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Conversion to psychosis in adolescents and adults: similar proportions, different predictors

Published online by Cambridge University Press:  06 April 2020

TianHong Zhang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
LiHua Xu
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
Ying Chen
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
YanYan Wei
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
XiaoChen Tang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
YeGang Hu
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
ZhiXing Li
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
RanPiao Gan
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
GuiSen Wu
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
HuiRu Cui
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
YingYing Tang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
Li Hui
Affiliation:
Institute of Mental Health, The Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou215137, Jiangsu, PR China
ChunBo Li
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
JiJun Wang*
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai, PR China Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
*
Author for correspondence: JiJun Wang, E-mail: jijunwang27@163.com

Abstract

Background

Age effects may be important for improving models for the prediction of conversion to psychosis for individuals in the clinical high risk (CHR) state. This study aimed to explore whether adolescent CHR individuals (ages 9–17 years) differ significantly from adult CHR individuals (ages 18–45 years) in terms of conversion rates and predictors.

Method

Consecutive CHR individuals (N = 517) were assessed for demographic and clinical characteristics and followed up for 3 years. Individuals with CHR were classified as adolescent (n = 244) or adult (n = 273) groups. Age-specific prediction models of psychosis were generated separately using Cox regression.

Results

Similar conversion rates were found between age groups; 52 out of 216 (24.1%) adolescent CHR individuals and 55 out of 219 (25.1%) CHR adults converted to psychosis. The conversion outcome was best predicted by negative symptoms compared to other clinical variables in CHR adolescents (χ2 = 7.410, p = 0.006). In contrast, positive symptoms better predicted conversion in CHR adults (χ2 = 6.585, p = 0.01).

Conclusions

Adolescent and adult CHR individuals may require a different approach to early identification and prediction. These results can inform the development of more precise prediction models based on age-specific approaches.

Type
Original Article
Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press

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