Prediction of Psychosis in Adolescents and Young Adults at High Risk Results From the Prospective European Prediction of Psychosis Study
Prediction of Psychosis in Adolescents and Young Adults at High Risk Results From the Prospective European Prediction of Psychosis Study
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DOI：
10.1001/archgenpsychiatry.2009.206
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发表时间：
2010-03-01
影响因子：
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通讯作者：
Klosterkoetter, Joachim
中科院分区：
文献类型：
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作者：
Ruhrmann, Stephan;Schultze-Lutter, Frauke;Klosterkoetter, Joachim
适应性预防目前被认为是减轻、延缓甚至避免精神病的最有希望的策略。现有的标准需要在特异性和个体风险评估方面进行改进，以便更好地针对性和更早地进行干预。目的：开发一种向首发精神病转变的差异预测临床模型。设计：前瞻性多中心、自然主义实地研究，总随访时间为18个月。设置：德国、芬兰、荷兰和英国的6个早期检测门诊中心。参与者：根据超高风险（UHR）标准或基于认知障碍（COGDIS）的基本诊断标准，245例处于精神病前驱状态的求助患者。主要结果测量：向精神病转变的发生率。结果：在18个月随访时，向精神病转变的发生率为19%。结合UHR和COGDIS产生最佳的敏感性。研究人员开发了一个预测模型，其中包括阳性症状、奇怪的想法、睡眠障碍、典型障碍、过去一年的功能水平和受教育年限。阳性似然比为19.9，曲线下面积为80.8%，阳性预测值为83.3%，诊断准确性极佳。一个4级预后指数进一步分类的一般风险的整个样本预测瞬时发病率高达85%，并允许估计的时间transition.Conclusions：预测模型确定了适当的预后准确性，在我们的样本中精神病的风险增加。提出了两步风险评估，UHR和认知障碍标准作为一般风险的第一步标准，预后指数作为第二步工具，进一步对每个患者进行风险分类。这一战略将使临床医生有针对性地采取预防措施，并将支持揭示精神病进展背后的生物和环境机制的努力。
Context: Indicated prevention is currently regarded as the most promising strategy to attenuate, delay, or even avert psychosis. Existing criteria need improvement in terms of specificity and individual risk assessment to allow for better targeted and earlier interventions.Objective: To develop a differential predictive clinical model of transition to first-episode psychosis.Design: Prospective multicenter, naturalistic field study with a total follow-up time of 18 months.Setting: Six early-detection outpatient centers in Germany, Finland, the Netherlands, and England.Participants: Two hundred forty-five help-seeking patients in a putatively prodromal state of psychosis according to either ultra-high-risk (UHR) criteria or the basic symptom-based criterion cognitive disturbances (COGDIS).Main Outcome Measure: Incidence of transition to psychosis.Results: At 18-month follow-up, the incidence rate for transition to psychosis was 19%. Combining UHR and COGDIS yielded the best sensitivity. A prediction model was developed and included positive symptoms, bizarre thinking, sleep disturbances, a schizotypal disorder, level of functioning in the past year, and years of education. With a positive likelihood ratio of 19.9, an area under the curve of 80.8%, and a positive predictive value of 83.3%, diagnostic accuracy was excellent. A 4-level prognostic index further classifying the general risk of the whole sample predicted instantaneous incidence rates of up to 85% and allowed for an estimation of time to transition.Conclusions: The prediction model identified an increased risk of psychosis with appropriate prognostic accuracy in our sample. A 2-step risk assessment is proposed, with UHR and cognitive disturbance criteria serving as first-step criteria for general risk and the prognostic index as a second-step tool for further risk classification of each patient. This strategy will allow clinicians to target preventive measures and will support efforts to unveil the biological and environmental mechanisms underlying progression to psychosis.