Prediction of psychosis in prodrome: development and validation of a simple, personalized risk calculator
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.
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The Zhang et al. model predicts psychosis onset in CHR-P with an AUC of 0.744 in the development sample (n=349, mean age 20.4, China).
“349 (20.4, China); 0.744 (AUC) 295”
From Preventive psychiatry: a blueprint for improving the mental health of young people (2021) · cites this paper as [295]
The Zhang et al. model has external validation AUCs of 0.804 (n=100, China) and 0.65 (n=98, mean age 18.59, US).
“100 (age not available, China); 0.804 (AUC) 295 98 (18.59, US); 0.65 (AUC) 294”
From Preventive psychiatry: a blueprint for improving the mental health of young people (2021) · cites this paper as [295]
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Preventive psychiatry: a blueprint for improving the mental health of young people
Fusar‐Poli, P., Correll, C. U., Arango, C., Berk, M., Patel, V., & Ioannidis, J. P. A. (2021) · World Psychiatry · doi:10.1002/wps.20869 · Cited by 497 · see citing works
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- Authors
- Zhang, T., Xu, L., Tang, Y., Li, H., Tang, X., Cui, H., Wei, Y., Wang, Y., Hu, Q., Liu, X., Li, C., Lu, Z., McCarley, R. W., Seidman, L. J., Wang, J., & on behalf of the SHARP (ShangHai At Risk for Psychosis) Study Group
- Affiliations
- Shanghai Jiao Tong University (CN)
- Florida Agricultural and Mechanical University (US)
- Tongji University (CN)
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Lu, Zheng
- Wang, JiJun
- ORCID
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2018-09-14
- Volume
- 49
- Issue
- 12
- Pages
- 1990-1998
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- OpenAlex
- W2890862698
- Cited by
- 82
- References
- 33
- Citations by year
- 2026: 2 · 2025: 10 · 2024: 9 · 2023: 12 · 2022: 13 · 2021: 16 · 2020: 13 · 2019: 7
- FWCI
- 7.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (R21MH093294)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Psychology › Clinical Psychology › Psychopathy, Forensic Psychiatry, Sexual Offending
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Keywords
- prodromal psychosis, clinical high risk for psychosis, risk calculator, functional decline, positive symptoms, negative symptoms, dysphoric mood
- MeSH terms
- Adolescent, Adult, China, Female, Humans, Male, Psychotic Disorders, Risk Factors, ROC Curve, Reproducibility of Results, Multivariate Analysis, Logistic Models, Disease Progression, Risk Assessment, Area Under Curve, Young Adult, Prodromal Symptoms
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