A Stratified Model for Psychosis Prediction in Clinical Practice

Michel, Chantal; Ruhrmann, Stephan; Schimmelmann, Benno G.; Klosterkötter, Joachim; Schultze-Lutter, Frauke (2014). A Stratified Model for Psychosis Prediction in Clinical Practice. Schizophrenia bulletin, 40(6), pp. 1533-1542. Oxford University Press 10.1093/schbul/sbu025

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Objective: Impaired cognition is an important dimension in psychosis and its at-risk states. Research on the value of impaired cognition for psychosis prediction in at-risk samples, however, mainly relies on study-specific sample means of neurocognitive tests, which unlike widely available general test norms are difficult to translate into clinical practice. The aim of this study was to explore the combined predictive value of at-risk criteria and neurocognitive deficits according to test norms with a risk stratification approach. Method: Potential predictors of psychosis (neurocognitive deficits and at-risk criteria) over 24 months were investigated in 97 at-risk patients. Results: The final prediction model included (1) at-risk criteria (attenuated psychotic symptoms plus subjective cognitive disturbances) and (2) a processing speed deficit (digit symbol test). The model was stratified into 4 risk classes with hazard rates between 0.0 (both predictors absent) and 1.29 (both predictors present). Conclusions: The combination of a processing speed deficit and at-risk criteria provides an optimized stratified risk assessment. Based on neurocognitive test norms, the validity of our proposed 3 risk classes could easily be examined in independent at-risk samples and, pending positive validation results, our approach could easily be applied in clinical practice in the future.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > University Psychiatric Services > University Hospital of Child and Adolescent Psychiatry and Psychotherapy
04 Faculty of Medicine > University Psychiatric Services > University Hospital of Child and Adolescent Psychiatry and Psychotherapy > Research Division

UniBE Contributor:

Michel, Chantal; Schimmelmann, Benno Karl Edgar and Schultze-Lutter, Frauke

Subjects:

600 Technology > 610 Medicine & health
100 Philosophy > 150 Psychology

ISSN:

0586-7614

Publisher:

Oxford University Press

Language:

English

Submitter:

Myriam Pyrlik

Date Deposited:

11 Sep 2014 11:47

Last Modified:

26 Jun 2016 01:49

Publisher DOI:

10.1093/schbul/sbu025

PubMed ID:

24609300

Uncontrolled Keywords:

Prediction, Psychosis, Neurocognition, Processing speed, At-risk criteria, Risk estimation

BORIS DOI:

10.7892/boris.46868

URI:

https://boris.unibe.ch/id/eprint/46868

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