scenarios were modeled, with varying degrees of access to treatment at different fibrosis stages and to different risk cohorts. Benefits were measured as quality-adjusted life-years and a $150,000/quality-adjusted life-year valuation was used to assess social benefits. RESULTS: Compared with limiting treatment to METAVIR fibrosis stages F3 or F4 and excluding PWID, expanding treatment to patients in all fibrosis stages and including PWID reduces cumulative new infections by 55% over a 20-year horizon and reduces the prevalence of HCV by 93%. We find that treating all HCV-infected individuals is cost saving and net social benefits are over $500 billion greater compared with limiting treatment. Including PWID in treatment access saves 12,900 to 41,200 lives. CONCLUSIONS: Increased access to treatment brings substantial value to society and over the long-term reduces costs for payers, as the benefits accrued from long-term reduction in prevalent and incident cases, mortality, and medical costs outweigh the cost of treatment.

Generalized cost-effectiveness analysis to assess treatment value in hepatitis C.

OBJECTIVES: To estimate the comprehensive value of direct-acting antivirals (DAAs) for the treatment of hepatitis C virus (HCV) compared with peginterferon alfa and ribavirin (PEG/riba) employing a generalized cost-effectiveness analysis (GCEA). STUDY DESIGN: To assess the societal-level cost-effectiveness of DAA treatment for HCV, we extended a previously published discrete-time Markov simulation model of HCV transmission and progression to include market dynamics and broader elements of value. METHODS: We followed a stepwise process to add novel value elements to a traditional CEA model for HCV treatments. For each additional element of value, we estimated incremental cost-effectiveness ratios (ICERs) of DAAs compared with PEG/riba. RESULTS: The health technology assessment (HTA)-style model yielded an ICER value of $64,512 per quality-adjusted life-year (QALY). Adding transmission dynamics resulted in an ICER value of $52,971 per QALY, whereas accounting for transmission dynamics and dynamic price and efficacy further decreased ICER values by 90% to $6406 per QALY. Incorporating genericization, productivity loss, caregiver spillover, and differential valuations of LYs vs quality of life, disease severity, and insurance value further decreased the ICER value to $4487 per QALY, a 93% reduction from the baseline HTA-style CEA to the fully realized GCEA. CONCLUSIONS: Our GCEA study results confirm that DAAs are a cost-effective treatment for HCV compared with PEG/riba even when using conventional cost-effectiveness approaches. Incorporating broader elements of value resulted in more than a 10-fold improvement in cost-effectiveness, emphasizing the substantive impact of a generalized approach and the importance of incorporating GCEAs into decision-making.

Quantifying spillover benefits in value assessment: a case study of increased graft survival on the US kidney transplant waitlist.

AIM: To quantify the wider impacts of increased graft survival on the size of the kidney transplant waitlist and health and economic outcomes. MATERIALS AND METHODS: The analysis employed known steady-state solutions to a double-queueing system as well as simulations of this system. Baseline input parameters were sourced from the Organ Procurement and Transplant Network and the United States Renal Data System. Three increased graft survival scenarios were modeled: decreases in repeat transplant candidates joining the waitlist of 25%, 50%, and 100%. RESULTS: Under the three scenarios, we estimated that the US waitlist size would decrease from 91,822 to 85,461 (6.9% decrease), 80,073 (12.8% decrease), and 69,340 (24.4% decrease), respectively. Patient outcomes improved, with lifetime quality-adjusted life years (QALYs) for a 1-year cohort of transplant recipients increasing by 10,010, 16,888, and 43,345 over the three scenarios. Discounted lifetime costs for the cohort in the new steady state were lower by $1.6 billion, $2.3 billion, and $9.0 billion for each scenario, respectively. Spillover impacts (i.e. benefits that accrued beyond the patients who directly experienced increased graft survival) accounted for 41-48% of the QALY gains and ranged from cost increases of 3.3% to decreases of 5.5%. LIMITATIONS: The model is a simplification of reality and does not account for the full degree of patient heterogeneity occurring in the real world. Health economic outcomes are extrapolated based on the assumption that the median patient is representative of the overall population. CONCLUSIONS: Increasing graft survival reduces demand from repeat transplants candidates, allowing additional candidates to receive transplants. These spillover impacts decrease waitlist size and shorten wait times, leading to improvements in graft and patient survival as well as quality-of-life. Cost-effectiveness analyses of treatments that increase kidney graft survival should incorporate spillover benefits that accrue beyond the direct recipient of an intervention.

Incremental net monetary benefit of ocrelizumab relative to subcutaneous interferon ß-1a.

AIM: Disease-modifying therapies (DMTs) impact the natural history of relapsing forms of multiple sclerosis (RRMS) by reducing annual relapse rates and slowing disability progression. The effect of DMTs on indirect costs has not been consistently explored in cost-effectiveness studies thus far. The value to patients of an emerging DMT, ocrelizumab, was quantified in comparison to subcutaneous interferon beta-1a (IFNßSC) for the prevalent RRMS population with mild-to-moderate disability in the US, based on two Phase 3 trials, OPERA I and OPERA II, of ocrelizumab vs IFNßSC in RRMS. MATERIALS AND METHODS: A Markov model was developed to compare disability progression as measured by Expanded Disability Status Scale (EDSS) and relapse outcomes over a 30-year horizon for ocrelizumab vs IFNßSC. Direct, indirect, and informal costs (2016 US dollars) and utilities for EDSS health states were obtained from the literature. Hazard ratios for disability progression and relapse rates were estimated from clinical trials. Value was assessed by calculating the net monetary benefit (NMB), defined as the monetary value of discounted quality-adjusted life years (QALYs) minus total costs, where the value of a QALY was $150,000. One-way sensitivity analyses were conducted. RESULTS: Ocrelizumab was associated with an incremental gain of 0.84 QALYs and cost savings of $287,713 relative to IFNßSC, resulting in an incremental NMB (INMB) of $413,611 per person over 30 years. The INMB increased by $151,763 for those initiating ocrelizumab at EDSS level 1 vs level 4. Influential parameters were QALY value, treatment costs, and disability progression; however, all sensitivity analyses indicated that the INMB for ocrelizumab relative to IFNßSC was ≥$300,000 per person. CONCLUSIONS: Ocrelizumab provides greater value to RRMS patients compared with IFNßSC. Initiating ocrelizumab at lower EDSS levels leads to a greater cumulative value due to slower disability progression, which extends years with higher quality-of-life.