Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
Department of Psychiatry, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.
Psychol Med. 2022 Oct;52(13):2632-2640. doi: 10.1017/S0033291720004675. Epub 2020 Dec 14.
Over the past two decades, early detection and early intervention in psychosis have become essential goals of psychiatry. However, clinical impressions are insufficient for predicting psychosis outcomes in clinical high-risk (CHR) individuals; a more rigorous and objective model is needed. This study aims to develop and internally validate a model for predicting the transition to psychosis within 10 years.
Two hundred and eight help-seeking individuals who fulfilled the CHR criteria were enrolled from the prospective, naturalistic cohort program for CHR at the Seoul Youth Clinic (SYC). The least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was used to develop a predictive model for a psychotic transition. We performed -means clustering and survival analysis to stratify the risk of psychosis.
The predictive model, which includes clinical and cognitive variables, identified the following six baseline variables as important predictors: 1-year percentage decrease in the Global Assessment of Functioning score, IQ, California Verbal Learning Test score, Strange Stories test score, and scores in two domains of the Social Functioning Scale. The predictive model showed a cross-validated Harrell's -index of 0.78 and identified three subclusters with significantly different risk levels.
Overall, our predictive model showed a predictive ability and could facilitate a personalized therapeutic approach to different risks in high-risk individuals.
在过去的二十年中，精神病学的主要目标已经变成了精神病的早期发现和早期干预。然而，对于临床高风险（CHR）个体，临床印象不足以预测精神病结局；需要更严格、更客观的模型。本研究旨在开发和内部验证一种预测 10 年内精神病转化的模型。
从 SYC 的前瞻性、自然主义 CHR 队列计划中招募了 208 名符合 CHR 标准的寻求帮助的个体。使用最小绝对值收缩和选择算子（LASSO）惩罚 Cox 回归来开发精神病转化的预测模型。我们进行了-均值聚类和生存分析来分层精神病的风险。
该预测模型包括临床和认知变量，确定了以下六个基线变量作为重要预测因子：1 年内总体功能评估评分的百分比下降、智商、加利福尼亚语言学习测试评分、奇怪故事测试评分以及社会功能量表的两个领域的评分。该预测模型显示交叉验证的 Harrell's -指数为 0.78，并确定了三个具有显著不同风险水平的亚组。
总体而言，我们的预测模型显示出了预测能力，并能够为高风险个体的不同风险提供个性化的治疗方法。
