For Personal Use. Only Reproduce with Permission from the Lancet Publishing Group. Exclusions before Randomisation Exclusions after Randomisation Sample Size Slippages in Randomised Trials: Exclusions and the Lost and Wayward
For Personal Use. Only Reproduce with Permission from the Lancet Publishing Group. Exclusions before Randomisation Exclusions after Randomisation Sample Size Slippages in Randomised Trials: Exclusions and the Lost and Wayward
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D. Grimes
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作者：
K. F. Schulz;F. Kenneth;Schulz;K. F. Schulz;D. Grimes
781如果研究者不能将所有随机分配的参与者纳入其主要分析，则适当的随机化1，2意义不大。因此，评估随机对照试验的一个关键方面涉及排除、退出、损失和方案偏离。研究者应该如何处理拒绝进入、忽视随访、离开城镇或在被要求服用阿司匹林时服用阿司匹林的受试者？不幸的是，许多处理这类问题的不恰当方法实际上看起来是合乎逻辑的，并且错误地吸引人。这就是它们阴险的本质，因为这种不适当的方法可能导致严重的偏见。在这里，我们讨论了随机化前后排除的影响。研究者可以在随机化前排除受试者。最终的随机治疗比较将保持无偏（良好的内部效度），无论研究人员是否有充分的理由或异想天开的理由排除特定的个体。然而，在这个阶段排除可能会损害外推，结果的普遍性（外部效度）。因此，对于大多数研究，我们建议本着大型和简单试验的精神，将合格标准保持在最低限度。3，4然而，存在一些排除某些参与者的正当理由。例如，个人可能有一种干预是禁忌的情况，或者他们可能被判断为可能失去随访。审判问题应指导方法。[5]然而，有时候，研究者强加了太多的资格标准，以至于他们的试验推断出的人群对任何人都没有明显的兴趣，此外，招募也变得困难。如果研究者排除了太多的参与者，或者排除了错误的参与者，那么他们的结果可能并不代表感兴趣的人，即使随机对照试验可能已经被仔细地完成了，也就是说，结果可能是真实的，但可能无关紧要。在随机化之前排除的标准应该指出研究者希望推断的人群。在判断试验结果时，读者应确保合格标准明确而具体。最重要的是，应在随机化前应用标准。读者还应该评估是否有任何标准使研究样本非典型，不具代表性或与感兴趣的人无关。然而，在实践中，试验的结果很少是完全不相关的："我们的患者和试验中的患者之间的大多数差异往往是定量的（他们有不同的年龄或社会阶层，或者结局事件的风险程度或对治疗的反应程度不同），而不是......
781 Proper randomisation 1,2 means little if investigators cannot include all randomly assigned participants in their primary analysis. Hence, a crucial aspect of assessing a randomised controlled trial pertains to exclusions, withdrawals, losses, and protocol deviations. How should investigators handle participants who refuse entry, ignore follow-up, leave town, or take aspartame when they were instructed to take aspirin? Unfortunately, many inappropriate approaches to dealing with these types of problem actually seem logical and falsely appealing. Therein lies their insidious nature, because such inappropriate approaches can result in serious biases. Here, we address the effect of exclusions made before and after randomisation. Investigators can exclude participants before randomisation. The eventual randomised treatment comparison will remain unbiased (good internal validity), irrespective of whether researchers have well-founded or whimsical reasons for exclusion of particular individuals. However, exclusions at this stage can hurt extrapolation, the generalisability, of the results (external validity). For most investigations, we therefore recommend that eligibility criteria be kept to a minimum, in the spirit of the large and simple trial. 3,4 However, some valid reasons exist for exclusion of certain participants. Individuals could, for example, have a condition for which an intervention is contraindicated, or they could be judged likely to be lost to follow-up. The trial question should guide the approach. 5 Sometimes, however, investigators impose so many eligibility criteria that their trial infers to a population of little apparent interest to anyone, and, in addition, recruitment becomes difficult. If investigators exclude too many participants, or the wrong participants, their results might not represent the people of interest, even though the randomised controlled trial might have been meticulously done—ie, the results could be true but potentially irrelevant. What to look for in exclusions before randomisation The eligibility criteria should indicate the population to which the investigators wish to infer. When judging the results of a trial, readers should make sure that the eligibility criteria are clear and specific. Most importantly, the criteria should have been applied before random-isation. Readers should also assess whether any of the criteria make the study sample atypical, unrepresentative, or irrelevant to the people of interest. In practice, however, results from a trial will infrequently be totally irrelevant: " most differences between our patients and those in trials tend to be quantitative (they have different ages or social classes or different degrees of risk of the outcome event or of responsiveness to therapy) rather than …