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Prediction of psychosis in prodrome: development and validation of a simple, personalized risk calculator

Published online by Cambridge University Press:  14 September 2018

TianHong Zhang ,
LiHua Xu ,
YingYing Tang ,
HuiJun Li ,
XiaoChen Tang ,
HuiRu Cui ,
YanYan Wei ,
Yan Wang ,
Qiang Hu  and
XiaoHua Liu
...Show all authors
TianHong Zhang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
LiHua Xu
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
YingYing Tang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
HuiJun Li
Affiliation:
Department of Psychology, Florida A & M University, Tallahassee, Florida 32307, USA
XiaoChen Tang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
HuiRu Cui
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
YanYan Wei
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
Yan Wang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
Qiang Hu
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
XiaoHua Liu
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
ChunBo Li
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
Zheng Lu*
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China Department of Psychiatry, Tongji Hospital, Tongji University School of Medicine, 389 Xin Cun Road, Shanghai 200065, China
Robert W. McCarley
Affiliation:
Department of Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Center, 75 Fenwood Rd, Boston, MA 02115, USA
Larry J. Seidman
Affiliation:
Department of Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Center, 75 Fenwood Rd, Boston, MA 02115, USA
JiJun Wang*
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai, PR China CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, PR China
*
Author for correspondence: JiJun Wang, E-mail: [email protected] and Lu Zheng, E-mail: [email protected]
Author for correspondence: JiJun Wang, E-mail: [email protected] and Lu Zheng, E-mail: [email protected]
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Abstract

Background

This study aim to derive and validate a simple and well-performing risk calculator (RC) for predicting psychosis in individual patients at clinical high risk (CHR).

Methods

From the ongoing ShangHai-At-Risk-for-Psychosis (SHARP) program, 417 CHR cases were identified based on the Structured Interview for Prodromal Symptoms (SIPS), of whom 349 had at least 1-year follow-up assessment. Of these 349 cases, 83 converted to psychosis. Logistic regression was used to build a multivariate model to predict conversion. The area under the receiver operating characteristic (ROC) curve (AUC) was used to test the effectiveness of the SIPS-RC. Second, an independent sample of 100 CHR subjects was recruited based on an identical baseline and follow-up procedures to validate the performance of the SIPS-RC.

Results

Four predictors (each based on a subset of SIPS-based items) were used to construct the SIPS-RC: (1) functional decline; (2) positive symptoms (unusual thoughts, suspiciousness); (3) negative symptoms (social anhedonia, expression of emotion, ideational richness); and (4) general symptoms (dysphoric mood). The SIPS-RC showed moderate discrimination of subsequent transition to psychosis with an AUC of 0.744 (p < 0.001). A risk estimate of 25% or higher had around 75% accuracy for predicting psychosis. The personalized risk generated by the SIPS-RC provided a solid estimate of conversion outcomes in the independent validation sample, with an AUC of 0.804 [95% confidence interval (CI) 0.662–0.951].

Conclusion

The SIPS-RC, which is simple and easy to use, can perform in the same manner as the NAPLS-2 RC in the Chinese clinical population. Such a tool may be used by clinicians to counsel appropriately their patients about clinical monitor v. potential treatment options.

Keywords

Ultra high riskclinical high riskschizophreniaconversiontransitionrisk factoroutcome
Type
Original Articles
Information
Psychological Medicine , Volume 49 , Issue 12 , September 2019 , pp. 1990 - 1998
Copyright
Copyright © Cambridge University Press 2018 

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Footnotes

*

Dr Larry J. Seidman passed away on 7 September 2017. Dr Robert W. McCarley passed away on 27 May 2017. Both were founders and core members of the SHARP (ShangHai At Risk for Psychosis) project.

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