Literature DB >> 28212505

Long-term validity of the At Risk Mental State (ARMS) for predicting psychotic and non-psychotic mental disorders.

P Fusar-Poli1, G Rutigliano2, D Stahl3, C Davies3, A De Micheli4, V Ramella-Cravaro3, I Bonoldi5, P McGuire3.   

Abstract

BACKGROUND: The long-term clinical validity of the At Risk Mental State (ARMS) for the prediction of non-psychotic mental disorders is unknown.
METHODS: Clinical register-based cohort study including all non-psychotic individuals assessed by the Outreach And Support in South London (OASIS) service (2002-2015). The primary outcome was risk of developing any mental disorder (psychotic or non-psychotic). Analyses included Cox proportional hazard models, Kaplan-Meier survival/failure function and C statistics.
RESULTS: A total of 710 subjects were included. A total of 411 subjects were at risk (ARMS+) and 299 not at risk (ARMS-). Relative to ARMS-, the ARMS+ was associated with an increased risk (HR=4.825) of developing psychotic disorders, and a reduced risk (HR=0.545) of developing non-psychotic disorders (mainly personality disorders). At 6-year, the ARMS designation retained high sensitivity (0.873) but only modest specificity (0.456) for the prediction of psychosis onset (AUC 0.68). The brief and limited intermittent psychotic symptoms (BLIPS) subgroup had a higher risk of developing psychosis, and a lower risk of developing non-psychotic disorders as compared to the attenuated psychotic symptoms (APS) subgroup (P<0.001).
CONCLUSIONS: In the long-term, the ARMS specifically predicts the onset of psychotic disorders, with modest accuracy, but not of non-psychotic disorders. Individuals meeting BLIPS criteria have distinct clinical outcomes. SIGNIFICANT OUTCOMES: In the long-term, the ARMS designation is still significantly associated with an increased risk of developing psychotic disorders but its prognostic accuracy is only modest. There is no evidence that the ARMS is associated with an increased risk of developing non-psychotic mental disorders. The BLIPS subgroup at lower risk of developing non-psychotic disorders compared to the APS subgroup. LIMITATIONS: While incident diagnoses employed in this study are high in ecological validity they have not been subjected to formal validation with research-based criteria.
Copyright © 2017 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Entities:  

Keywords:  ARMS; Early intervention; Psychosis; Risk; Risk factors; Schizophrenia

Mesh:

Year:  2016        PMID: 28212505     DOI: 10.1016/j.eurpsy.2016.11.010

Source DB:  PubMed          Journal:  Eur Psychiatry        ISSN: 0924-9338            Impact factor:   5.361


  41 in total

1.  Lack of evidence to favor specific preventive interventions in psychosis: a network meta-analysis.

Authors:  Cathy Davies; Andrea Cipriani; John P A Ioannidis; Joaquim Radua; Daniel Stahl; Umberto Provenzani; Philip McGuire; Paolo Fusar-Poli
Journal:  World Psychiatry       Date:  2018-06       Impact factor: 49.548

2.  Improving outcomes of first-episode psychosis: an overview.

Authors:  Paolo Fusar-Poli; Patrick D McGorry; John M Kane
Journal:  World Psychiatry       Date:  2017-10       Impact factor: 49.548

3.  Development and Validation of a Dynamic Risk Prediction Model to Forecast Psychosis Onset in Patients at Clinical High Risk.

Authors:  Erich Studerus; Katharina Beck; Paolo Fusar-Poli; Anita Riecher-Rössler
Journal:  Schizophr Bull       Date:  2020-02-26       Impact factor: 9.306

4.  Lack of Diagnostic Pluripotentiality in Patients at Clinical High Risk for Psychosis: Specificity of Comorbidity Persistence and Search for Pluripotential Subgroups.

Authors:  Scott W Woods; Albert R Powers; Jerome H Taylor; Charlie A Davidson; Jason K Johannesen; Jean Addington; Diana O Perkins; Carrie E Bearden; Kristin S Cadenhead; Tyrone D Cannon; Barbara A Cornblatt; Larry J Seidman; Ming T Tsuang; Elaine F Walker; Thomas H McGlashan
Journal:  Schizophr Bull       Date:  2018-02-15       Impact factor: 9.306

5.  What causes psychosis? An umbrella review of risk and protective factors.

Authors:  Joaquim Radua; Valentina Ramella-Cravaro; John P A Ioannidis; Abraham Reichenberg; Nacharin Phiphopthatsanee; Taha Amir; Hyi Yenn Thoo; Dominic Oliver; Cathy Davies; Craig Morgan; Philip McGuire; Robin M Murray; Paolo Fusar-Poli
Journal:  World Psychiatry       Date:  2018-02       Impact factor: 49.548

6.  Comorbid diagnoses for youth at clinical high risk of psychosis.

Authors:  Jean Addington; Danijela Piskulic; Lu Liu; Jonathan Lockwood; Kristin S Cadenhead; Tyrone D Cannon; Barbara A Cornblatt; Thomas H McGlashan; Diana O Perkins; Larry J Seidman; Ming T Tsuang; Elaine F Walker; Carrie E Bearden; Daniel H Mathalon; Scott W Woods
Journal:  Schizophr Res       Date:  2017-03-31       Impact factor: 4.939

7.  Development and Validation of a Clinically Based Risk Calculator for the Transdiagnostic Prediction of Psychosis.

Authors:  Paolo Fusar-Poli; Grazia Rutigliano; Daniel Stahl; Cathy Davies; Ilaria Bonoldi; Thomas Reilly; Philip McGuire
Journal:  JAMA Psychiatry       Date:  2017-05-01       Impact factor: 21.596

Review 8.  Mental Health Services Research Targeting the Clinical High-Risk State for Psychosis: Lessons, Future Directions and Integration with Patient Perspectives.

Authors:  Sarah V McIlwaine; Jai Shah
Journal:  Curr Psychiatry Rep       Date:  2021-02-03       Impact factor: 5.285

9.  Association of Hippocampal Glutamate Levels With Adverse Outcomes in Individuals at Clinical High Risk for Psychosis.

Authors:  Matthijs G Bossong; Mathilde Antoniades; Matilda Azis; Carly Samson; Beverley Quinn; Ilaria Bonoldi; Gemma Modinos; Jesus Perez; Oliver D Howes; James M Stone; Paul Allen; Philip McGuire
Journal:  JAMA Psychiatry       Date:  2019-02-01       Impact factor: 21.596

Review 10.  Psychosis Risk and Development: What Do We Know From Population-Based Studies?

Authors:  Eva Mennigen; Carrie E Bearden
Journal:  Biol Psychiatry       Date:  2019-12-20       Impact factor: 13.382

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