Analysis of factors associated with use of real-world data in single technology appraisals of cancer drugs by the National Institute for Health and Care Excellence

IF 2 Q3 HEALTH POLICY & SERVICES Journal of Cancer Policy Pub Date : 2024-09-26 DOI:10.1016/j.jcpo.2024.100507
{"title":"Analysis of factors associated with use of real-world data in single technology appraisals of cancer drugs by the National Institute for Health and Care Excellence","authors":"","doi":"10.1016/j.jcpo.2024.100507","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><div>This study investigates factors associated with use of real-world data (RWD) in economic modelling for single technology appraisals (STAs) of cancer drugs by the National Institute for Health and Care Excellence (NICE) to improve systematic understanding of the use of RWD.</div></div><div><h3>Methods</h3><div>The data were extracted from STAs of cancer drugs, for which NICE issued guidance between January 2011 and December 2022 (n=267). Binary regression was used to test hypotheses concerning the greater or lesser use of RWD. Bonferroni-Holm correction was used to control error rates in multiple hypotheses tests. Several explanatory variables were considered in this analysis, including time (<em>Time</em>), incidence rate of disease (<em>IR</em>), availability of direct treatment comparison (<em>AD</em>), generalisability of trial data (<em>GE</em>), maturity of survival data in trial (<em>MS</em>) and previous technology recommendations by NICE (<em>PR</em>). The primary outcome variable was <em>any</em> use of RWD. Secondary outcome variables were specific uses of RWD in economic models.</div></div><div><h3>Results</h3><div><em>AD</em> had a statistical negative association with <em>any</em> use of RWD whereas no associations with <em>non-parametric</em> and <em>parametric</em> use of RWD were found. <em>Time</em> had several statistical associations with use of RWD (validating survival distributions for the intervention, estimating progression-free survival for the intervention, estimating overall survival for comparators and transition probabilities).</div></div><div><h3>Conclusions</h3><div>RWD were more likely to be used in economic modelling of cancer drugs when randomised controlled trials failed to provide relevant clinical information of the drug for appraisals, particularly in the absence of direct treatment comparisons. These results, based on analysis of data systematically collected from previous appraisals, suggest that uses of RWD were associated with data gaps in the economic modelling. While this result may support some of the claimed advantages of using RWD when evidence is absent, the question, the extent to which use of RWD in indirect treatment comparisons reduces uncertainty is still to be determined.</div></div>","PeriodicalId":38212,"journal":{"name":"Journal of Cancer Policy","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cancer Policy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213538324000419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Objectives

This study investigates factors associated with use of real-world data (RWD) in economic modelling for single technology appraisals (STAs) of cancer drugs by the National Institute for Health and Care Excellence (NICE) to improve systematic understanding of the use of RWD.

Methods

The data were extracted from STAs of cancer drugs, for which NICE issued guidance between January 2011 and December 2022 (n=267). Binary regression was used to test hypotheses concerning the greater or lesser use of RWD. Bonferroni-Holm correction was used to control error rates in multiple hypotheses tests. Several explanatory variables were considered in this analysis, including time (Time), incidence rate of disease (IR), availability of direct treatment comparison (AD), generalisability of trial data (GE), maturity of survival data in trial (MS) and previous technology recommendations by NICE (PR). The primary outcome variable was any use of RWD. Secondary outcome variables were specific uses of RWD in economic models.

Results

AD had a statistical negative association with any use of RWD whereas no associations with non-parametric and parametric use of RWD were found. Time had several statistical associations with use of RWD (validating survival distributions for the intervention, estimating progression-free survival for the intervention, estimating overall survival for comparators and transition probabilities).

Conclusions

RWD were more likely to be used in economic modelling of cancer drugs when randomised controlled trials failed to provide relevant clinical information of the drug for appraisals, particularly in the absence of direct treatment comparisons. These results, based on analysis of data systematically collected from previous appraisals, suggest that uses of RWD were associated with data gaps in the economic modelling. While this result may support some of the claimed advantages of using RWD when evidence is absent, the question, the extent to which use of RWD in indirect treatment comparisons reduces uncertainty is still to be determined.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
国家健康与护理卓越研究所对癌症药物的单一技术评估中使用真实世界数据的相关因素分析。
研究目的本研究调查了美国国家健康与护理优化研究所(NICE)在癌症药物单一技术评估(STAs)的经济建模中使用真实世界数据(RWD)的相关因素,以提高对RWD使用的系统性理解:方法:从2011年1月至2022年12月期间NICE发布指南的抗癌药物STA中提取数据(n=267)。采用二元回归法检验有关RWD使用多寡的假设。Bonferroni-Holm 校正用于控制多重假设检验中的误差率。该分析考虑了多个解释变量,包括时间(Time)、疾病发病率(IR)、是否有直接治疗对比(AD)、试验数据的通用性(GE)、试验中生存数据的成熟度(MS)和 NICE 先前的技术建议(PR)。主要结果变量为是否使用 RWD。次要结果变量为经济模型中RWD的具体用途:结果:AD 与任何 RWD 的使用在统计学上呈负相关,而与非参数和参数 RWD 的使用则无关联。时间与RWD的使用有几种统计学关联(验证干预的生存分布、估计干预的无进展生存期、估计比较者的总生存期和过渡概率):当随机对照试验无法为评估提供药物的相关临床信息时,尤其是在缺乏直接治疗比较的情况下,在癌症药物的经济建模中更有可能使用RWD。这些结果是在对以往评估中系统收集的数据进行分析的基础上得出的,表明随机对照试验的使用与经济建模中的数据缺口有关。虽然这一结果可能支持了在缺乏证据时使用 RWD 的一些优势,但在间接治疗比较中使用 RWD 在多大程度上减少了不确定性这一问题仍有待确定。
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 去求助
来源期刊
Journal of Cancer Policy
Journal of Cancer Policy Medicine-Health Policy
CiteScore
2.40
自引率
7.70%
发文量
47
审稿时长
65 days
期刊最新文献
Income disparities have a significant impact on thyroid cancer recurrence and survival An assessment of cancer centre level designation and guideline adherent care in those with rectal cancer: A population based retrospective cohort study Spending on anticancer drugs among Medicare beneficiaries: Analyzing predictors of drug expenditures Barriers to identifying and addressing health-related social needs in cancer care: Patient and patient navigator perspectives Analysis of factors associated with use of real-world data in single technology appraisals of cancer drugs by the National Institute for Health and Care Excellence
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1