Analysis of trials, meta-analyses and observational studies

试验分析、荟萃分析和观察性研究

• 批准号: MC_UU_12023/21
• 负责人: James Carpenter
• 金额: $ 324.41万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MC_UU_12023%2F21
• 关键词: Analysis; trials; meta; analyses; observational

We cover issues such as survival analysis methods that allow for non-proportional hazards in both trials and IPD meta-analyses, modelling of prognostic and predictive factors, and analysis of longitudinal and clustered data. On the application of causal models, CTU trials are a rich resource for evaluating aspects of patient management other than the randomised comparison, such as the impact of second-line or concomitant treatments. Although often left to clinician discretion, the trial will usually collect information on the basis for these decisions. Exploiting such data in a major causal analysis of the DART trial in HIV, we showed that 24-weekly and 12 weekly CD4 monitoring give similar results, and that a single CD4 count at 48 weeks leads to better survival than no CD4 monitoring. Finally, on missing data, even modest amounts of missing data can lead to bias and make study conclusions unreliable and/or imprecise. Some methods to deal with it can lead to further bias or imprecision, yet prevail in many disease areas, and are recommended by some regulators. In collaboration with the London School of Hygiene and Tropical Medicine (LSHTM), we have proposed a new framework for the analysis of clinical trials with missing data, which has been adopted by a Drug Information Association working group and for a pharmaceutical company regulatory submission.

我们涵盖了诸如允许在试验和IPD荟萃分析中允许非比例危害的生存分析方法，预后和预测因素的建模以及纵向和聚类数据的分析。关于因果模型的应用，CTU试验是评估患者管理方面的丰富资源，而不是随机比较（例如二线或伴随治疗的影响）。尽管经常留给临床医生的酌处权，但该试验通常会根据这些决定收集信息。在HIV的DART试验的主要因果分析中利用此类数据，我们表明24周和12个每周的CD4监测给出了相似的结果，并且在48周时的单个CD4计数比没有CD4监测更好。最后，在丢失的数据上，即使是少量丢失的数据也会导致偏见，并使研究结论不可靠和/或不精确。处理它的一些方法可能导致进一步的偏见或不精确，但在许多疾病地区占上风，并且某些监管机构建议使用。与伦敦卫生和热带医学学院（LSHTM）合作，我们提出了一个新的框架，用于分析缺少数据的临床试验，该临床试验已由药物信息协会工作组和制药公司的监管提交采用。

项目成果

Effect of Variable Selection Strategy on the Performance of Prognostic Models When Using Multiple Imputation.

• DOI: 10.1161/circoutcomes.119.005927
• 发表时间: 2019-11
• 期刊: Circulation. Cardiovascular quality and outcomes
• 作者: Austin PC;Lee DS;Ko DT;White IR
• 通讯作者: White IR

rpsftm: An R Package for Rank Preserving Structural Failure Time Models

• DOI: 10.32614/rj-2017-068
• 发表时间: 2017-12-01
• 期刊: R JOURNAL
• 影响因子: 2.1
• 作者: Allison, Annabel;White, Ian R.;Bond, Simon
• 通讯作者: Bond, Simon

Multiple Imputation for Multilevel Data with Continuous and Binary Variables

• DOI: 10.1214/18-sts646
• 发表时间: 2018-05-01
• 期刊: STATISTICAL SCIENCE
• 影响因子: 5.7
• 作者: Audigier, Vincent;White, Ian R.;Resche-Rigon, Matthieu
• 通讯作者: Resche-Rigon, Matthieu

Withholding Primary Pneumocystis Pneumonia Prophylaxis in Virologically Suppressed Patients With Human Immunodeficiency Virus: An Emulation of a Pragmatic Trial in COHERE.

• DOI: 10.1093/cid/ciaa615
• 发表时间: 2021-07-15
• 期刊: Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
• 作者: Atkinson A;Zwahlen M;Barger D;d'Arminio Monforte A;De Wit S;Ghosn J;Girardi E;Svedhem V;Morlat P;Mussini C;Noguera-Julian A;Stephan C;Touloumi G;Kirk O;Mocroft A;Reiss P;Miro JM;Carpenter JR;Furrer H;Opportunistic Infections Project Working Group of the Collaboration of Observational HIV Epidemiological Research Europe (COHERE) in EuroCoord
• 通讯作者: Opportunistic Infections Project Working Group of the Collaboration of Observational HIV Epidemiological Research Europe (COHERE) in EuroCoord

Information anchored reference-based sensitivity analysis for truncated normal data with application to survival analysis

对截断的正常数据进行信息锚定的基于参考的敏感性分析及其在生存分析中的应用

• DOI: 10.1111/stan.12250
• 发表时间: 2021
• 期刊: Statistica Neerlandica
• 影响因子: 1.5
• 作者: Atkinson A