Mann J John, Currier Dianne, Stanley Barbara, Oquendo Maria A, Amsel Lawrence V, Ellis Steven P
Department of Neuroscience, New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY 10032, USA.
Int J Neuropsychopharmacol. 2006 Aug;9(4):465-74. doi: 10.1017/S1461145705005687. Epub 2005 Jun 21.
Predicting suicide is difficult due to its low base-rate and the limited specificity of clinical predictors. Prospective biological studies suggest that dysfunctions in the serotonergic system and hypothalamic-pituitary-adrenal axis have some predictive power for completed suicide in mood disorders. A prediction model that incorporates biological testing to increase specificity and sensitivity of prediction of suicide is of potential clinical value. Meta-analyses of prospective biological studies of suicide and cerebrospinal fluid 5-hydroxyindoleacetic acid (CSF 5-HIAA) and suicide and the dexamethasone suppression test (DST) in mood disorders using the penalized quasi-likelihood (PQL) and bootstrap method yield odds ratios for prediction of suicide of 4.48 and 4.65 respectively. Two combinatory prediction models, the first requiring positive results on more than one test, and the second requiring a positive result on either one of two tests, were tested to assess their sensitivity, specificity, and predictive power using biological data from published and unpublished studies. The prediction model that requires both DST and CSF 5-HIAA tests to be positive results in 37.5% sensitivity, 88% specificity, and has a positive predictive value of 23%. The prediction model that requires either DST or CSF 5-HIAA tests to be positive results in 87.5% sensitivity, 28% specificity, and has a positive predictive value of 10%. Thus, models attempting to predict a lethal outcome that is uncommon perform very differently making model choice of major importance. Further work on refining biological predictors and integration with clinical predictors is needed to optimize a model to predict suicide in the clinic.
由于自杀的低基础发生率以及临床预测指标的特异性有限,预测自杀行为具有一定难度。前瞻性生物学研究表明,血清素能系统和下丘脑 - 垂体 - 肾上腺轴的功能障碍对心境障碍中最终发生的自杀行为具有一定的预测能力。一个纳入生物学检测以提高自杀预测特异性和敏感性的预测模型具有潜在的临床价值。使用惩罚拟似然法(PQL)和自助法对自杀与脑脊液5 - 羟吲哚乙酸(CSF 5 - HIAA)以及自杀与心境障碍中的地塞米松抑制试验(DST)的前瞻性生物学研究进行荟萃分析,得出预测自杀的优势比分别为4.48和4.65。通过已发表和未发表研究中的生物学数据,对两个组合预测模型进行了测试,第一个模型要求在一项以上检测中得到阳性结果,第二个模型要求在两项检测中的任意一项得到阳性结果,以评估它们的敏感性、特异性和预测能力。要求DST和CSF 5 - HIAA检测均为阳性结果的预测模型,其敏感性为37.5%,特异性为88%,阳性预测值为23%。要求DST或CSF 5 - HIAA检测为阳性结果的预测模型,其敏感性为87.5%,特异性为28%,阳性预测值为10%。因此,试图预测一种不常见的致命结果的模型表现差异很大,这使得模型选择至关重要。需要进一步开展工作来完善生物学预测指标并将其与临床预测指标相结合,以优化临床中预测自杀行为的模型。