RESUMO
BACKGROUND: Patients with relapsed or refractory diffuse large B-cell lymphoma (r/r DLBCL) have limited treatment options and poor prognoses. Tisagenlecleucel, a chimeric antigen receptor (CAR) T-cell therapy has shown early promise in improving survival outcomes, but at a high upfront cost. This study evaluated the cost-effectiveness of tisagenlecleucel versus salvage chemotherapy for treating patients with r/r DLBCL who have failed at least 2 lines of systemic therapies. METHODS: A hybrid decision tree and three-state partitioned survival model (progression-free (PF), progressive disease and death) was developed from the Singapore healthcare payer perspective. Survival curves from JULIET trial and CORAL-1 extension study were extrapolated beyond trial period over a 15-year time horizon to estimate the underlying progression-free survival and overall survival parametric distributions for both arms. Health state utilities were retrieved from the literature, and direct costs were sourced from public healthcare institutions in Singapore. One-way probabilistic sensitivity analyses and scenario analyses were conducted to explore the impact of uncertainties and assumptions on cost-effectiveness results. RESULTS: Compared with salvage chemotherapy, tisagenlecleucel was associated with a base-case incremental cost-effectiveness ratio (ICER) US$508,530 (S$686,516) per quality adjusted life year (QALY) gained and US$320,200 (S$432,269) per life year (LY) gained. One-way sensitivity analysis showed the ICER was most sensitive to time horizon, PF utility and cost of tisagenlecleucel. Scenario analyses confirmed that the ICERs remained high under favorable assumptions and substantial price reduction was required to reduce the ICER. CONCLUSIONS: Our analysis showed tisagenlecleucel use in r/r DLBCL patients who failed at least 2 prior lines of systemic therapies was associated with exceedingly high ICER, which is unlikely to represent good use of healthcare resources. Comparative clinical evidence from the ongoing trials might provide more insight into future evaluations.