Urine drug screening (UDS) assays can rapidly and sensitively detect drugs of abuse but can also produce spurious results due to interfering substances. We previously developed an approach to identify interfering medications using electronic health record (EHR) data, but the approach was limited to UDS assays for which presumptive positives were confirmed using more specific methods. Here we adapted the approach to search for medications that cause false positives on UDS assays lacking confirmation data. From our institution’s EHR data, we used our previous dataset of 698,651 UDS and confirmation results. We also collected 211,108 UDS results for acetaminophen, ethanol and salicylates. Both datasets included individuals’ prior medication exposures. We hypothesized that the odds of a presumptive positive would increase following exposure to an interfering medication independently of exposure to the assay’s target drug(s). For a given assay–medication pair, we quantified potential interference as an odds ratio from logistic regression. We evaluated interference of selected compounds in spiking experiments. Compared to the approach requiring confirmation data, our adapted approach showed only modestly diminished ability to detect interfering medications. Applying our approach to the new data, we discovered and validated multiple compounds that can cause presumptive positives on the UDS assay for acetaminophen. Our approach can reveal interfering medications using EHR data from institutions at which UDS results are not routinely confirmed.

中文翻译：

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一种无需确认测试数据即可识别尿液药物筛选分析中干扰药物的计算方法

尿液药物筛查（UDS）分析可以快速，灵敏地检测滥用药物，但由于干扰物质的影响，也会产生虚假结果。我们之前开发了一种使用电子健康记录（EHR）数据来识别干扰药物的方法，但是该方法仅限于使用更具体的方法确认阳性的UDS分析。在这里，我们采用了这种方法来搜索在缺乏确认数据的UDS分析中导致假阳性的药物。从我们机构的EHR数据中，我们使用了以前的698,651 UDS和确认结果数据集。我们还收集了对乙酰氨基酚，乙醇和水杨酸酯的211,108 UDS结果。这两个数据集都包括个人以前的药物暴露情况。我们假设，在暴露于干扰药物后，独立于测定的目标药物的暴露，推定阳性的几率会增加。对于给定的化验-药物对，我们通过逻辑回归将潜在干扰量化为比值比。我们在加标实验中评估了所选化合物的干扰。与需要确认数据的方法相比，我们采用的方法仅显示出适度降低了检测干扰药物的能力。将我们的方法应用于新数据，我们发现并验证了多种化合物，这些化合物可能导致对乙酰氨基酚的UDS分析呈阳性。我们的方法可以使用未定期确认UDS结果的机构的EHR数据来揭示干扰药物。