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癌症药物基金中的不确定性与数据收集协议分析

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

作者信息

Trigg Laura A, Barnish Maxwell S, Hayward Samuel, Shaw Naomi, Crathorne Louise, Groves Brad, Spoors John, Strong Thomas, Melendez-Torres G J, Farmer Caroline

机构信息

Department of Public Health and Sports Sciences, Peninsula Technology Assessment Group (PenTAG), Exeter, UK.

National Institute for Health and Care Excellence, London, UK.

出版信息

Pharmacoecon Open. 2024 Mar;8(2):303-311. doi: 10.1007/s41669-023-00460-9. Epub 2023 Dec 12.

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.

摘要

背景

管理准入协议(MAA)是一种商业安排,可让患者更早地获得创新医疗技术,同时通过数据收集来解决证据基础方面的不确定性。在英国,数据收集协议(DCA)概述了在MAA期间将收集的证据,旨在解决技术在临床和成本效益方面的不确定性,以便英国国家卫生与临床优化研究所(NICE)委员会就是否报销做出最终决定。

目的

本研究的目的是确定导致建议进入癌症药物基金(CDF)的主要不确定性,并评估相应的DCA如何试图解决这些问题。

方法

编制了一个CDF内商定的MAA数据库,涵盖2016年7月至2020年12月期间(即CDF常规收集证据直至分析之时)。分析了进入CDF的技术在证据基础方面的不确定性,以及MAA期间计划收集数据的结果。这些数据概述了CDF中健康技术进入时的关键不确定性以及DCA针对的证据类型。

结果

在对39个癌症药物基金(CDF)案例的评估中,NICE委员会在成本效益估计中总共确定了108个关键不确定性。总生存期是最常确定的不确定性,其次是证据对目标人群的可推广性。DCA规定了一系列与了解技术临床有效性相关的结果,不过只有不到一半(43.6%)的DCA解决了NICE委员会确定的所有关键不确定性。

结论

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其他方法,以确保NICE委员会能够就是否报销做出最终决定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e68/10883900/8dc190688a99/41669_2023_460_Fig1_HTML.jpg

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