• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

《NICE 癌症治疗技术评估中使用的生存分析方法回顾:一致性、局限性和改进领域》

A Review of Survival Analysis Methods Used in NICE Technology Appraisals of Cancer Treatments: Consistency, Limitations, and Areas for Improvement.

机构信息

School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.

Saw Swee Hock School of Public Health, National University of Singapore.

出版信息

Med Decis Making. 2019 Nov;39(8):899-909. doi: 10.1177/0272989X19881967. Epub 2019 Nov 9.

DOI:10.1177/0272989X19881967
PMID:31707911
Abstract

In June 2011, the National Institute for Health and Care Excellence (NICE) Decision Support Unit published a Technical Support Document (TSD) providing recommendations on survival analysis for NICE technology appraisals (TAs). Survival analysis outputs are influential inputs into economic models estimating the cost-effectiveness of new cancer treatments. Hence, it is important that systematic and justifiable model selection approaches are used. This study investigates the extent to which the TSD recommendations have been followed since its publication. We reviewed NICE cancer TAs completed between July 2011 and July 2017. Information on survival analyses undertaken and associated critiques for overall survival (OS) and progression-free survival were extracted from the company submissions, Evidence Review Group (ERG) reports, and final appraisal determination documents. Information was extracted from 58 TAs. Only 4 (7%) followed all TSD recommendations for OS outcomes. The vast majority (91%) compared a range of common parametric models and assessed their fit to the data (86%). Only a minority of TAs included an assessment of the shape of the hazard function (38%) or proportional hazards assumption (40%). Validation of the extrapolated portion of the survival function using external data was attempted in a minority of TAs (40%). Extrapolated survival functions were frequently criticized by ERGs (71%). Survival analysis within NICE TAs remains suboptimal, despite publication of the TSD. Model selection is not undertaken in a systematic way, resulting in inconsistencies between TAs. More attention needs to be given to assessing hazard functions and validation of extrapolated survival functions. Novel methods not described in the TSD have been used, particularly in the context of immuno-oncology, suggesting that an updated TSD may be of value.

摘要

2011 年 6 月,英国国家卫生与保健优化研究所(NICE)决策支持单位发布了一份技术支持文件(TSD),就生存分析在 NICE 技术评估(TA)中的应用提出了建议。生存分析结果是评估新癌症治疗方法成本效益的经济模型的重要输入。因此,采用系统和合理的模型选择方法非常重要。本研究调查了自 TSD 发布以来,其建议得到遵循的程度。

我们回顾了 2011 年 7 月至 2017 年 7 月期间完成的 NICE 癌症 TA。从公司提交的文件、证据审查组(ERG)报告和最终评估决定文件中提取了关于生存分析的信息,以及关于总生存期(OS)和无进展生存期(PFS)的相关评论。

信息从 58 项 TA 中提取。只有 4 项(7%)遵循了 OS 结果的所有 TSD 建议。绝大多数(91%)比较了一系列常见的参数模型,并评估了它们对数据的拟合程度(86%)。只有少数 TA 包括对危险函数形状的评估(38%)或比例风险假设(40%)。少数 TA(40%)尝试使用外部数据验证生存函数的外推部分。外推生存函数经常受到 ERG 的批评(71%)。

尽管 TSD 已经发布,但 NICE TA 中的生存分析仍然不理想。模型选择没有系统地进行,导致 TA 之间存在不一致。需要更加关注评估危险函数和验证外推生存函数。已经使用了 TSD 中未描述的新方法,特别是在免疫肿瘤学方面,这表明更新的 TSD 可能具有价值。

相似文献

1
A Review of Survival Analysis Methods Used in NICE Technology Appraisals of Cancer Treatments: Consistency, Limitations, and Areas for Improvement.《NICE 癌症治疗技术评估中使用的生存分析方法回顾:一致性、局限性和改进领域》
Med Decis Making. 2019 Nov;39(8):899-909. doi: 10.1177/0272989X19881967. Epub 2019 Nov 9.
2
How Do Pharmaceutical Companies Model Survival of Cancer Patients? A Review of NICE Single Technology Appraisals in 2017.制药公司如何对癌症患者的生存情况进行建模?对 2017 年 NICE 单一技术评估的回顾。
Int J Technol Assess Health Care. 2019 Jan;35(2):160-167. doi: 10.1017/S0266462319000175.
3
Clinical effectiveness reporting of novel cancer drugs in the context of non-proportional hazards: a review of nice single technology appraisals.新型癌症药物在非比例风险情况下的临床效果报告:对 NICE 单一技术评估的回顾。
Int J Technol Assess Health Care. 2023 Mar 8;39(1):e16. doi: 10.1017/S0266462323000119.
4
Use of external data to inform overall survival extrapolation in NICE technology appraisals for oncology drugs.利用外部数据为英国国家卫生与临床优化研究所(NICE)肿瘤药物技术评估中的总生存期外推提供信息。
J Med Econ. 2025 Dec;28(1):803-813. doi: 10.1080/13696998.2025.2506968. Epub 2025 May 24.
5
The use of UK primary care databases in health technology assessments carried out by the National Institute for health and care excellence (NICE).英国初级医疗数据库在英国国家卫生与临床优化研究所(NICE)开展的卫生技术评估中的应用。
BMC Health Serv Res. 2020 Jul 22;20(1):675. doi: 10.1186/s12913-020-05529-3.
6
Modelling approaches for histology-independent cancer drugs to inform NICE appraisals: a systematic review and decision-framework.基于组织学的癌症药物建模方法,为 NICE 评估提供信息:系统评价和决策框架。
Health Technol Assess. 2021 Dec;25(76):1-228. doi: 10.3310/hta25760.
7
A review and validation of overall survival extrapolation in health technology assessments of cancer immunotherapy by the National Institute for Health and Care Excellence: how did the initial best estimate compare to trial data subsequently made available?英国国家卫生与临床优化研究所对癌症免疫疗法卫生技术评估中总生存外推法的回顾与验证:最初的最佳估计与随后可得的试验数据相比如何?
J Med Econ. 2019 Mar;22(3):205-214. doi: 10.1080/13696998.2018.1547303. Epub 2018 Nov 30.
8
The use of exploratory analyses within the National Institute for Health and Care Excellence single technology appraisal process: an evaluation and qualitative analysis.在英国国家卫生与临床优化研究所(NICE)单一技术评估过程中使用探索性分析:评估与定性分析。
Health Technol Assess. 2016 Apr;20(26):1-48. doi: 10.3310/hta20260.
9
The Type and Impact of Evidence Review Group Exploratory Analyses in the NICE Single Technology Appraisal Process.英国国家卫生与临床优化研究所单一技术评估过程中证据审查小组探索性分析的类型及影响
Value Health. 2017 Jun;20(6):785-791. doi: 10.1016/j.jval.2016.08.729. Epub 2016 Oct 21.
10
Venetoclax for Treating Chronic Lymphocytic Leukaemia: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.维奈托克治疗慢性淋巴细胞白血病:NICE 单技术评估的循证评估组观点。
Pharmacoeconomics. 2018 Apr;36(4):399-406. doi: 10.1007/s40273-017-0599-9.

引用本文的文献

1
Relative Survival Modeling for Appraising the Cost-Effectiveness of Life-Extending Treatments: An Application to Tafamidis for the Treatment of Transthyretin Amyloidosis with Cardiomyopathy.评估延长生命治疗成本效益的相对生存模型:塔非酰胺治疗转甲状腺素蛋白淀粉样变心肌病的应用
Med Decis Making. 2025 Aug;45(6):726-739. doi: 10.1177/0272989X251342459. Epub 2025 Jun 17.
2
Evaluating Semi-Markov Processes and Other Epidemiological Time-to-Event Models by Computing Disease Sojourn Density as Partial Differential Equations.通过将疾病停留密度计算为偏微分方程来评估半马尔可夫过程和其他流行病学事件发生时间模型。
Med Decis Making. 2025 Jul;45(5):569-586. doi: 10.1177/0272989X251333398. Epub 2025 May 8.
3
Improving Health Outcomes Through Treatment Sequencing Optimization in Multiple Myeloma: A Simulation Model in Transplant-Ineligible Patients.
通过多发性骨髓瘤治疗序贯优化提高健康结局:移植不合格患者的模拟模型。
Cancer Rep (Hoboken). 2024 Oct;7(10):e70027. doi: 10.1002/cnr2.70027.
4
An Evaluation of an Algorithm for the Selection of Flexible Survival Models for Cancer Immunotherapies: Pass or Fail?一种用于选择癌症免疫疗法中灵活生存模型的算法评估:通过还是失败?
Pharmacoeconomics. 2024 Dec;42(12):1395-1412. doi: 10.1007/s40273-024-01429-0. Epub 2024 Sep 20.
5
Trends in NICE technology appraisals of non-small cell lung cancer drugs over the last decade.过去十年间英国国家卫生与临床优化研究所(NICE)对非小细胞肺癌药物进行技术评估的趋势。
Eur J Health Econ. 2025 Apr;26(3):455-471. doi: 10.1007/s10198-024-01711-0. Epub 2024 Aug 30.
6
Mixture and Non-mixture Cure Models for Health Technology Assessment: What You Need to Know.用于卫生技术评估的混合与非混合治愈模型:你需要了解的内容。
Pharmacoeconomics. 2024 Oct;42(10):1073-1090. doi: 10.1007/s40273-024-01406-7. Epub 2024 Jul 5.
7
Challenges and Opportunities in Interdisciplinary Research and Real-World Data for Treatment Sequences in Health Technology Assessments.在健康技术评估的治疗序列中,跨学科研究和真实世界数据面临的挑战与机遇。
Pharmacoeconomics. 2024 May;42(5):487-506. doi: 10.1007/s40273-024-01363-1. Epub 2024 Apr 1.
8
SurvInt: a simple tool to obtain precise parametric survival extrapolations.SurvInt:一种简单的工具,可获得精确的参数生存外推。
BMC Med Inform Decis Mak. 2024 Mar 14;24(1):76. doi: 10.1186/s12911-024-02475-6.
9
Deep Learning Techniques with Genomic Data in Cancer Prognosis: A Comprehensive Review of the 2021-2023 Literature.癌症预后中基因组数据的深度学习技术:2021 - 2023年文献综述
Biology (Basel). 2023 Jun 21;12(7):893. doi: 10.3390/biology12070893.
10
Survival Extrapolation Incorporating General Population Mortality Using Excess Hazard and Cure Models: A Tutorial.利用超额风险和治愈模型纳入一般人群死亡率的生存外推:教程。
Med Decis Making. 2023 Aug;43(6):737-748. doi: 10.1177/0272989X231184247. Epub 2023 Jul 13.