Center for Precision Psychiatry, Massachusetts General Hospital, 185 Cambridge Street, 2(nd) floor, Boston, MA 02114, USA; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge Street, 6(th) floor, Boston, MA 02114, USA; Department of Psychiatry, Massachusetts General Hospital / Harvard Medical School, 55 Fruit St, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, MA 02142, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA.
Department of Neurology, Massachusetts General Hospital / Harvard Medical School, 55 Fruit St, Boston, MA 02114, USA.
Gen Hosp Psychiatry. 2023 Mar-Apr;81:22-31. doi: 10.1016/j.genhosppsych.2022.12.004. Epub 2022 Dec 12.
Pharmacological treatment of depression mostly occurs in non-psychiatric settings, but the determinants of initial choice of antidepressant treatment in these settings are unclear. We investigate how non-psychiatrists choose among four antidepressant classes at first prescription (selective serotonin reuptake inhibitors [SSRI], bupropion, mirtazapine, or serotonin-norepinephrine reuptake inhibitors [SNRI]).
Using electronic health records (EHRs), we included adult patients at the time of first antidepressant prescription with a co-occurring diagnosis code for a depressive disorder. We selected 64 variables based on a literature search and expert consultation, constructed the variables from either structured codes or through applying natural language processing (NLP), and modeled antidepressant choice using multinomial logistic regression, using SSRI as the reference class.
With 47,528 patients, we observed significant associations for 36 of 64 variables. Many of these associations suggested antidepressants' known pharmacological properties/actions guided choice. For example, there was a decreased likelihood of bupropion prescription among patients with epilepsy (adjusted OR 0.49, 95%CI: 0.41-0.57, p < 0.001), and an increased likelihood of mirtazapine prescription among patients with insomnia (adjusted OR 1.59, 95%CI: 1.40-1.80, p < 0.001).
Broadly speaking, non-psychiatrists' selection of antidepressant class appears to be at least in part guided by clinically relevant pharmacological considerations.
抑郁症的药物治疗大多发生在非精神科环境中，但这些环境中抗抑郁药物治疗初始选择的决定因素尚不清楚。我们研究了非精神科医生在首次处方时如何在四种抗抑郁药类别（选择性 5-羟色胺再摄取抑制剂 [SSRIs]、安非他酮、米氮平或 5-羟色胺-去甲肾上腺素再摄取抑制剂 [SNRIs]）之间做出选择。
我们使用电子健康记录 (EHR)，纳入首次抗抑郁药处方时同时伴有抑郁障碍诊断代码的成年患者。我们根据文献检索和专家咨询选择了 64 个变量，从结构化代码中提取这些变量，或通过应用自然语言处理 (NLP) 构建这些变量，并使用多项逻辑回归模型来建模抗抑郁药的选择，以 SSRIs 作为参考类别。
在 47528 名患者中，我们观察到 64 个变量中的 36 个存在显著关联。这些关联中的许多表明抗抑郁药已知的药理学特性/作用指导了选择。例如，癫痫患者使用安非他酮的可能性降低（调整后的 OR 0.49，95%CI：0.41-0.57，p<0.001），失眠患者使用米氮平的可能性增加（调整后的 OR 1.59，95%CI：1.40-1.80，p<0.001）。
总体而言，非精神科医生对抗抑郁药类别的选择似乎至少部分受到临床相关药理学考虑的指导。
