Collider bias undermines our understanding of COVID-19 disease risk and severity.
Collider bias undermines our understanding of COVID-19 disease risk and severity.
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DOI：
10.1038/s41467-020-19478-2
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发表时间：
2020-11-12
影响因子：
16.6
通讯作者：
Hemani G
中科院分区：
文献类型：
--
作者：
Griffith GJ;Morris TT;Tudball MJ;Herbert A;Mancano G;Pike L;Sharp GC;Sterne J;Palmer TM;Davey Smith G;Tilling K;Zuccolo L;Davies NM;Hemani G
许多观察性研究试图确定SARS-CoV-2感染和COVID-19疾病结局的风险因素。研究使用的数据集来自住院患者、活动性感染检测人员或自愿参与的人员。在这里，我们强调了解释来自这种非代表性样本的观测证据的挑战。对撞机偏差可以诱导两个或多个变量之间的关联，这些变量影响个体被采样的可能性，扭曲样本中这些变量之间的关联。通过分析英国生物银行的数据，与更广泛的队列相比，接受COVID-19检测的参与者在一系列遗传、行为、心血管、人口统计学和人体测量学特征方面都得到了高度选择。我们讨论了诱发这些问题的机制，以及有助于缓解这些问题的方法。虽然在现有的研究中应该探讨碰撞机偏差，但缓解问题的最佳方法是在研究设计阶段使用适当的抽样策略。许多已发表的关于当前SARS-CoV-2大流行的研究分析了来自人群的非代表性样本的数据。在这里，使用英国生物银行的样本，Gibran Hemani和他的同事讨论了这些研究遭受对撞机偏见的可能性，并提供了优化研究设计的建议。
Numerous observational studies have attempted to identify risk factors for infection with SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from patients admitted to hospital, people tested for active infection, or people who volunteered to participate. Here, we highlight the challenge of interpreting observational evidence from such non-representative samples. Collider bias can induce associations between two or more variables which affect the likelihood of an individual being sampled, distorting associations between these variables in the sample. Analysing UK Biobank data, compared to the wider cohort the participants tested for COVID-19 were highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the mechanisms inducing these problems, and approaches that could help mitigate them. While collider bias should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage. Many published studies of the current SARS-CoV-2 pandemic have analysed data from non-representative samples from populations. Here, using UK BioBank samples, Gibran Hemani and colleagues discuss the potential for such studies to suffer from collider bias, and provide suggestions for optimising study design to account for this.
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影响因子：
64.8
作者：
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
通讯作者：
Marchini J
DOI：
10.1097/ede.0000000000000504
发表时间：
2016-09
期刊：
Epidemiology (Cambridge, Mass.)
影响因子：
--
作者：
Arnold BF;Ercumen A;Benjamin-Chung J;Colford JM Jr
通讯作者：
Colford JM Jr
影响因子：
2
作者：
Changeux, Jean-Pierre;Amoura, Zahir;Miyara, Makoto
通讯作者：
Miyara, Makoto
影响因子：
2.7
作者：
Aronow, Peter M.;Lee, Donald K. K.
通讯作者：
Lee, Donald K. K.
影响因子：
7.7
作者：
Cole, Stephen R.;Platt, Robert W.;Poole, Charles
通讯作者：
Poole, Charles