Background and Objective Haemophilia B is a rare genetic disease that is caused by a deficiency of coagulation factor IX (FIX) in the blood and leads to internal and external bleeding. Under the current standard of care, haemophilia is treated either prophylactically or on-demand via intravenous infusions of FIX. These treatment strategies impose a high burden on patients and health care systems as haemophilia B requires lifelong treatment, and FIX is costly. Etranacogene dezaparvovec (ED) is a gene therapy for haemophilia B that has been recently approved by the United States Food and Drug Administration and has received a recommendation for conditional marketing authorization by the European Medicines Agency. We aimed to examine the cost-effectiveness of ED versus extended half-life FIX (EHL-FIX) prophylaxis for moderate-to-severe haemophilia B from a German health care payer perspective. Methods A microsimulation model was implemented in R. The model used data from the ED phase 3 clinical trial publication and further secondary data sources to simulate and compare patients receiving ED or EHL-FIX prophylaxis over a lifetime horizon, with the potential for ED patients to switch treatment to EHL-FIX prophylaxis when the effectiveness of ED waned. Primary outcomes of this analysis included discounted total costs, discounted quality-adjusted life years (QALYs), incremental cost-effectiveness, and the incremental net monetary benefit. The annual discount rate for costs and effects was 3%. Uncertainty was examined via probabilistic analysis and additional univariate sensitivity analyses. Results Probabilistic analysis indicated that patients treated with ED instead of EHL-FIX prophylaxis gained 0.50 QALYs and experienced cost savings of EUR 1,179,829 at a price of EUR 1,500,000 per ED treatment. ED was the dominant treatment strategy. At a willingness to pay of EUR 50,000/QALY, the incremental net monetary benefit amounted to EUR 1,204,840. Discussion Depending on the price, ED can save costs and improve health outcomes of haemophilia patients compared with EHL-FIX prophylaxis, making it a potentially cost-effective alternative. These results are uncertain due to a lack of evidence regarding the long-term effectiveness of ED.

Aims: Haemophilia is a rare genetic disease that hinders blood clotting. We aimed to review model-based cost-effectiveness analyses (CEAs) of haemophilia treatments, describe the sources of clinical evidence used by these CEAs, summarize the reported cost-effectiveness of different treatment strategies, and assess the quality and risk of bias. Methods: We conducted a systematic literature review of model-based CEAs of haemophilia treatments by searching databases, the Tufts Medical Center CEA registry, and grey literature. We summarized and qualitatively synthesized the approaches and results of the included CEAs, without a meta-analysis due the diversity of the studies. Results: 32 eligible studies were performed in 12 countries and reported 53 pairwise comparisons. Most studies analysed patients with haemophilia A rather than haemophilia B. Comparisons of prophylactic versus on-demand treatment indicated that prophylaxis may not be cost-effective, but there was no clear consensus. Emicizumab was generally cost-effective compared with clotting factor treatments and was always dominant for patients with inhibitors. Immune tolerance induction following a Malmö protocol was found to be cost-effective compared to bypassing agents, while there was no consensus for the other protocols. Gene therapies as well as treatment with extended half-life coagulation factors were always cost-effective over their comparators. Studies were highly heterogenous regarding their time horizons, model structures, the inclusion of bleeding-related mortality and quality-of-life impacts. This heterogeneity limited the comparability of the studies. 19 of the 32 included studies received industry funding, which may have biased their results. Limitations: It was not possible to perform a quantitative synthesis of the results due to the heterogeneity of the underlying studies. Conclusion: Differences in results between previous CEAs may have been driven by heterogeneity in modelling approaches, clinical input data, and potential funding biases. A more consistent evidence base and modelling approach would enhance the comparability between CEAs.