The main objective was to use discrete event simulation to model the impact of wait-time, defined as the time between leukapheresis and chimeric antigen receptor (CAR-T) infusion, when assessing the cost-effectiveness of tisagenlecleucel in young patients with relapsed/refractory acute lymphoblastic leukemia.
The movement of patients through the model was determined by parametric time-to-event distributions, with the competing risk of an event determining the costs and quality-adjusted life-years (QALYs) assigned. Cost-effectiveness was expressed using the incremental cost-effectiveness ratio (ICER) for tisagenlecleucel compared with chemotherapy over the lifetime.
The base case generated a total of 5.79 QALYs and $622 872 for tisagenlecleucel and 1.19 QALYs and $181 219 for blinatumomab, resulting in an ICER of $96 074 per QALY. An increase in mean CAR-T wait-time to 6.20 months reduced the benefit and costs of tisagenlecleucel to 2.78 QALYs and $294 478 because of fewer patients proceeding to infusion, reducing the ICER to $71 112 per QALY. Alternatively, when the cost of tisagenlecleucel was assigned pre-infusion in sensitivity analysis, the ICER increased with increasing wait-time.
Under a payment arrangement where CAR-T cost is incurred post-infusion, the loss of benefit to patients is not reflected in the ICER. This may be misguiding to decision makers, where cost-effectiveness ratios are used to guide resource allocation. discrete event simulation is an important tool for economic modeling of CAR-T as it is amenable to capturing the impact of wait-time, facilitating better understanding of factors affecting service delivery and consequently informed decision making to deliver faster access to CAR-T for patients.