The impact of amortization of gene therapies funding on the results and conclusions of CEMs and BIMs.

BACKGROUND: Gene replacement therapy (GRT) is a treatment method used to combat or prevent various diseases. Its high one-off cost constitutes a major obstacle for successful market access. This paper aims to assess and discuss the applicability of amortization in models, such as cost-effectiveness models (CEMs) and budget impact models (BIMs) informing HTA recommendations and reimbursement decisions. METHODS AND FINDINGS: A hypothetical CEA and BIA were considered. The objective was to compare the GRT with and without amortization. A straight-line amortization model was used. The CEM and BIM were considered and assessed based on two set of scenarios: considering different amortization duration or different discounting rate. The impact of amortization against the total cost of gene therapy was assessed for all the scenarios. The cost difference between GRT with and without amortization in relation to its total cost was -$58,855, thus amortization does not have a significant impact on the results and conclusions of the cost-effectiveness analysis. For BIM in the base case, amortization had no impact on the results. CONCLUSION: Amortization has negligible impact on the results of CEM and total BIM and no impact on the conclusions from the model. One exception is the budget impact in case of an amortization period longer than the time horizon of BIM, where a half of the GRT price is moved beyond the model time horizon. Amortization has a distinguishing effect from an accounting perspective, but it does not have any implication for payers.

Gene Therapy Evidence Generation and Economic Analysis: Pragmatic Considerations to Facilitate Fit-for-Purpose Health Technology Assessment.

Gene therapies (GTs) are considered to be a paradigm-shifting class of treatments with the potential to treat previously incurable diseases or those with significant unmet treatment needs. However, considerable challenges remain in their health technology assessment (HTA), mainly stemming from the inability to perform robust clinical trials to convince decision-makers to pay the high prices for the potential long-term treatment benefits provided. This article aims to review the recommendations that have been published for evidence generation and economic analysis for GTs against the feasibility of their implementation within current HTA decision analysis frameworks. After reviewing the systematically identified literature, we found that questions remain on the appropriateness of GT evidence generation, considering that additional, broader values brought by GTs seem insufficiently incorporated within proposed analytic methods. In cases where innovative methods are proposed, HTA organizations remain highly conservative and resistant to change their reference case and decision analysis framework. Such resistances are largely attributed to the substantial evidence uncertainty, resource-consuming administration process, and the absence of consensus on the optimized methodology to balance all the advantages and potential pitfalls of GTs.

An overview of health technology assessments of gene therapies with the focus on cost-effectiveness models.

BACKGROUND: Gene therapies can treat, prevent, or cure a disease by changing the expression of a person's genes. They are an innovative strategy for treating genetic disorders; however, they are still emerging on the market access and in the healthcare system. Health technology assessment (HTA) agencies have not yet elaborated any standardised approach for assessing gene therapies; therefore, significant differences can be seen during HTAs carried out in various countries. In this review, we focused on submitted economic models of gene therapies approved for use by the US FDA and EMA with the aim to provide a comprehensive summary of how selected HTA bodies assessed the cost-effectiveness of gene therapies. An additional objective was to examine and discuss differences in the methods used in economic models across countries and drugs. METHODS: We identified economic models of gene therapies from six countries (NICE, IQWiG, SMC, HAS, CADTH, ICER) and focused on nine agents (Glybera, Imlygic, Strimvelis, Yescarta, Kymriah, Luxturna, Zynteglo, Zolgensma, Tecartus). Details of cost-utility evaluations and budget impact models were reviewed and extracted. RESULTS: Overall, 983 publications were identified, and 17 studies were included for the analysis. Reviewed evaluations of gene therapies differed in terms of the study perspective, discounting, extrapolation of outcomes based on limited and immature data, time horizon, and adequate estimation of benefits in terms of quality-adjusted life-years. Methods of economic evaluations were in line with the current recommendations; however, long-term follow-up studies are still missing. CONCLUSIONS: Discrepancies in an economic evaluation of gene therapies between different HTA bodies are rooted in a lack of general assessment frameworks specific to gene therapies. Although challenges were resolved by adjustments to the currently used value assessment framework, new methodological approaches would be useful. In addition, to improve the methods and quality of an evaluation, further research would be valuable.