Analysis of Stepped-Wedge Cluster Randomized Trials When Treatment Effects Vary by Exposure Time or Calendar Time.

IF 1.8 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Kenneth M Lee, Elizabeth L Turner, Avi Kenny
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Abstract

Stepped-wedge cluster randomized trials (SW-CRTs) are traditionally analyzed with models that assume an immediate and sustained treatment effect. Previous work has shown that making such an assumption in the analysis of SW-CRTs when the true underlying treatment effect varies by exposure time can produce severely misleading estimates. Alternatively, the true underlying treatment effect might vary by calendar time. Comparatively less work has examined treatment effect structure misspecification in this setting. Here, we evaluate the behavior of the linear mixed effects model-based immediate treatment effect, exposure time-averaged treatment effect, and calendar time-averaged treatment effect estimators in different scenarios where these estimators are misspecified for the true underlying treatment effect structure. We show that the immediate treatment effect estimator is relatively robust to bias when estimating a true underlying calendar time-averaged treatment effect estimand. However, when there is a true underlying calendar (exposure) time-varying treatment effect, misspecifying an analysis with an exposure (calendar) time-averaged treatment effect estimator can yield severely misleading estimates which may converge to a value with the opposite sign of the true calendar (exposure) time-averaged treatment effect estimand. In this article, we highlight these two different time scales on which treatment effects can vary in SW-CRTs and clarify potential vulnerabilities that may arise when considering different types of time-varying treatment effects in a SW design. Accordingly, we emphasize the need for researchers to carefully consider whether the treatment effect may vary as a function of exposure time or calendar time in the analysis of SW-CRTs.

治疗效果随暴露时间或日历时间变化的楔形聚类随机试验分析。
楔形聚类随机试验(sw - crt)传统上采用假设立即和持续治疗效果的模型进行分析。先前的研究表明,当真正的潜在治疗效果随暴露时间而变化时,在sw - crt分析中做出这样的假设可能会产生严重的误导性估计。或者,真正的潜在治疗效果可能因日历时间而异。在这种情况下,研究治疗效果结构错误的工作相对较少。在这里,我们评估了基于线性混合效应模型的即时治疗效应、暴露时间平均治疗效应和日历时间平均治疗效应估计器在不同情况下的行为,这些估计器被错误地指定为真实的潜在治疗效应结构。我们表明,当估计真实的潜在日历时间平均治疗效果估计时,即时治疗效果估计器对偏差相对稳健。然而,当存在真实的潜在日历(暴露)时变治疗效果时,错误地指定使用暴露(日历)时间平均治疗效果估计器的分析可能会产生严重误导的估计,这些估计可能收敛到与真实日历(暴露)时间平均治疗效果估计相反的值。在本文中,我们强调了SW- crt中治疗效果变化的两种不同的时间尺度,并阐明了在SW设计中考虑不同类型的时变治疗效果时可能出现的潜在漏洞。因此,我们强调研究人员需要仔细考虑在sw - crt分析中,治疗效果是否会随着暴露时间或日历时间的变化而变化。
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来源期刊
Statistics in Medicine
Statistics in Medicine 医学-公共卫生、环境卫生与职业卫生
CiteScore
3.40
自引率
10.00%
发文量
334
审稿时长
2-4 weeks
期刊介绍: The journal aims to influence practice in medicine and its associated sciences through the publication of papers on statistical and other quantitative methods. Papers will explain new methods and demonstrate their application, preferably through a substantive, real, motivating example or a comprehensive evaluation based on an illustrative example. Alternatively, papers will report on case-studies where creative use or technical generalizations of established methodology is directed towards a substantive application. Reviews of, and tutorials on, general topics relevant to the application of statistics to medicine will also be published. The main criteria for publication are appropriateness of the statistical methods to a particular medical problem and clarity of exposition. Papers with primarily mathematical content will be excluded. The journal aims to enhance communication between statisticians, clinicians and medical researchers.
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