OBJECTIVES : This study aims to: 1) estimate the minimum magnitude of improvement on patient outcomes needed and maximum reimbursable prices that will make CAR-T cell therapy cost-effective for adult patients with relapsed/refractory acute lymphoblastic leukemia (ALL) and; 2) identify parameters that future research on CAR-T therapy should focus on.

METHODS We developed a probabilistic Markov model to predict the long-term health outcomes and costs of adult patients with relapsed/refractory ALL who receive each of the available treatment modalities including CAR-T therapy, blinatumomab, inotuzumab, bone marrow transplant, and salvage chemotherapy. We simulate the inclusion of CAR-T into each treatment modality using a wide range of potential treatment effects to determine what clinical effects and what size of effect would be necessary for CAR-T to be cost-effective. Sources of data necessary to populate this model include a combination of published systematic reviews and routinely-collected databases.

RESULTS Bone marrow transplant was associated with the largest improvement in life expectancy among adult patients with ALL, followed by CAR T-cell therapy, blinatumomab, inotuzumab, and salvage chemotherapy. Maximum reimbursable price of CAR T-cell therapy depends on willingness to pay (WTP) values, treatment comparator, the sequence of treatments. If CAR T-cells are used to treat first relapse of ALL, at a WTP of $50,000 per QALY gained, the maximum reimbursable price of CAR T-cell therapy were $19,431, $125,686 and $132,130 when compared to salvage chemotherapy, blinatumomab and inotuzumab, respectively. However, if CAR T-cells are used as a subsequent relapse treatment, its maximum reimbursable prices decreased substantially. CAR T-cell therapy has no therapeutic headroom compared to bone marrow transplant.

CONCLUSIONS Maximum reimbursable price of CAR T-cell therapy depends on willingness to pay values, treatment comparator, and sequence of treatments. Early economic evaluation can determine which factors of treatment can impact the cost-effectiveness of new interventions.