Rosenberg Noa, Manders Evert, van den Berg Sibren, Deesker Lisa J, Garrelfs Sander F, de Visser Saco J, Groothoff Jaap W, Hollak Carla E M
Medicine for Society, Platform at Amsterdam University Medical Center - University of Amsterdam, Amsterdam, The Netherlands.
Department of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Research Institute, Meibergdreef 9, Amsterdam, The Netherlands.
Orphanet J Rare Dis. 2024 Dec 23;19(1):485. doi: 10.1186/s13023-024-03446-w.
The combination of high prices and uncertain effectiveness is a growing challenge in the field of orphan medicines, hampering health technology assessments. Hence, new methods for establishing price benchmarks might be necessary to support reimbursement negotiations. In this study, we applied several pricing models containing cost-based elements to the case of lumasiran for treating primary hyperoxaluria type 1.
Price ranges were calculated by estimating minimum and maximum scenarios for four pricing models: Novel Cancer Pricing Model (NCP-model), AIM Model for Innovative Medicines (AIM-model), Discounted Cash Flow model (DCF-model), and the Real-Option Rate Of Return model (ROROR-model). Data was gathered from disease registries, scientific literature, Security and Exchange Committee filings, and expert opinion. A sensitivity analysis was performed to assess the parameters with the largest influence.
Outcomes resulting from the NCP-model ranged between €87,000 and €224,000 per patient per year, between €33,000 and €340,000 for the AIM-model, between €182,000 and €748,000 for the DCF-model, and between €81,000 and €273,000 for the ROROR-model.
Outcomes of the four pricing models show wide and heterogeneous price ranges. The DCF-model might be most compatible with the case of lumasiran, due to inclusion of parameters for prevalence, incidence, prescription restrictions and cost of capital. The minimum DCF price could serve as a starting point for pricing and reimbursement negotiations. Uncertainties can be solved by more transparency on input variables.
高昂的价格与不确定的疗效并存，这在孤儿药领域构成了日益严峻的挑战，阻碍了卫生技术评估。因此，可能需要新的方法来建立价格基准，以支持报销谈判。在本研究中，我们将几种包含基于成本要素的定价模型应用于治疗1型原发性高草酸尿症的鲁马西拉案例。
通过估算四种定价模型（新型癌症定价模型（NCP模型）、创新药物AIM模型（AIM模型）、现金流折现模型（DCF模型）和实物期权回报率模型（ROROR模型））的最低和最高情景来计算价格范围。数据收集自疾病登记处、科学文献、美国证券交易委员会文件以及专家意见。进行了敏感性分析，以评估影响最大的参数。
NCP模型得出的结果为每位患者每年87,000欧元至224,000欧元，AIM模型为33,000欧元至340,000欧元，DCF模型为182,000欧元至748,000欧元，ROROR模型为81,000欧元至273,000欧元。
四种定价模型的结果显示出广泛且各异的价格范围。DCF模型可能与鲁马西拉案例最为契合，因为它纳入了患病率、发病率、处方限制和资本成本等参数。DCF模型的最低价格可作为定价和报销谈判的起点。通过提高输入变量的透明度可以解决不确定性问题。
