• 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

临床预测规则制定与评估的方法学标准:文献综述

Methodological standards for the development and evaluation of clinical prediction rules: a review of the literature.

作者信息

Cowley Laura E, Farewell Daniel M, Maguire Sabine, Kemp Alison M

机构信息

Division of Population Medicine, School of Medicine, Neuadd Meirionnydd, Heath Park, Cardiff University, Wales, CF14 4YS UK.

出版信息

Diagn Progn Res. 2019 Aug 22;3:16. doi: 10.1186/s41512-019-0060-y. eCollection 2019.

DOI:10.1186/s41512-019-0060-y
PMID:31463368
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6704664/
Abstract

Clinical prediction rules (CPRs) that predict the absolute risk of a clinical condition or future outcome for individual patients are abundant in the medical literature; however, systematic reviews have demonstrated shortcomings in the methodological quality and reporting of prediction studies. To maximise the potential and clinical usefulness of CPRs, they must be rigorously developed and validated, and their impact on clinical practice and patient outcomes must be evaluated. This review aims to present a comprehensive overview of the stages involved in the development, validation and evaluation of CPRs, and to describe in detail the methodological standards required at each stage, illustrated with examples where appropriate. Important features of the study design, statistical analysis, modelling strategy, data collection, performance assessment, CPR presentation and reporting are discussed, in addition to other, often overlooked aspects such as the acceptability, cost-effectiveness and longer-term implementation of CPRs, and their comparison with clinical judgement. Although the development and evaluation of a robust, clinically useful CPR is anything but straightforward, adherence to the plethora of methodological standards, recommendations and frameworks at each stage will assist in the development of a rigorous CPR that has the potential to contribute usefully to clinical practice and decision-making and have a positive impact on patient care.

摘要

预测个体患者临床状况或未来结局绝对风险的临床预测规则(CPRs)在医学文献中大量存在;然而,系统评价已表明预测研究在方法学质量和报告方面存在缺陷。为了最大限度地发挥CPRs的潜力和临床实用性,必须对其进行严格开发和验证,并且必须评估它们对临床实践和患者结局的影响。本综述旨在全面概述CPRs开发、验证和评估所涉及的阶段,并详细描述每个阶段所需的方法学标准,并在适当的地方举例说明。除了其他经常被忽视的方面,如CPRs的可接受性、成本效益和长期实施,以及它们与临床判断的比较外,还讨论了研究设计、统计分析、建模策略、数据收集、性能评估、CPR呈现和报告的重要特征。尽管开发和评估一个强大的、临床有用的CPR绝非易事,但在每个阶段遵循大量的方法学标准、建议和框架将有助于开发一个严谨的CPR,它有可能对临床实践和决策做出有益贡献,并对患者护理产生积极影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de40/6704664/f3197cad5a29/41512_2019_60_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de40/6704664/958d80dc6490/41512_2019_60_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de40/6704664/f3197cad5a29/41512_2019_60_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de40/6704664/958d80dc6490/41512_2019_60_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de40/6704664/f3197cad5a29/41512_2019_60_Fig2_HTML.jpg

相似文献

1
Methodological standards for the development and evaluation of clinical prediction rules: a review of the literature.临床预测规则制定与评估的方法学标准:文献综述
Diagn Progn Res. 2019 Aug 22;3:16. doi: 10.1186/s41512-019-0060-y. eCollection 2019.
2
Diagnostic clinical prediction rules for categorising low back pain: A systematic review.用于对腰痛进行分类的诊断性临床预测规则:一项系统评价。
Musculoskeletal Care. 2023 Dec;21(4):1482-1496. doi: 10.1002/msc.1816. Epub 2023 Oct 9.
3
Clinical prediction rules for children: a systematic review.临床预测规则在儿童中的应用:系统综述。
Pediatrics. 2011 Sep;128(3):e666-77. doi: 10.1542/peds.2011-0043. Epub 2011 Aug 22.
4
Critical appraisal of clinical prediction rules that aim to optimize treatment selection for musculoskeletal conditions.对旨在优化肌肉骨骼疾病治疗选择的临床预测规则进行评价。
Phys Ther. 2010 Jun;90(6):843-54. doi: 10.2522/ptj.20090233. Epub 2010 Apr 22.
5
Clinical prediction rules for prognosis and treatment prescription in neck pain: A systematic review.颈部疼痛预后及治疗处方的临床预测规则:一项系统评价
Musculoskelet Sci Pract. 2017 Feb;27:155-164. doi: 10.1016/j.math.2016.10.066. Epub 2016 Oct 31.
6
Impact analysis studies of clinical prediction rules relevant to primary care: a systematic review.与初级保健相关的临床预测规则的影响分析研究:一项系统综述
BMJ Open. 2016 Mar 15;6(3):e009957. doi: 10.1136/bmjopen-2015-009957.
7
Systematic review of the effects of care provided with and without diagnostic clinical prediction rules.对有无诊断性临床预测规则的护理效果的系统评价。
Diagn Progn Res. 2017 Apr 26;1:13. doi: 10.1186/s41512-017-0013-2. eCollection 2017.
8
The future of Cochrane Neonatal.考克兰新生儿协作网的未来。
Early Hum Dev. 2020 Nov;150:105191. doi: 10.1016/j.earlhumdev.2020.105191. Epub 2020 Sep 12.
9
Clinical Prediction Rules That Don't Hold Up-Where to Go From Here?不成立的临床预测规则——接下来何去何从?
J Orthop Sports Phys Ther. 2016 Jul;46(7):502-5. doi: 10.2519/jospt.2016.0606.
10
Prescriptive clinical prediction rules in back pain research: a systematic review.背痛研究中的规范性临床预测规则:一项系统综述。
J Man Manip Ther. 2009;17(1):36-45. doi: 10.1179/106698109790818214.

引用本文的文献

1
Non-invasive breath testing to detect colorectal cancer: protocol for a multicentre, case-control development and validation study (COBRA2 study).用于检测结直肠癌的非侵入性呼气测试:一项多中心病例对照研究的开发与验证方案(COBRA2研究)
BMC Cancer. 2025 Jul 29;25(1):1230. doi: 10.1186/s12885-025-14520-2.
2
Development and validation of prediction models for diabetic retinopathy in type 2 diabetes patients.2型糖尿病患者糖尿病视网膜病变预测模型的开发与验证
PLoS One. 2025 Jul 10;20(7):e0325814. doi: 10.1371/journal.pone.0325814. eCollection 2025.
3
Number of Publications on New Clinical Prediction Models: A Bibliometric Review.

本文引用的文献

1
Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness.机器学习和人工智能研究如何造福患者:透明度、可重复性、伦理和有效性方面的 20 个关键问题。
BMJ. 2020 Mar 20;368:l6927. doi: 10.1136/bmj.l6927.
2
Impact of predictor measurement heterogeneity across settings on the performance of prediction models: A measurement error perspective.预测指标在不同环境下的变异性对预测模型性能的影响:测量误差的角度。
Stat Med. 2019 Aug 15;38(18):3444-3459. doi: 10.1002/sim.8183. Epub 2019 May 31.
3
Quantifying the added value of new biomarkers: how and how not.
关于新临床预测模型的出版物数量:一项文献计量学综述。
JMIR Med Inform. 2025 Jul 4;13:e62710. doi: 10.2196/62710.
4
Evaluation of changes in prediction modelling in biomedicine using systematic reviews.使用系统评价评估生物医学中预测模型的变化
BMC Med Res Methodol. 2025 Jul 1;25(1):167. doi: 10.1186/s12874-025-02605-2.
5
Validation of Rapid Rule-Out Criteria Using the Beckman Access hsTnI Assay for Patients With Suspected Myocardial Infarction in a Cardiac Emergency Department.在心脏急诊科使用贝克曼Access hsTnI检测法对疑似心肌梗死患者进行快速排除标准的验证
Emerg Med Australas. 2025 Jun;37(3):e70085. doi: 10.1111/1742-6723.70085.
6
Heterogeneity in mortality risk prediction: a study of vulnerable adults in the Canadian longitudinal study on aging.死亡率风险预测中的异质性:加拿大老龄化纵向研究中弱势成年人的研究
Aging Clin Exp Res. 2025 May 26;37(1):165. doi: 10.1007/s40520-025-03063-y.
7
Comparing the predictive discrimination of machine learning models for ordinal outcomes: A case study of dehydration prediction in patients with acute diarrhea.比较机器学习模型对有序结果的预测辨别力:急性腹泻患者脱水预测的案例研究。
PLOS Digit Health. 2025 May 6;4(5):e0000820. doi: 10.1371/journal.pdig.0000820. eCollection 2025 May.
8
A Blueprint for Clinical-Driven Medical Device Development: The Feverkidstool Application to Identify Children With Serious Bacterial Infection.临床驱动的医疗设备开发蓝图:用于识别严重细菌感染儿童的Feverkidstool应用程序
Mayo Clin Proc Digit Health. 2024 Oct 30;2(4):656-664. doi: 10.1016/j.mcpdig.2024.10.003. eCollection 2024 Dec.
9
The revised Canadian Bleeding (CAN-BLEED) score for risk stratification of bleeding trauma patients: a mixed retrospective-prospective cohort study.用于创伤出血患者风险分层的修订版加拿大出血(CAN-BLEED)评分:一项回顾性与前瞻性相结合的队列研究。
Scand J Trauma Resusc Emerg Med. 2025 Feb 20;33(1):31. doi: 10.1186/s13049-025-01336-z.
10
Identifying children who develop severe chronic kidney disease using primary care records.利用初级保健记录识别患有严重慢性肾病的儿童。
PLoS One. 2025 Feb 10;20(2):e0314084. doi: 10.1371/journal.pone.0314084. eCollection 2025.
量化新生物标志物的附加价值:方法与误区
Diagn Progn Res. 2018 Jul 11;2:14. doi: 10.1186/s41512-018-0037-2. eCollection 2018.
4
Evaluating the impact of prediction models: lessons learned, challenges, and recommendations.评估预测模型的影响:经验教训、挑战及建议。
Diagn Progn Res. 2018 Jun 12;2:11. doi: 10.1186/s41512-018-0033-6. eCollection 2018.
5
Predictors for independent external validation of cardiovascular risk clinical prediction rules: Cox proportional hazards regression analyses.心血管疾病风险临床预测规则独立外部验证的预测因素:Cox比例风险回归分析。
Diagn Progn Res. 2018 Feb 6;2:3. doi: 10.1186/s41512-018-0025-6. eCollection 2018.
6
The effects of misclassification in routine healthcare databases on the accuracy of prognostic prediction models: a case study of the CHA2DS2-VASc score in atrial fibrillation.常规医疗保健数据库中的错误分类对预后预测模型准确性的影响:以心房颤动的CHA2DS2-VASc评分为例的案例研究
Diagn Progn Res. 2017 Nov 16;1:18. doi: 10.1186/s41512-017-0018-x. eCollection 2017.
7
Systematic review of the effects of care provided with and without diagnostic clinical prediction rules.对有无诊断性临床预测规则的护理效果的系统评价。
Diagn Progn Res. 2017 Apr 26;1:13. doi: 10.1186/s41512-017-0013-2. eCollection 2017.
8
High-performance medicine: the convergence of human and artificial intelligence.高性能医学:人机智能融合。
Nat Med. 2019 Jan;25(1):44-56. doi: 10.1038/s41591-018-0300-7. Epub 2019 Jan 7.
9
PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration.PROBAST:一种用于评估偏倚风险和预测模型研究适用性的工具:说明和阐述。
Ann Intern Med. 2019 Jan 1;170(1):W1-W33. doi: 10.7326/M18-1377.
10
Potential impact of the validated Predicting Abusive Head Trauma (PredAHT) clinical prediction tool: A clinical vignette study.验证性预测虐待性头部创伤(PredAHT)临床预测工具的潜在影响:临床病例研究。
Child Abuse Negl. 2018 Dec;86:184-196. doi: 10.1016/j.chiabu.2018.09.017. Epub 2018 Oct 9.