混淆
联想(心理学)
医学
抗癌药物
药品
数据科学
计算机科学
心理学
药理学
病理
心理治疗师
作者
Youjin Wang,Shahinaz M. Gadalla
标识
DOI:10.1158/1055-9965.epi-20-1612
摘要
Abstract Cancer risk associations with commonly prescribed medications have been mainly evaluated in hypothesis-driven studies that focus on one drug at a time. Agnostic drug-wide association studies (DWAS) offer an alternative approach to simultaneously evaluate associations between a large number of drugs with one or more cancers using large-scale electronic health records. Although cancer DWAS approaches are promising, a number of challenges limit their applicability. This includes the high likelihood of false positivity; lack of biological considerations; and methodological shortcomings, such as inability to tightly control for confounders. As such, the value of DWAS is currently restricted to hypothesis generation with detected signals needing further evaluation. In this commentary, we discuss those challenges in more detail and summarize the approaches to overcome them by using published cancer DWAS studies, including the accompanied article by Støer and colleagues. Despite current concerns, DWAS future is filled with opportunities for developing innovative analytic methods and techniques that incorporate pharmacology, epidemiology, cancer biology, and genetics. See related article by Støer et al., p. 682
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