Method - Analysis

方法-分析

• 批准号: MC_UU_00004/07
• 负责人: James Carpenter
• 金额: $ 301.86万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MC_UU_00004%2F07
• 关键词: Method; Analysis

Appropriate statistical analysis of trial data is key for their correct interpretation. The analysis programme develops and disseminates practical solutions to analysis challenges, principally: • missing data on patients’ outcomes (ubiquitous, and aggravated by the current pandemic). We continue to address the challenge of how to make accessible, defensible, assumptions about missing patient outcome data, and how to correctly incorporate these in the trial’s interpretation. • ensuring trials meet their objectives, by thinking carefully about the (i) patient population, (i) outcomes and how they will be measured, and (iii) how to take account of unplanned developments once patients are enrolled in a study (such as inability to tolerate treatment, or switching to another treatment). These issues are particularly important for the Unit’s tuberculosis and cancer trials. • using computer simulation to effectively understand how useful proposed trials are likely to be, and in particular how resilient to a range of scenarios that may unfold as the trial progresses• collaborating with the Alan Turing Institute to exploit recent advances in machine learning to identify subgroups of patients who may particularly benefit from certain treatments.

对试验数据进行适当的统计分析是正确解读的关键。该分析方案制定并传播了针对分析挑战的实用解决方案，主要是：·关于患者结局的缺失数据（普遍存在，并因当前的大流行而加剧）。我们将继续解决如何对缺失的患者结局数据做出可访问的、可辩护的假设，以及如何将这些假设正确地纳入试验解释的挑战。·确保试验达到其目标，仔细考虑（i）患者人群，（i）结果及其测量方法，以及（iii）一旦患者入组研究，如何考虑计划外的发展（例如无法耐受治疗或改用另一种治疗）。这些问题对该股的结核病和癌症试验特别重要。·使用计算机模拟来有效地了解拟议的试验可能有多有用，特别是随着试验的进展，对可能出现的一系列场景的适应能力如何·与艾伦·图灵研究所合作，利用机器学习的最新进展来识别可能特别受益于某些治疗的患者亚组。

项目成果

The complexity underlying treatment rankings: how to use them and what to look at.

• DOI: 10.1136/bmjebm-2021-111904
• 发表时间: 2023-06
• 期刊: BMJ evidence-based medicine
• 影响因子: 5.8
• 作者: Chiocchia V;White IR;Salanti G
• 通讯作者: Salanti G

Access to unpublished protocols and statistical analysis plans of randomised trials.

• DOI: 10.1186/s13063-022-06641-x
• 发表时间: 2022-08-17
• 期刊: Trials
• 影响因子: 2.5

Multiple Imputation and its Application 2e

多重插补及其应用2e

• DOI: 10.1002/9781119756118
• 发表时间: 2023
• 作者: Carpenter J

MSR9 Adjusting for Switches to Multiple Treatments in Randomised Controlled Trials: A Comparison of Inverse Probability Weighting and Two-Stage Estimation Methods

MSR9 在随机对照试验中调整多种治疗的切换：逆概率加权和两阶段估计方法的比较

• DOI: 10.1016/j.jval.2023.09.2068
• 发表时间: 2023
• 期刊: Value in Health
• 影响因子: 4.5
• 作者: Bell Gorrod H

Current Practices in Missing Data Handling for Interrupted Time Series Studies Performed on Individual-Level Data: A Scoping Review in Health Research.

• DOI: 10.2147/clep.s314020
• 发表时间: 2021
• 期刊: Clinical epidemiology
• 影响因子: 3.9
• 作者: Bazo-Alvarez JC;Morris TP;Carpenter JR;Petersen I
• 通讯作者: Petersen I