PBI75 REVIEW OF ECONOMIC EVALUATIONS FOR GENE THERAPIES:ARE WE READY FOR THE FUTURE?

Abstract

High prices asked upfront for novel one-off gene therapies accompanied by uncertain long-term value claims raise concerns around reimbursement and affordability for Health Technology Assessments (HTAs) and payers. Economic evaluations (EEs) are commonly used to inform these reimbursement decisions. This study aimed to examine economic evaluation studies of Gene Therapies (GTs) and to provide an overview of the quality of the economic evidence available for use in decision making. We conducted a systematic review of peer reviewed literature to identify published EEs in English between 2007 and 2019. Data extracted from EEs included model, input and outcomes characteristics. Quality was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. A narrative analysis was performed in which we discussed methodology, assumptions and quality of EEs, as well as use and implications in decision-making. The systematic review yielded seven EEs of gene therapies. All EEs were cost-utility analyses and scored satisfactory to good on the CHEERS checklist. Five EEs modeled ‘traditional’ upfront payment and two an outcome-based payment scheme. Four studies concluded GTs were not cost-effective. Three EEs further explored different assumptions around long-term survival, alternative payment schemes (annuity-based payment, pay for performance) and their effect on the incremental cost-effectiveness ratio using extensive subgroup analyses or scenario’s. EEs with scenario analyses were considered most informative for decision making, providing insights in the effect of assumptions and feasibility alternative approaches. Although the quality of an EE may be considered good, their informativeness for HTA and payers and policy makers can be limited. We therefore recommend including scenario analyses in gene therapy EEs, simulating different effectiveness assumptions, payment scheme’s or survival extrapolation methods. With the introduction of new therapies comes the need to explore use and appropriateness of our evidence generation tools, including EEs, to inform our decisions.