Implications of the choice of method to identify major depressive disorder in large research cohorts

Jorge A. Sanchez-Ruiz , Nicolas A. Nuñez , Gregory D. Jenkins , Brandon J. Coombes , Lauren A. Lepow , Braja Gopal Patra , Ardesheer Talati , Mark Olfson , J. John Mann , Myrna M. Weissman , Jyotishman Pathak , Alexander Charney , Euijung Ryu , Joanna M. Biernacka
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Abstract

Background

Clinical heterogeneity and variations in methods to identify major depressive disorder (MDD) across studies compromise replicability of research findings. This study evaluated potential implications of different MDD case definitions in a large biobank cohort.

Methods

Among Mayo Clinic Biobank participants, MDD was identified using two methods: self-report MDD in a participant questionnaire (PQ-MDD) and MDD ICD codes in the electronic health record (EHR-MDD). We examined agreement between these definitions and evaluated relationships between case agreement and participant characteristics, including MDD polygenic risk scores (PRS). Finally, we evaluated associations between different MDD case/control definitions and participant characteristics known to be related to MDD.

Results

Among 55,656 participants, 23 % were identified as PQ-MDD cases and 17 % as EHR-MDD cases, with 85 % overall agreement (61 % case agreement) between these definitions. Among participants identified as MDD cases by one method, older and male patients, and those with lower measures of morbidity at enrollment, were less likely to be identified as cases by the other method. The strength of the associations between different MDD case/control definitions and participant characteristics varied depending on whether MDD definitions used the same source of information (i.e., EHR-only, self-report only)—resulting in stronger associations—versus different sources of information (i.e., one from EHR, one from self-report)—resulting in weaker associations.

Conclusion

Our results demonstrate how the methods used to identify patients with history of MDD can affect sample characteristics and risk factor associations, highlighting the importance of considering phenotype ascertainment in the interpretation of research results.
在大型研究队列中识别重度抑郁症的方法选择的意义
研究背景:临床异质性和不同研究中识别重度抑郁症(MDD)方法的差异影响了研究结果的可重复性。本研究在一个大型生物库队列中评估了不同MDD病例定义的潜在含义。方法在Mayo Clinic Biobank的参与者中,使用两种方法来识别MDD:参与者问卷中的自我报告MDD (PQ-MDD)和电子健康记录中的MDD ICD代码(EHR-MDD)。我们检查了这些定义之间的一致性,并评估了病例一致性与参与者特征之间的关系,包括MDD多基因风险评分(PRS)。最后,我们评估了不同MDD病例/对照定义和已知与MDD相关的参与者特征之间的关联。结果在55,656名参与者中,23 %被确定为PQ-MDD病例,17 %被确定为EHR-MDD病例,这些定义之间的总体一致性为85 %(61 %)。在通过一种方法确定为重度抑郁症病例的参与者中,年龄较大和男性患者,以及在入组时发病率较低的患者,不太可能被另一种方法确定为病例。不同MDD病例/对照定义和参与者特征之间的关联强度取决于MDD定义是否使用相同的信息来源(即,仅EHR,仅自我报告)-导致更强的关联,而不同的信息来源(即,一个来自EHR,一个来自自我报告)-导致较弱的关联。结论:我们的研究结果表明,用于识别重度抑郁症患者病史的方法如何影响样本特征和风险因素关联,突出了在解释研究结果时考虑表型确定的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of mood and anxiety disorders
Journal of mood and anxiety disorders Applied Psychology, Experimental and Cognitive Psychology, Clinical Psychology, Psychiatry and Mental Health, Psychology (General), Behavioral Neuroscience
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