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Poor functional recovery is better predicted than conversion in studies of outcomes of clinical high risk of psychosis: insight from SHARP.

Authors
  • Zhang, TianHong1
  • Yang, ShuWen1
  • Xu, LiHua1
  • Tang, XiaoChen1
  • Wei, YanYan1
  • Cui, HuiRu1
  • Li, HuiJun2
  • Tang, YingYing1
  • Hui, Li3
  • Li, ChunBo1
  • Chen, XingShi1, 3
  • Wang, JiJun1, 4, 5
  • 1 Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China. , (China)
  • 2 Department of Psychology, Florida A&M University, Tallahassee, Florida32307, USA.
  • 3 Institute of Mental Health, The Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou215137, Jiangsu, PR China. , (China)
  • 4 Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai, PR China. , (China)
  • 5 Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China. , (China)
Type
Published Article
Journal
Psychological Medicine
Publisher
Cambridge University Press
Publication Date
Jul 01, 2020
Volume
50
Issue
9
Pages
1578–1584
Identifiers
DOI: 10.1017/S0033291719002174
PMID: 31451124
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Few of the previous studies of clinical high risk of psychosis (CHR) have explored whether outcomes other than conversion, such as poor functioning or treatment responses, are better predicted when using risk calculators. To answer this question, we compared the predictive accuracy between the outcome of conversion and poor functioning by using the NAPLS-2 risk calculator. Three hundred CHR individuals were identified using the Chinese version of the Structured Interview for Prodromal Symptoms. Of these, 228 (76.0%) completed neurocognitive assessments at baseline and 199 (66.3%) had at least a 1-year follow-up assessment. The latter group was used in the NAPLS-2 risk calculator. We divided the sample into two broad categories based on different outcome definitions, conversion (n = 46) v. non-conversion (n = 153) or recovery (n = 138) v. poor functioning (n = 61). Interestingly, the NAPLS-2 risk calculator showed moderate discrimination of subsequent conversion to psychosis in this sample with an area under the receiver operating characteristic curve (AUC) of 0.631 (p = 0.007). However, for discriminating poor functioning, the AUC of the model increased to 0.754 (p < 0.001). Our results suggest that the current risk calculator was a better fit for predicting a poor functional outcome and treatment response than it was in the prediction of conversion to psychosis.

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