Economic Evidence on Potentially Curative Gene Therapy Products: A Systematic Literature Review

Objective The aim of this review was to summarize all available evidence on the cost effectiveness of potentially curative gene therapies and identify challenges that economic evaluations face in this area. Methods We conducted a systematic review of four databases (PubMed/MEDLINE, Embase, CINAHL, EconLit) and grey literature sources. We conducted the search on August 23, 2019 and updated it on November 26, 2020. We included all English, French and Spanish language studies that addressed a gene therapy that had received regulatory approval or had entered a phase III trial, and also reported on costs related to the therapy. Critical appraisal was conducted to assess quality of reporting in included studies. Results Fifty-six studies were identified. Of the 42 full economic evaluations, 71% (n = 30) evaluated chimeric antigen receptor T-cell therapies, most used either a Markov model (n = 17, 40%) and/or a partitioned survival model (n = 17, 40%), and 76% (n = 32) adopted a public or private payer perspective. The model characteristics with the greatest impact on cost effectiveness included assumptions about the efficacy of the treatment and the comparators used. Conclusion All gene therapies in this review were shown to be more effective than their comparators, although due to high costs not all were considered cost effective at standard cost-effectiveness thresholds. Despite their high cost, some gene therapies have the potential to dominate the alternatives in conditions with high mortality/disability. The choice of comparator and assumptions regarding long-term effectiveness had substantial impacts on cost-effectiveness estimates and need to be carefully considered. Both the quality of inputs and the quality of reporting were highly variable.

Automated summary

This review summarized evidence on the cost effectiveness of potentially curative gene therapies, with most studies evaluating chimeric antigen receptor T-cell therapies using Markov or partitioned survival models. While gene therapies were more effective than comparators, their high costs meant that not all were considered cost effective. Choice of comparator and assumptions about long-term effectiveness had significant impacts on cost-effectiveness estimates.