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Development and validation of a non-remission risk prediction model in First Episode Psychosis: An analysis of two longitudinal studies

Published online by Cambridge University Press:  18 June 2021

Samuel Leighton*
Affiliation:
University of Glasgow
Pavan Mallikarjun
Affiliation:
University of Birmingham
Rajeev Krishnadas
Affiliation:
NHS Greater Glasgow & Clyde
Jonathan Cavanagh
Affiliation:
University of Glasgow
Simon Rogers
Affiliation:
University of Glasgow
Rachel Upthegrove
Affiliation:
University of Birmingham
Max Birchwood
Affiliation:
University of Warwick
Stephen Marwaha
Affiliation:
University of Birmingham
Ewout Steyerberg
Affiliation:
University of Leiden
Georgios Gkoutos
Affiliation:
University of Birmingham
Matthew Broome
Affiliation:
University of Birmingham
Peter Liddle
Affiliation:
University of Nottingham
Linda Everard
Affiliation:
Neuropsychiatry - The Barberry Center
Swaran Singh
Affiliation:
University of Warwick
Nicholas Freemantle
Affiliation:
University College London
David Fowler
Affiliation:
University of Sussex
Peter Jones
Affiliation:
University of Cambridge
Vimal Sharma
Affiliation:
University of Chester
Robin Murray
Affiliation:
Institute of Psychiatry, Psychology and Neuroscience, King's College London
Til Wykes
Affiliation:
Institute of Psychiatry, Psychology and Neuroscience, King's College London
Richard Drake
Affiliation:
University of Manchester
Iain Buchan
Affiliation:
University of Liverpool
Shon Lewis
Affiliation:
University of Manchester
*
*corresponding author.
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Abstract

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Aims

Psychosis is a major mental illness with first onset in young adults. The prognosis is poor in around half of the people affected, and difficult to predict. The few tools available to predict prognosis have major weaknesses which limit their use in clinical practice. We aimed to develop and validate a risk prediction model of symptom non-remission in first-episode psychosis.

Method

Our development cohort consisted of 1027 patients with first-episode psychosis recruited between 2005 to 2010 from 14 early intervention services across the National Health Service in England. Our validation cohort consisted of 399 patients with first-episode psychosis recruited between 2006 to 2009 from a further 11 English early intervention services. The one-year non-remission rate was 52% and 54% in the development and validation cohorts, respectively. Multivariable logistic regression was used to develop a risk prediction model for non-remission, which was externally validated.

Result

The prediction model showed good discrimination (C-statistic of 0.74 (0.72, 0.76) and adequate calibration with intercept alpha of 0.13 (0.03, 0.23) and slope beta of 0.99 (0.87, 1.12). Our model improved the net-benefit by 16% at a risk threshold of 50%, equivalent to 16 more detected non-remitted first-episode psychosis individuals per 100 without incorrectly classifying remitted cases.

Conclusion

Once prospectively validated, our first episode psychosis prediction model could help identify patients at increased risk of non-remission at initial clinical contact.

Type
Rapid-Fire Poster Presentations
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists
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