Feasibility studies and external pilot studies are used increasingly to inform planning decisions related to a definitive randomized controlled trial. These studies can provide information on process measures, such as consent rates, treatment fidelity and compliance, and methods of outcome measurement. Additionally, they can provide initial parameter estimates for a sample size calculation, such as a standard deviation or the ‘success’ rate for a binary outcome in the control group. However, the issue of estimating treatment effects in pilot or feasibility studies is controversial. Between-group estimates of treatment effect from pilot studies are sometimes used to calculate the sample size for a main trial, alongside estimated standard deviations. However, whilst estimating a standard deviation is an empirical matter, a targeted treatment effect should be established in terms of clinical judgement, as a minimum important difference (MID), not through analysis of pilot data. Secondly, between-group effects measured in pilot studies are sometimes used to indicate the magnitude of an effect that might be obtained in a main trial, and a decision on progression made with reference to the associated confidence interval. Such estimates will be imprecise in typically small pilot studies and therefore do not allow a robust decision on a main trial; both a decision to proceed and a decision not to proceed may be made too readily. Thirdly, a within-group change might be estimated from a pilot or a feasibility study in a desire to assess the potential efficacy of a novel intervention prior to testing it in a main trial, but again such estimates are liable to be imprecise and do not allow sound causal inferences. Treatment effects calculated from pilot or feasibility studies should not be the basis of a sample size calculation for a main trial, as the MID to be detected should be based primarily on clinical judgement rather than statistics. Deciding on progression to a main trial based on these treatment effects is also misguided, as they will normally be imprecise, and may be biased if the pilot or feasibility study is unrepresentative of the main trial.

中文翻译：

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是否应该在试点和可行性研究中估计治疗效果？

可行性研究和外部试点研究越来越多地用于为与最终随机对照试验相关的规划决策提供信息。这些研究可以提供有关过程测量的信息，例如同意率、治疗保真度和依从性以及结果测量方法。此外，他们可以为样本量计算提供初始参数估计，例如标准偏差或对照组中二元结果的“成功”率。然而，在试点或可行性研究中估计治疗效果的问题是有争议的。来自试点研究的治疗效果的组间估计有时用于计算主要试验的样本量，以及估计的标准偏差。然而，虽然估计标准偏差是一个经验问题，应根据临床判断确定靶向治疗效果，作为最小重要差异（MID），而不是通过对试验数据的分析。其次，在试点研究中测量的组间效应有时用于指示可能在主要试验中获得的效应的大小，以及参考相关置信区间做出的进展决定。这种估计在典型的小型试点研究中是不精确的，因此不允许对主要试验做出稳健的决定；决定继续进行和不继续进行的决定都可能太容易做出。第三，可以从试点或可行性研究中估计组内变化，以便在主要试验中测试之前评估新干预的潜在功效，但同样，这样的估计可能是不精确的，并且不允许进行合理的因果推论。从试点或可行性研究计算的治疗效果不应作为主要试验样本量计算的基础，因为要检测的 MID 应主要基于临床判断而不是统计数据。根据这些治疗效果决定是否进展到主要试验也是错误的，因为它们通常是不精确的，并且如果试点或可行性研究不能代表主要试验，则可能存在偏差。