Prowse Sarah R, Treweek Shaun, Brazzelli Miriam, Bruhn Hanne
Aberdeen Centre for Evaluation, University of Aberdeen, Aberdeen, UK.
J Eval Clin Pract. 2025 Jun;31(4):e70147. doi: 10.1111/jep.70147.
Randomised controlled trials are considered the 'gold standard' in clinical research and decision-making. However, many trials have significant flaws that current review processes fail to identify early enough for corrections to be made. Flaws in trial design, conduct and reporting ultimately lead to research waste. This rapid review provides insights from global research aimed at improving trial 'informativeness' as described by Zarin and colleagues.
A rapid review was conducted with a focus on research addressing trial design processes that might improve informativeness aligned with one or more of the five key conditions outlined by Zarin and colleagues: 1) Importance, 2) Design, 3) Feasibility, 4) Integrity and 5) Reporting. A further thematic analysis was conducted using NVivo 12.
The final review includes 42 texts. Of the 27 recommended processes or actions to improve trial informativeness, most were relevant to the second condition of trial design (2) Design; 44%). A key recommendation was the use of 'tools' to enhance trial informativeness. A total of 23 tools were identified across the conditions of 1) Importance (17%), 2) Design (74%) and 5) Reporting (9%).
This review highlights how a better understanding of design processes that lead to informative trials can reduce or eliminate research waste. Further research is needed on how these processes can better support pre-funding peer review, which would also increase the likelihood of producing informative trials.
随机对照试验被认为是临床研究和决策中的“黄金标准”。然而,许多试验存在重大缺陷,当前的审查流程未能足够早地识别这些缺陷以便进行纠正。试验设计、实施和报告中的缺陷最终会导致研究资源的浪费。本快速综述提供了来自全球研究的见解,旨在提高扎林及其同事所描述的试验“信息量”。
进行了一项快速综述,重点关注针对可能提高信息量的试验设计流程的研究,这些流程与扎林及其同事概述的五个关键条件中的一个或多个条件相符:1)重要性,2)设计,3)可行性,4)完整性,5)报告。使用NVivo 12进行了进一步的主题分析。
最终综述纳入了42篇文献。在27项推荐的提高试验信息量的流程或行动中,大多数与试验设计的第二个条件(2)设计;44%)相关。一项关键建议是使用“工具”来提高试验信息量。在1)重要性(17%)、2)设计(74%)和5)报告(9%)的条件下共识别出23种工具。
本综述强调了更好地理解导致信息量丰富的试验的设计流程如何能够减少或消除研究浪费。需要进一步研究这些流程如何能够更好地支持资助前同行评审,这也将增加产生信息量丰富的试验的可能性。