Cost-Effectiveness and Value of Perfect Information Analyses for Bruton's Tyrosine Kinase Inhibitors for Patients with Relapsed or Refractory Mantle Cell Lymphoma in the United States
Year: 2020
Type: dissertation
Abstract: Objectives: This study aimed to (1) evaluate the cost-effectiveness of second-generation Bruton’s tyrosine kinase (BTK) inhibitors, including acalabrutinib and zanubrutinib, compared with the first-generation BTK inhibitor (ibrutinib) in treating patients with relapsed or refractory mantle cell lymphoma (R/R MCL) using existing evidence from phase I/II clinical trials for second-generation BTK inhibitors; (2) assess the value of additional information analyses to identify the gap and uncertainty of the current evidence and to prioritize future studies to resolve uncertainty; (3) compare the expected value of additional evidence with expected opportunity costs for performing additional studies. Methods and Materials: A Markov model with two health states (progression-free [PF] and progression or death) was established, comparing acalabrutinib or zanubrutinib with ibrutinib from the United States (US) payer perspective. To simulate health outcomes for each treatment regimen, transition probabilities between the two health states were derived from parametric distributions fitted to Kaplan–Meier (KM) curves based on PF survival (PFS) curves from the phase III clinical trial reported by Dreyling et al. (Lancet 2016) for ibrutinib, the phase II clinical trial reported by Wang et al. (Lancet 2018) for acalabrutinib, and the phase I/II clinical trial reported by Tam et al. (Blood 2019) for zanubrutinib. The analysis was conducted over a lifetime horizon, and health utility outcomes and costs were discounted at 3.5% per year. The PFS life years (LYs) and PFS quality-adjusted LYs (QALYs) for each treatment, the incremental PFS LYs and PFS QALYs gained with acalabrutinib or zanubrutinib over ibrutinib, and the incremental cost-effectiveness ratio (ICER) and cost-utility ratio (ICUR) were estimated in both base and probabilistic sensitivity analyses (PSA; 100,000 simulations). The expected value of perfect information (EVPI) was calculated from the net monetary benefit (NMB) and net health benefit (NHB) that are forgone, by comparing the overall optimal treatment resulting from the PSA ICURs with the optimal strategy in each of 100,000 PSA simulations. Results: Treatment with acalabrutinib resulted in incremental PFS LYs and PFS QALYs of (3.40, 2.66) while zanubrutinib was associated with incremental PFS LYs and PFS QALYs of (2.21, 1.71) when compared with ibrutinib. The incremental costs per PFS QALY gained when comparing acalabrutinib and zanubrutinib with ibrutinib were $41,744 and $37,813, respectively. For a willingness to pay (WTP) value of $100,000, the probabilities of acalabrutinib, zanubrutinib, and ibrutinib being cost-effective are 50%, 34%, and 16%, respectively. Using the available evidence regarding clinical efficacy, costs, and utility outcomes as inputs for the model, an uncertainty cost of $92,473 (NHB=0.93 QALYs is forgone) per patient was obtained, which implies a need for additional research. The uncertainty costs of effectiveness for acalabrutinib, zanubrutinib, and ibrutinib were $66,709, $53,916, and $984, respectively, while the health-related quality of life (HRQoL) (disutility values) of adverse events was associated with an uncertainty cost of $85,949. Conclusions: The results demonstrate that acalabrutinib is more cost-effective compared with ibrutinib and zanubrutinib and greatly improves health outcomes in R/R MCL patients. However, decisions based on this analysis, which used phase I/II trials, are associated with a high level of uncertainty in terms of health benefits that may be forgone for some populations if acalabrutinib is adopted by health insurance companies. Future studies that compare the efficacy and HRQoL of these agents are recommended.
Author: Neda Al Rawashdh
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3085290259