The Acceptance of Overall Survival Extrapolation Methods in Solid Tumor Treatments by Health Technology Assessment Agencies in England, France, and Australia between 2017 and 2022.

IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Medical Decision Making Pub Date : 2025-11-01 Epub Date: 2025-08-02 DOI:10.1177/0272989X251351635
Jean-Baptiste Trouiller, Arthur Quenéchdu, Mondher Toumi, Laurent Boyer, Philippe Laramée
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引用次数: 0

Abstract

BackgroundSurvival extrapolation is used to predict patients' overall survival beyond clinical trial follow-up. It can significantly affect the results of a cost-effectiveness analysis and subsequent pricing and reimbursement decisions. However, selecting an appropriate model involves subjectivity, leading to discrepancies between methods submitted by manufacturers and those accepted by health technology assessment (HTA) agencies. This review describes the acceptance and criticisms of overall survival extrapolation methods by HTA agencies in England, France, and Australia.MethodsElectronic searches conducted on September 4, 2022, identified HTA evaluations for oncology therapies indicated for the treatment of solid tumors from the National Institute for Health and Care Excellence (NICE) in England, the Haute Autorité de Santé (HAS) in France, and the Pharmaceutical Benefits Advisory Committee (PBAC) in Australia, published between August 2017 and August 2022. Information on the overall survival extrapolation model submitted by the manufacturer was extracted. The acceptance decision of the HTA agency and the key criticisms were also recorded.ResultsA total of 140 HTA evaluations were identified. The initial overall survival extrapolation method was accepted in 21% of cases. The most frequently cited criticisms related to a lack of or inappropriate incorporation of treatment effect waning over time (31%). Other criticisms included choice of parametric distribution, in which multiple distributions were often considered plausible (24%); immaturity of survival data (15%); and concerns about the proportional hazards assumption, which lacked clinical validity (8%).ConclusionThis review highlights the low acceptance of survival extrapolation methods and the areas of discordance between manufacturers and HTA agencies in England, France, and Australia. Low acceptance rates of survival extrapolation methods by HTA bodies can affect pricing and reimbursement decisions of new therapies, delaying patient access.HighlightsThis review found that the survival extrapolation methods initially submitted by companies were accepted in only 21% of cases.The most common areas of discordance between companies and HTA agencies were inappropriate modeling of treatment effect over time, choice of parametric distribution, immaturity of survival data, and concerns about the proportional hazards assumption.There is a need for more consistent guidance on the selection of an appropriate extrapolation method to limit the inherent subjectivity surrounding survival curve selection.

2017 - 2022年英国、法国和澳大利亚卫生技术评估机构对实体瘤治疗中总生存期外推法的接受程度
生存外推法用于预测临床试验随访后患者的总生存期。它可以显著影响成本效益分析的结果以及随后的定价和报销决策。然而,选择合适的模型涉及主观性,导致制造商提交的方法与卫生技术评估(HTA)机构接受的方法存在差异。本综述描述了英国、法国和澳大利亚HTA机构对总体生存外推法的接受和批评。方法:于2022年9月4日进行的电子检索,确定了2017年8月至2022年8月期间英国国家健康与护理卓越研究所(NICE)、法国高级自治机构(HAS)和澳大利亚药物效益咨询委员会(PBAC)针对实体瘤治疗的肿瘤疗法的HTA评估。提取制造商提交的总体生存外推模型信息。并记录了HTA机构的受理决定和主要批评意见。结果共鉴定出140个HTA评价。21%的病例接受初始总生存外推法。最常见的批评是缺乏或不适当地纳入治疗效果随着时间的推移而减弱(31%)。其他批评包括参数分布的选择,其中多个分布通常被认为是合理的(24%);生存数据不成熟(15%);对比例风险假设的担忧,缺乏临床效度(8%)。结论:本综述强调了英国、法国和澳大利亚对生存外推法的接受度较低,以及制造商和HTA机构之间存在不一致的领域。HTA机构对生存推断方法的低接受率会影响新疗法的定价和报销决策,延迟患者获得治疗。本综述发现,最初由公司提交的生存外推方法仅在21%的病例中被接受。公司和HTA机构之间最常见的不一致领域是不适当的治疗效果随时间的建模,参数分布的选择,生存数据的不成熟,以及对比例风险假设的担忧。有必要在选择适当的外推方法方面提供更一致的指导,以限制围绕生存曲线选择的固有主观性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Medical Decision Making
Medical Decision Making 医学-卫生保健
CiteScore
6.50
自引率
5.60%
发文量
146
审稿时长
6-12 weeks
期刊介绍: Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.
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