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Prog Neuropsychopharmacol Biol Psychiatry. 2008 Dec 12;32(8):1873-8. doi: 10.1016/j.pnpbp.2008.08.024. Epub 2008 Sep 9.

An integrated psychobiological predictive model of emergent psychopathology among young relatives at risk for schizophrenia.

Author information

  • 1Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA. sme12@pitt.edu

Abstract

OBJECTIVE:

Studies of young relatives at elevated risk for schizophrenia have pointed to the importance of a variety of neurobiological, cognitive, and clinical risk factors for the disorder; yet few have employed integrated models to estimate the joint contribution of these factors to heightened schizophrenic risk. We tested the predictive power of an integrated psychobiological model of schizophrenia risk to subsequent psychopathology development among young relatives at risk for the disorder.

METHODS:

Young first (n=66) and second (n=20) degree relatives of schizophrenia probands were followed for an average of 3 (SD=1.13) years to examine their trajectories toward psychopathology development. Neurobiologic, cognitive, and clinical measures were employed in an integrated structural equation model to estimate their contribution to the prospective emergence of psychopathology.

RESULTS:

Results indicated that neurobiological, neurocognitive, and psychosis proneness factors at baseline were all uniquely predictive of subsequent psychopathology development, and that an integrated model of psychopathology development that took into account these factors provided an excellent fit to the observed data. Subsequent classification analyses of model accuracy using likelihood ratios adjusting for the base-rate of psychopathology development in this sample revealed that individuals identified by this model had a 71% chance of developing psychopathology in the future.

CONCLUSIONS:

An integrated model of biobehavioral risk factors may provide a powerful method for predicting psychopathology and schizophrenia risk in at-risk samples. If validated, this model may be useful for early detection and intervention programs. Future research will need to focus particularly on predicting schizophrenia development and refining models to further enhance sensitivity.

PMID:
18812206
[PubMed - indexed for MEDLINE]
PMCID:
PMC2649961
Free PMC Article

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