Psychotic Disorders Division, McLean Hospital HMS, Boston, MA, USA.
Department of Research Computing, HMS, Boston, MA, USA.
Schizophr Res. 2019 Jul;209:234-244. doi: 10.1016/j.schres.2019.02.003. Epub 2019 Feb 28.
There is a large variability in the recovery trajectory and outcome of first episode of psychosis [FEP] patients. To date, individuals' outcome trajectories at early stage of illness and potential risk factors associated with a poor outcome trajectory are largely unknown. This study aims to apply three separate predictors (positive symptoms, negative symptoms, and soft neurological signs) to identify homogeneous function outcome trajectories in patients with FEP using objective data-driven methods, and to explore the potential risk /protective factors associated with each trajectory.
A total of 369 first episode patients (93% antipsychotic naive) were included in the baseline assessments and followed-up at 4-8 weeks, 6 months, and 1 year. K means cluster modeling for longitudinal data (kml3d) was used to identify distinct, homogeneous clusters of functional outcome trajectories. Patients with at least 3 assessments were included in the trajectory analyses (N = 129). The Scale for the Assessment of Negative Symptoms (SANS), Scale for the Assessment of Positive Symptoms (SAPS), and Neurological examination abnormalities (NEA) were used as predictors against Global Assessment of Functioning Scale (GAF).
In each of the three predictor models, four distinct functional outcome trajectories emerged: "Poor", "Intermediate", High" and "Catch-up". Individuals with male gender; ethnic minority status; low premorbid adjustment; low executive function/IQ, low SES, personality disorder, substance use history may be risk factors for poor recovery.
Functioning recovery in individuals with FEP is heterogeneous, although distinct recovery profiles are apparent. Data-driven trajectory analysis can facilitate better characterization of individual longitudinal patterns of functioning recovery.
首次发作精神分裂症[FEP]患者的恢复轨迹和结果存在很大差异。迄今为止,个体在疾病早期的结局轨迹以及与不良结局轨迹相关的潜在风险因素在很大程度上尚不清楚。本研究旨在应用三种独立的预测指标(阳性症状、阴性症状和软神经体征),使用客观的数据驱动方法,识别 FEP 患者的同质功能结局轨迹,并探讨与每个轨迹相关的潜在风险/保护因素。
共有 369 名首发患者(93%为抗精神病药物初治)纳入基线评估,并在 4-8 周、6 个月和 1 年内进行随访。使用纵向数据的 K 均值聚类模型(kml3d)来识别功能结局轨迹的不同、同质集群。至少有 3 次评估的患者被纳入轨迹分析(N=129)。使用阴性症状评定量表(SANS)、阳性症状评定量表(SAPS)和神经系统检查异常(NEA)作为预测指标,对抗总体功能评定量表(GAF)。
在每个预测模型中,都出现了四个不同的功能结局轨迹:“较差”、“中等”、“高”和“追赶”。男性;少数民族;低前期适应;低执行功能/智商、低社会经济地位、人格障碍、物质使用史的个体可能是恢复不良的风险因素。
FEP 个体的功能恢复是异质的,尽管存在明显的恢复特征。基于数据的轨迹分析可以更好地描述个体功能恢复的纵向模式。