A roadmap to using randomization in clinical trials.
A roadmap to using randomization in clinical trials.
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DOI：
10.1186/s12874-021-01303-z
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发表时间：
2021-08-16
影响因子：
4
通讯作者：
Randomization Innovative Design Scientific Working Group
中科院分区：
文献类型：
--
作者：
Berger VW;Bour LJ;Carter K;Chipman JJ;Everett CC;Heussen N;Hewitt C;Hilgers RD;Luo YA;Renteria J;Ryeznik Y;Sverdlov O;Uschner D;Randomization Innovative Design Scientific Working Group
随机化是任何涉及治疗比较的临床试验的基础。它有助于减轻选择偏差，促进治疗组在重要的已知和未知混杂因素方面的相似性，并有助于统计测试的有效性。具有不同概率结构和不同统计特性的各种受限随机化过程是可用的。本文的目的是为临床试验中限制随机化程序的选择和应用提供系统的路线图。我们在一项随机、比较、平行组临床试验中调查了可用的限制性随机化程序，以进行平等（1:1）分配的受试者顺序分配。我们探索这些过程的统计特性，包括平衡/随机性权衡、I 类错误率和功效。我们通过在各种实验场景下进行模拟，对不同程序进行头对头的比较，包括违反常见模型假设的情况。我们还提供了一些现实生活中的临床试验示例，以说明选择在实践中实施的随机化程序的思维过程。针对 1:1 分配的受限随机化程序在其引起的平衡/随机性程度方面有所不同，更重要的是，当违反常见模型假设时（例如，当结果受到线性时间趋势的影响；测量误差分布被错误指定；或在实验中引入选择偏差时），它们在统计推断的有效性和效率方面有所不同。有些程序比其他程序更稳健。协变量调整分析对于确保结果的有效性可能至关重要。在为样本量非常小的临床试验选择随机化程序时，需要特别考虑。随机化设计、数据分析技术（参数或非参数）和分析策略（基于随机化或基于总体模型）的选择都是非常重要的考虑因素。基于随机化的测试是基于可能性的测试的稳健且有效的替代方案，临床研究人员应该更频繁地考虑。在线版本包含可在 10.1186/s12874-021-01303-z 获取的补充材料。
Randomization is the foundation of any clinical trial involving treatment comparison. It helps mitigate selection bias, promotes similarity of treatment groups with respect to important known and unknown confounders, and contributes to the validity of statistical tests. Various restricted randomization procedures with different probabilistic structures and different statistical properties are available. The goal of this paper is to present a systematic roadmap for the choice and application of a restricted randomization procedure in a clinical trial. We survey available restricted randomization procedures for sequential allocation of subjects in a randomized, comparative, parallel group clinical trial with equal (1:1) allocation. We explore statistical properties of these procedures, including balance/randomness tradeoff, type I error rate and power. We perform head-to-head comparisons of different procedures through simulation under various experimental scenarios, including cases when common model assumptions are violated. We also provide some real-life clinical trial examples to illustrate the thinking process for selecting a randomization procedure for implementation in practice. Restricted randomization procedures targeting 1:1 allocation vary in the degree of balance/randomness they induce, and more importantly, they vary in terms of validity and efficiency of statistical inference when common model assumptions are violated (e.g. when outcomes are affected by a linear time trend; measurement error distribution is misspecified; or selection bias is introduced in the experiment). Some procedures are more robust than others. Covariate-adjusted analysis may be essential to ensure validity of the results. Special considerations are required when selecting a randomization procedure for a clinical trial with very small sample size. The choice of randomization design, data analytic technique (parametric or nonparametric), and analysis strategy (randomization-based or population model-based) are all very important considerations. Randomization-based tests are robust and valid alternatives to likelihood-based tests and should be considered more frequently by clinical investigators. The online version contains supplementary material available at 10.1186/s12874-021-01303-z.
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影响因子：
2
作者：
ALTMAN, DG;ROYSTON, JP
通讯作者：
ROYSTON, JP
DOI：
10.1177/1740774515621721
发表时间：
2016-02
期刊：
Clinical trials (London, England)
影响因子：
--
作者：
Berry SM;Petzold EA;Dull P;Thielman NM;Cunningham CK;Corey GR;McClain MT;Hoover DL;Russell J;Griffiss JM;Woods CW
通讯作者：
Woods CW
DOI：
10.1111/j.1467-9876.2004.00436.x
发表时间：
2004-01-01
影响因子：
1.6
作者：
Antognini, AB;Giovagnoli, A
通讯作者：
Giovagnoli, A
影响因子：
5.7
作者：
Atkinson, Anthony C.
通讯作者：
Atkinson, Anthony C.
影响因子：
2.7
作者：
ATKINSON, AC
通讯作者：
ATKINSON, AC