A Review of the Cost-Effectiveness Evidence for FDA-Approved Cell and Gene Therapies

Sumaya Abuloha,Shu Niu, Darlene Adirika, Benjamin P. Harvey,Mikael Svensson

HUMAN GENE THERAPY(2024)

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摘要
Cell and gene therapy (CGT) innovations have provided several significant breakthroughs in recent years. However, CGTs often come with a high upfront cost, raising questions about patient access, affordability, and long-term value. This study reviewed cost-effectiveness analysis (CEA) studies that have attempted to assess the long-term value of Food and Drug Administration (FDA)-approved CGTs. Two reviewers independently searched the Tufts Medical Center CEA Registry to identify all studies for FDA-approved CGTs, per January 2023. A data extraction template was used to summarize the evidence in terms of the incremental cost-effectiveness ratio expressed as the cost per quality-adjusted life year (QALY) and essential modeling assumptions, combined with a template to extract the adherence to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. The review identified 26 CEA studies for seven CGTs. Around half of the base-case cost-effectiveness results indicated that the cost per QALY was below $100,000-$150,000, often used as a threshold for reasonable cost-effectiveness in the United States. However, the results varied substantially across studies for the same treatment, ranging from being considered very cost-effective to far from cost-effective. Most models were based on data from single-arm trials with relatively short follow-ups, and different long-term extrapolations between studies caused large differences in the modeled cost-effectiveness results. In sum, this review showed that, despite the high upfront costs, many CGTs have cost-effectiveness evidence that can support long-term value. Nonetheless, substantial uncertainty regarding long-term value exists because so much of the modeling results are driven by uncertain extrapolations beyond the clinical trial data.
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关键词
cost-effectiveness analysis,cell and gene therapies,decision modeling,transparency
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