Italian Medicines Agency, Rome, Italy; Department of Medicine and Aging Sciences, University of Studies G. d'Annunzio, Chieti-Pescara, Italy.
Institute for Leadership and Management in Health, Kingston Business School, Kingston University, London, England, UK.
Value Health. 2021 Sep;24(9):1273-1278. doi: 10.1016/j.jval.2021.04.1278. Epub 2021 Jun 24.
The main objective of this study was to evaluate the potential role of efficacy data and other information available at the time of price and reimbursement (P&R) decision-making process within the definition of oncology treatment costs in Italy.
The study included all P&R dossiers submitted to the Italian Medicines Agency between July 2015 and December 2017. It prospectively collected the data of the P&R process starting from dossier submission up to the Italian Health Service reimbursement decision. The cost of treatment per patient was estimated using both the list price ("gross cost") and the confidential net price ("net cost") of drug packages and applied to the median duration of treatment. A 2-sample stage Heckman decomposition model was used to evaluate the potential role of efficacy data and other information available at the time of P&R decision making on the gross and net cost.
A total of 37 oncology drugs related to 58 therapeutic indications were analyzed. The multivariate model showed that the variation of progression-free survival is the only variable predictor statistically associated with treatment cost, but this effect was observed only when confidential net prices were used (P=.026).
Considering the perspective of a developed country having a public healthcare service with a central reimbursement negotiation is determined a relevant reduction in the treatment cost purchased by public payers. This is a useful approach to guarantee the affordability of innovative oncology drugs and to contain public expenditures on healthcare. Furthermore, the negotiation of confidential discounts and agreement clauses in managed entry agreements seemed to reward oncology drugs displaying an added therapeutic benefit.
本研究的主要目的是评估在意大利肿瘤治疗成本定义中，定价和报销（P&R）决策过程中可获得的疗效数据和其他信息的潜在作用。
该研究纳入了 2015 年 7 月至 2017 年 12 月期间提交给意大利药品管理局的所有 P&R 档案。它前瞻性地收集了 P&R 流程的数据，从档案提交到意大利卫生服务报销决策。每位患者的治疗成本使用药物包的标价（“毛成本”）和机密净价（“净成本”）进行估计，并应用于治疗的中位数持续时间。采用双样本 Heckman 分解模型评估 P&R 决策时可获得的疗效数据和其他信息对毛成本和净成本的潜在作用。
共分析了 37 种与 58 种治疗适应症相关的肿瘤药物。多变量模型显示，无进展生存期的变化是唯一与治疗成本具有统计学关联的变量预测因素，但仅在使用机密净价时观察到这种影响（P=.026）。
从拥有公共医疗服务和中央报销谈判的发达国家的角度来看，购买者支付的治疗成本显著降低。这是一种确保创新肿瘤药物可负担性和控制医疗保健公共支出的有效方法。此外，在管理准入协议中谈判机密折扣和协议条款似乎会奖励显示出附加治疗益处的肿瘤药物。
