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使用试验序贯分析估算进一步试验的样本量:使用戒烟干预的示例。

Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation intervention.

机构信息

Division of Primary Care, University of Nottingham, Nottingham, NG7 2RD, UK.

Copenhagen Trial Unit, Centre for Clinical Intervention Research, Department 7812, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.

出版信息

BMC Med Res Methodol. 2020 Nov 30;20(1):284. doi: 10.1186/s12874-020-01169-7.

Abstract

BACKGROUND

Assessing benefits and harms of health interventions is resource-intensive and often requires feasibility and pilot trials followed by adequately powered randomised clinical trials. Data from feasibility and pilot trials are used to inform the design and sample size of the adequately powered randomised clinical trials. When a randomised clinical trial is conducted, results from feasibility and pilot trials may be disregarded in terms of benefits and harms.

METHODS

We describe using feasibility and pilot trial data in the Trial Sequential Analysis software to estimate the required sample size for one or more trials investigating a behavioural smoking cessation intervention. We show how data from a new, planned trial can be combined with data from the earlier trials using trial sequential analysis methods to assess the intervention's effects.

RESULTS

We provide a worked example to illustrate how we successfully used the Trial Sequential Analysis software to arrive at a sensible sample size for a new randomised clinical trial and use it in the argumentation for research funds for the trial.

CONCLUSIONS

Trial Sequential Analysis can utilise data from feasibility and pilot trials as well as other trials, to estimate a sample size for one or more, similarly designed, future randomised clinical trials. As this method uses available data, estimated sample sizes may be smaller than they would have been using conventional sample size estimation methods.

摘要

背景

评估卫生干预措施的效益和危害需要耗费大量资源,通常需要进行可行性和初步试验,然后再进行充分有力的随机临床试验。可行性和初步试验的数据用于为充分有力的随机临床试验的设计和样本量提供信息。当进行随机临床试验时,可能会忽略可行性和初步试验中关于效益和危害的数据。

方法

我们描述了如何在 Trial Sequential Analysis 软件中使用可行性和初步试验数据来估计一项或多项行为戒烟干预措施研究所需的样本量。我们展示了如何使用 Trial Sequential Analysis 方法结合新计划试验的数据和早期试验的数据,来评估干预措施的效果。

结果

我们提供了一个实例来说明如何成功地使用 Trial Sequential Analysis 软件为新的随机临床试验确定合理的样本量,并在为该试验申请研究资金的论证中使用该样本量。

结论

Trial Sequential Analysis 可以利用可行性和初步试验以及其他试验的数据,来估计一个或多个类似设计的未来随机临床试验的样本量。由于该方法使用了可用的数据,因此估计的样本量可能比使用传统的样本量估计方法小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ee2/7702700/d821e856630e/12874_2020_1169_Fig1_HTML.jpg

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