OBJECTIVES: The static cost-calculator approach for BIA is often used by budget-holders to evaluate the financial impact of new treatments. However, for many cases in oncology, this traditional approach potentially under-values innovative products that significantly delay disease progression to a costlier disease state. Using nmCRPC as an illustrative example, we propose a dynamic BIA model that follows patients and associated costs as they enter the eligible population and as they progress to advanced disease or death.

METHODS: A 5-year horizon model was developed using a US payer perspective. A prevalent cohort enters the first-year population, and an incidence cohort is added each subsequent year. Patients are tracked for the remainder of the time horizon with 1 of the following health states: nmCRPC, metastatic CRPC, and death. Published overall survival and metastasis-free survival (MFS) rates were used to estimate the numbers of patients in each state under the current standard of care (SoC). Drug and disease management costs were also derived from published literature. Monthly drug costs were assumed at $10,000 for a novel treatment and $200 for the SoC. Assuming 100% uptake for the novel product, the budget impact using a traditional approach was compared with this dynamic approach using 3 scenarios with hazard ratios (HR) for MFS of 0.5, 0.4, and 0.3.

RESULTS: Compared with the traditional approach, the dynamic approach estimated lower budget impacts for all MFS HR scenarios. Furthermore, greater reductions were observed with improvements in the HR for MFS. Namely, with an HR of 0.5, 0.4, and 0.3, the budget impacts were significantly reduced by 35%, 36%, and 37%, respectively, after Year 1, and by 73%, 76%, and 79%, respectively, by the end of Year 5.

CONCLUSIONS: The dynamic approach more accurately estimates the budgetary impact of novel oncology treatments and demonstrates the value of innovation.