OBJECTIVES:

Early assessment of cost-effectiveness of new products may support development and could also support reimbursement processes through early dialogues between stakeholders. The objective of this study is to assess the cost-effectiveness of acalabrutinib for chronic lymphocytic leukemia (CLL) based on published phase I/II data.

METHODS:

A partitioned survival model was constructed comparing acalabrutinib to ibrutinib for treatment of CLL until death or disease progression. Progression free survival (PFS) and overall survival (OS) were extrapolated from published data of ibrutinib and a hazard ratio was applied for acalabrutinib. The analysis was conducted over a lifetime horizon with monthly cycles from the United Kingdom (UK) healthcare payer perspective. The incremental cost-effectiveness ratio (ICER) was assessed with resource utilization inputs and discounting percentages according to guidelines of the National Institute for Health and Care Excellence (NICE). One-way sensitivity analysis was performed and 576 plausible scenarios were assessed in order to determine critical variables (defined by variations around the base case ICER larger than 15% throughout all scenarios) and likely ICER ranges.

RESULTS:

Results show that the model is most sensitive to eleven critical input parameters. The most relevant parameters were the OS for acalabrutinib and PFS and drug costs for both treatments. Utility differences between both treatments can also have a major impact (>50%) on the ICER. In 34% of scenarios, treatment with acalabrutinib would be cost-effective with a threshold of £ 30,000. The ICER increases with longer PFS but decreases with longer OS.

CONCLUSIONS:

Results are most sensitive to treatment costs and survival estimates, but are also greatly influenced by on-treatment utility differences between both treatments. Decision makers would benefit from more research into OS and on-treatment utility. This research shows that it is possible to establish a model and determine critical variables for cost-effectiveness in an early phase of development.