a London School of Economics ; University College London , London , UK.
Ann Med. 2018 Jun;50(4):312-322. doi: 10.1080/07853890.2018.1453233. Epub 2018 Apr 4.
Randomised controlled trials (RCTs) are commonly viewed as the best research method to inform public health and social policy. Usually they are thought of as providing the most rigorous evidence of a treatment's effectiveness without strong assumptions, biases and limitations.
This is the first study to examine that hypothesis by assessing the 10 most cited RCT studies worldwide.
These 10 RCT studies with the highest number of citations in any journal (up to June 2016) were identified by searching Scopus (the largest database of peer-reviewed journals).
This study shows that these world-leading RCTs that have influenced policy produce biased results by illustrating that participants' background traits that affect outcomes are often poorly distributed between trial groups, that the trials often neglect alternative factors contributing to their main reported outcome and, among many other issues, that the trials are often only partially blinded or unblinded. The study here also identifies a number of novel and important assumptions, biases and limitations not yet thoroughly discussed in existing studies that arise when designing, implementing and analysing trials.
Researchers and policymakers need to become better aware of the broader set of assumptions, biases and limitations in trials. Journals need to also begin requiring researchers to outline them in their studies. We need to furthermore better use RCTs together with other research methods. Key messages RCTs face a range of strong assumptions, biases and limitations that have not yet all been thoroughly discussed in the literature. This study assesses the 10 most cited RCTs worldwide and shows that trials inevitably produce bias. Trials involve complex processes - from randomising, blinding and controlling, to implementing treatments, monitoring participants etc. - that require many decisions and steps at different levels that bring their own assumptions and degree of bias to results.
随机对照试验（RCT）通常被视为为公共卫生和社会政策提供信息的最佳研究方法。通常认为，它们提供了一种治疗效果的最严格证据，而无需进行强有力的假设、偏见和限制。
本研究首次通过评估全球最具影响力的 10 项 RCT 研究来检验这一假设。
通过在 Scopus（最大的同行评审期刊数据库）中搜索，确定了这 10 项引用率最高的 RCT 研究。
本研究表明，这些具有世界影响力的 RCT 研究由于参与者的背景特征会影响结果，而这些特征在试验组之间的分布往往很差，试验往往忽略了对其主要报告结果有影响的其他因素，以及许多其他问题，例如试验通常只有部分或未完全设盲。该研究还确定了在设计、实施和分析试验时出现的一些在现有研究中尚未充分讨论的新的和重要的假设、偏见和局限性。
研究人员和政策制定者需要更好地了解试验中更广泛的假设、偏见和局限性。期刊也需要开始要求研究人员在研究中概述这些内容。我们需要更好地将 RCT 与其他研究方法结合使用。
RCT 面临一系列尚未在文献中充分讨论的强烈假设、偏见和局限性。本研究评估了全球最具影响力的 10 项 RCT，并表明试验不可避免地会产生偏差。试验涉及从随机化、设盲和控制到实施治疗、监测参与者等复杂的过程——这些过程需要在不同层面上做出许多决策和步骤，从而带来自己的假设和程度的偏差。
