Literature DB >> 30019850

Exploring the predictive power of the unspecific risk category of the Basel Screening Instrument for Psychosis.

David Peralta1,2, Erich Studerus1, Christina Andreou1, Katharina Beck1,3, Sarah Ittig1, Letizia Leanza1,3, Laura Egloff1,3, Anita Riecher-Rössler1.   

Abstract

AIM: Ultrahigh risk (UHR) criteria, consisting of brief limited intermittent psychotic symptoms (BLIPS), attenuated psychotic symptoms (APS) and genetic risk and deterioration (GRD) syndrome are the most widely used criteria for assessing the clinical high-risk state for psychosis (CHR-P). The Basel Screening Instrument for Psychosis (BSIP) includes a further risk category, the unspecific risk category (URC). However, little is known about the predictive power of this risk category compared to other risk categories.
METHODS: Two hundred CHR-P patients were detected as part of the Früherkennung von Psychosen (FePsy) study using the BSIP. Transition to psychosis was assessed in regular intervals for up to 7 years.
RESULTS: Patients meeting only the URC criterion (n = 40) had a significantly lower risk of transition to psychosis than the UHR group (including BLIPS, APS and GRD) (HR 0.19 [0.05; 0.80] (P = 0.024). Furthermore, the URC only risk group had a lower transition risk than the APS without BLIPS group (P = 0.015) and a trendwise lower risk than the BLIPS group (P = 0.066). However, despite the lower transition risk in the URC only group, there were still two patients (5%) in this group with a later transition to psychosis.
CONCLUSIONS: The URC includes patients who have a lower risk of transition than those included by the UHR categories and thereby increases the sensitivity of the BSIP. This offers the possibility of a stratified intervention, with these subjects receiving low intensity follow-up and treatment.
© 2018 John Wiley & Sons Australia, Ltd.

Entities:  

Keywords:  follow-up studies; prodromal symptoms; psychotic disorders; risk; sensitivity and specificity

Mesh:

Year:  2018        PMID: 30019850     DOI: 10.1111/eip.12719

Source DB:  PubMed          Journal:  Early Interv Psychiatry        ISSN: 1751-7885            Impact factor:   2.732


  2 in total

1.  Predictors of study drop-out and service disengagement in patients at clinical high risk for psychosis.

Authors:  Letizia Leanza; Erich Studerus; Amatya J Mackintosh; Katharina Beck; Leonie Seiler; Christina Andreou; Anita Riecher-Rössler
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2019-10-23       Impact factor: 4.328

2.  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

  2 in total

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