An Analysis of Uncertainties and Data Collection Agreements in the Cancer Drugs Fund.

IF 2 Q2 ECONOMICS
PharmacoEconomics Open Pub Date : 2024-03-01 Epub Date: 2023-12-12 DOI:10.1007/s41669-023-00460-9
Laura A Trigg, Maxwell S Barnish, Samuel Hayward, Naomi Shaw, Louise Crathorne, Brad Groves, John Spoors, Thomas Strong, G J Melendez-Torres, Caroline Farmer
{"title":"An Analysis of Uncertainties and Data Collection Agreements in the Cancer Drugs Fund.","authors":"Laura A Trigg, Maxwell S Barnish, Samuel Hayward, Naomi Shaw, Louise Crathorne, Brad Groves, John Spoors, Thomas Strong, G J Melendez-Torres, Caroline Farmer","doi":"10.1007/s41669-023-00460-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Managed Access Agreements (MAAs) are a commercial arrangement that provide patients earlier access to innovative health technologies while uncertainties in the evidence base are resolved through data collection. In the UK, data collection agreements (DCAs) outline the evidence that will be collected during the MAA period and are intended to resolve uncertainties in the clinical- and cost-effectiveness of a technology sufficient for the National Institute of Health and Care Excellence (NICE) committee to make a final decision on reimbursement.</p><p><strong>Objective: </strong>The aim of this study was to identify the primary uncertainties leading to a recommendation for entry to the Cancer Drugs Fund (CDF) and evaluate how the corresponding DCAs attempt to address these.</p><p><strong>Methods: </strong>A database of MAAs agreed within the CDF was compiled with coverage between July 2016 and December 2020 (the time during which evidence generation was routinely collected within the CDF up until the time of analysis). Uncertainties in the evidence base for technologies entering the CDF were analysed alongside the outcomes planned for data collection during the MAA. These data provide an overview of the key uncertainties surrounding health technologies in the CDF on entry and the types of evidence targeted by DCAs.</p><p><strong>Results: </strong>In the assessment of 39 Cancer Drugs Fund (CDF) cases, NICE committees identified a total of 108 key uncertainties in cost-effectiveness estimates. Overall survival was the most commonly identified uncertainty, followed by generalisability of the evidence to the target population. DCAs specified a range of outcomes relevant to understanding the clinical effectiveness of the technology, though fewer than half (43.6%) of the DCAs addressed all the key uncertainties identified by the NICE committee.</p><p><strong>Conclusion: </strong>The analysis indicated that data collection within the CDF is not sufficient to resolve all the uncertainties identified by the NICE committee, meaning that other approaches will be needed at re-appraisal to ensure that the NICE committee can reach a final decision on reimbursement.</p>","PeriodicalId":19770,"journal":{"name":"PharmacoEconomics Open","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10883900/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PharmacoEconomics Open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41669-023-00460-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/12/12 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Managed Access Agreements (MAAs) are a commercial arrangement that provide patients earlier access to innovative health technologies while uncertainties in the evidence base are resolved through data collection. In the UK, data collection agreements (DCAs) outline the evidence that will be collected during the MAA period and are intended to resolve uncertainties in the clinical- and cost-effectiveness of a technology sufficient for the National Institute of Health and Care Excellence (NICE) committee to make a final decision on reimbursement.

Objective: The aim of this study was to identify the primary uncertainties leading to a recommendation for entry to the Cancer Drugs Fund (CDF) and evaluate how the corresponding DCAs attempt to address these.

Methods: A database of MAAs agreed within the CDF was compiled with coverage between July 2016 and December 2020 (the time during which evidence generation was routinely collected within the CDF up until the time of analysis). Uncertainties in the evidence base for technologies entering the CDF were analysed alongside the outcomes planned for data collection during the MAA. These data provide an overview of the key uncertainties surrounding health technologies in the CDF on entry and the types of evidence targeted by DCAs.

Results: In the assessment of 39 Cancer Drugs Fund (CDF) cases, NICE committees identified a total of 108 key uncertainties in cost-effectiveness estimates. Overall survival was the most commonly identified uncertainty, followed by generalisability of the evidence to the target population. DCAs specified a range of outcomes relevant to understanding the clinical effectiveness of the technology, though fewer than half (43.6%) of the DCAs addressed all the key uncertainties identified by the NICE committee.

Conclusion: The analysis indicated that data collection within the CDF is not sufficient to resolve all the uncertainties identified by the NICE committee, meaning that other approaches will be needed at re-appraisal to ensure that the NICE committee can reach a final decision on reimbursement.

癌症药物基金的不确定性和数据收集协议分析。
背景:管理下获取协议(MAA)是一种商业安排,在通过数据收集解决证据基础中的不确定性的同时,让患者更早地获取创新医疗技术。在英国,数据收集协议(DCA)概述了在 MAA 期间将收集的证据,其目的是解决某项技术在临床和成本效益方面的不确定性,使英国国家健康与护理卓越研究所(NICE)委员会能够就报销问题做出最终决定:本研究旨在确定导致建议进入癌症药物基金(CDF)的主要不确定性因素,并评估相应的诊断性评估协议如何试图解决这些不确定性因素:编制了一个在 CDF 内达成一致的 MAA 数据库,其覆盖范围为 2016 年 7 月至 2020 年 12 月(CDF 内例行收集证据生成的时间,直至分析之时)。在分析进入 CDF 的技术的证据基础不确定性的同时,还分析了在 MAA 期间计划收集数据的结果。这些数据概述了进入 CDF 的医疗技术的主要不确定性,以及 DCA 所针对的证据类型:在对 39 个癌症药物基金(CDF)案例的评估中,NICE 委员会共发现了 108 个成本效益估算中的关键不确定性。总体存活率是最常见的不确定因素,其次是证据对目标人群的普遍性。虽然只有不到一半(43.6%)的DCA涉及到了NICE委员会确定的所有关键不确定性,但DCA明确了一系列与了解技术临床有效性相关的结果:分析表明,CDF 内的数据收集不足以解决 NICE 委员会确定的所有不确定性,这意味着在重新评估时需要采用其他方法,以确保 NICE 委员会能够就报销问题做出最终决定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
3.50
自引率
0.00%
发文量
64
审稿时长
8 weeks
期刊介绍: PharmacoEconomics - Open focuses on applied research on the economic implications and health outcomes associated with drugs, devices and other healthcare interventions. The journal includes, but is not limited to, the following research areas:Economic analysis of healthcare interventionsHealth outcomes researchCost-of-illness studiesQuality-of-life studiesAdditional digital features (including animated abstracts, video abstracts, slide decks, audio slides, instructional videos, infographics, podcasts and animations) can be published with articles; these are designed to increase the visibility, readership and educational value of the journal’s content. In addition, articles published in PharmacoEconomics -Open may be accompanied by plain language summaries to assist readers who have some knowledge of, but not in-depth expertise in, the area to understand important medical advances.All manuscripts are subject to peer review by international experts. Letters to the Editor are welcomed and will be considered for publication.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信