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随机对照试验。

Randomized Controlled Trials.

机构信息

Department of Quantitative Health Sciences & Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH.

Department of Quantitative Health Sciences & Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH.

出版信息

Chest. 2020 Jul;158(1S):S79-S87. doi: 10.1016/j.chest.2020.03.013.

Abstract

Randomized controlled trials (RCTs) are considered the highest level of evidence to establish causal associations in clinical research. There are many RCT designs and features that can be selected to address a research hypothesis. Designs of RCTs have become increasingly diverse as new methods have been proposed to evaluate increasingly complex scientific hypotheses. This article reviews the principles and general concepts behind many common RCT designs and introduces newer designs that have been proposed, such as adaptive and cluster randomized trials. A focus on the many choices for randomization within an RCT is described, along with their potential tradeoffs. To illustrate their diversity, examples of RCTs from the literature are provided. Statistical considerations, such as power and type I error rates, are discussed with the intention of providing practical guidance about how to specify study hypotheses that address the scientific question while being statistically appropriate. Finally, the freely available Consolidated Standards of Reporting Trials guidelines and US Food and Drug Administration guidance documents are introduced, along with a set of guidelines one should consider when planning an RCT or reviewing RCTs submitted for publication in peer-reviewed academic journals.

摘要

随机对照试验(RCTs)被认为是在临床研究中建立因果关系的最高证据级别。有许多 RCT 设计和特征可供选择,以解决研究假设。随着新方法被提出以评估越来越复杂的科学假设,RCT 的设计变得越来越多样化。本文回顾了许多常见 RCT 设计背后的原则和一般概念,并介绍了一些新提出的设计,如适应性和聚类随机试验。重点介绍了 RCT 中随机化的许多选择,以及它们的潜在权衡。为了说明它们的多样性,提供了来自文献的 RCT 示例。讨论了统计考虑因素,如功效和 I 类错误率,旨在提供关于如何指定研究假设的实用指导,这些假设在解决科学问题的同时在统计学上是恰当的。最后,介绍了可用的统一报告试验标准和美国食品和药物管理局指导文件,以及在计划 RCT 或审查提交给同行评议学术期刊发表的 RCT 时应考虑的一组指南。

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