Carrión Ricardo E, Cornblatt Barbara A, Burton Cynthia Z, Tso Ivy F, Auther Andrea M, Adelsheim Steven, Calkins Roderick, Carter Cameron S, Niendam Tara, Sale Tamara G, Taylor Stephan F, McFarlane William R
From the Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, Glen Oaks, N.Y.; the Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Northwell Health, Manhasset, N.Y.; the Departments of Psychiatry and Molecular Medicine, Hofstra Northwell School of Medicine, Hempstead, N.Y.; the Department of Psychiatry, University of Michigan, Ann Arbor; the Department of Psychiatry, Stanford University, Palo Alto, Calif.; the Imaging Research Center and the Center for Neuroscience, University of California Davis, Sacramento, Calif.; Portland State University Regional Research Institute, Portland, Ore.; the Mid-Valley Behavioral Care Network, Marion County Health Department, Salem, Ore.; Tufts University School of Medicine, Boston; and Maine Medical Center Research Institute, Portland.
Am J Psychiatry. 2016 Oct 1;173(10):989-996. doi: 10.1176/appi.ajp.2016.15121565. Epub 2016 Jul 1.
As part of the second phase of the North American Prodrome Longitudinal Study (NAPLS-2), Cannon and colleagues report, concurrently with the present article, on a risk calculator for the individualized prediction of a psychotic disorder in a 2-year period. The present study represents an external validation of the NAPLS-2 psychosis risk calculator using an independent sample of patients at clinical high risk for psychosis collected as part of the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP).
Of the total EDIPPP sample of 210 subjects rated as being at clinical high risk based on the Structured Interview for Prodromal Syndromes, 176 had at least one follow-up assessment and were included in the construction of a new prediction model with six predictor variables in the NAPLS-2 psychosis risk calculator (unusual thoughts and suspiciousness, symbol coding test performance, verbal learning test performance, decline in social functioning, baseline age, and family history). Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC). The NAPLS-2 risk calculator was then used to generate a psychosis risk estimate for each case in the external validation sample.
The external validation model showed good discrimination, with an AUC of 0.790 (95% CI=0.644-0.937). In addition, the personalized risk generated by the risk calculator provided a solid estimation of the actual conversion outcome in the validation sample.
Two independent samples of clinical high-risk patients converge to validate the NAPLS-2 psychosis risk calculator. This prediction calculator represents a meaningful step toward early intervention and the personalized treatment of psychotic disorders.
作为北美前驱期纵向研究(NAPLS - 2)第二阶段的一部分,坎农及其同事在发表本文的同时,报告了一种用于个体化预测两年内发生精神障碍风险的计算器。本研究使用作为精神病早期检测、干预和预防项目(EDIPPP)一部分收集的处于临床高风险的独立患者样本,对NAPLS - 2精神病风险计算器进行外部验证。
在基于前驱症状结构化访谈被评定为临床高风险的210名EDIPPP样本受试者中,176人至少有一次随访评估,并被纳入构建一个新的预测模型,该模型包含NAPLS - 2精神病风险计算器中的六个预测变量(异常思维和猜疑、符号编码测试表现、言语学习测试表现、社会功能下降、基线年龄和家族史)。使用受试者工作特征曲线下面积(AUC)评估判别性能。然后使用NAPLS - 2风险计算器为外部验证样本中的每个病例生成精神病风险估计值。
外部验证模型显示出良好的判别能力,AUC为0.790(95%CI = 0.644 - 0.937)。此外,风险计算器生成的个性化风险为验证样本中的实际转化结果提供了可靠估计。
两个独立的临床高风险患者样本共同验证了NAPLS - 2精神病风险计算器。这个预测计算器是朝着精神病早期干预和个性化治疗迈出的有意义的一步。