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A predictive model for conversion to psychosis in clinical high-risk patients

Published online by Cambridge University Press:  28 June 2018

Adam J. Ciarleglio Open the ORCID record for Adam J. Ciarleglio [Opens in a new window] ,
Gary Brucato ,
Michael D. Masucci ,
Rebecca Altschuler ,
Tiziano Colibazzi ,
Cheryl M. Corcoran ,
Francesca M. Crump ,
Guillermo Horga ,
Eugénie Lehembre-Shiah  and
Wei Leong
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Adam J. Ciarleglio*
Affiliation:
Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA Department of Psychiatry, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Research Foundation for Mental Hygiene, New York, NY, USA
Gary Brucato
Affiliation:
Department of Psychiatry, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Research Foundation for Mental Hygiene, New York, NY, USA The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Michael D. Masucci
Affiliation:
Department of Psychiatry, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Research Foundation for Mental Hygiene, New York, NY, USA The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Rebecca Altschuler
Affiliation:
The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Tiziano Colibazzi
Affiliation:
Department of Psychiatry, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Research Foundation for Mental Hygiene, New York, NY, USA The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Cheryl M. Corcoran
Affiliation:
Icahn School of Medicine at Mt. Sinai, New York, NY, USA
Francesca M. Crump
Affiliation:
The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Guillermo Horga
Affiliation:
Department of Psychiatry, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Research Foundation for Mental Hygiene, New York, NY, USA The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Eugénie Lehembre-Shiah
Affiliation:
The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Wei Leong
Affiliation:
The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Scott A. Schobel
Affiliation:
F. Hoffman-LaRoche A.G., Basel, Switzerland
Melanie M. Wall
Affiliation:
Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA Department of Psychiatry, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Research Foundation for Mental Hygiene, New York, NY, USA
Lawrence H. Yang
Affiliation:
College of Global Public Health, New York University, New York, NY, USA
Jeffrey A. Lieberman
Affiliation:
Department of Psychiatry, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Research Foundation for Mental Hygiene, New York, NY, USA The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
Ragy R. Girgis
Affiliation:
Department of Psychiatry, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA Research Foundation for Mental Hygiene, New York, NY, USA The Center of Prevention and Evaluation, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA
*
Author for correspondence: Adam J. Ciarleglio, E-mail: [email protected]
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Abstract

Background

The authors developed a practical and clinically useful model to predict the risk of psychosis that utilizes clinical characteristics empirically demonstrated to be strong predictors of conversion to psychosis in clinical high-risk (CHR) individuals. The model is based upon the Structured Interview for Psychosis Risk Syndromes (SIPS) and accompanying clinical interview, and yields scores indicating one's risk of conversion.

Methods

Baseline data, including demographic and clinical characteristics measured by the SIPS, were obtained on 199 CHR individuals seeking evaluation in the early detection and intervention for mental disorders program at the New York State Psychiatric Institute at Columbia University Medical Center. Each patient was followed for up to 2 years or until they developed a syndromal DSM-4 disorder. A LASSO logistic fitting procedure was used to construct a model for conversion specifically to a psychotic disorder.

Results

At 2 years, 64 patients (32.2%) converted to a psychotic disorder. The top five variables with relatively large standardized effect sizes included SIPS subscales of visual perceptual abnormalities, dysphoric mood, unusual thought content, disorganized communication, and violent ideation. The concordance index (c-index) was 0.73, indicating a moderately strong ability to discriminate between converters and non-converters.

Conclusions

The prediction model performed well in classifying converters and non-converters and revealed SIPS measures that are relatively strong predictors of conversion, comparable with the risk calculator published by NAPLS (c-index = 0.71), but requiring only a structured clinical interview. Future work will seek to externally validate the model and enhance its performance with the incorporation of relevant biomarkers.

Keywords

Clinical high riskprediction modelpsychosis predictionschizophrenia
Type
Original Articles
Information
Psychological Medicine , Volume 49 , Issue 7 , May 2019 , pp. 1128 - 1137
Copyright
Copyright © Cambridge University Press 2018 

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