Risk prediction models in psychiatry: Toward a new frontier for the prevention of mental illnesses

Francesco Bernardini, Luigi Attademo, Sean D. Cleary, Charles Luther, Ruth Shim, Roberto Quartesan, Michael T. Compton

Research output: Contribution to journalReview article

21 Citations (Scopus)

Abstract

Objective: We conducted a systematic, qualitative review of risk prediction models designed and tested for depression, bipolar disorder, generalized anxiety disorder, posttraumatic stress disorder, and psychotic disorders. Our aim was to understand the current state of research on risk prediction models for these 5 disorders and thus future directions as our field moves toward embracing prediction and prevention. Data Sources: Systematic searches of the entire MEDLINE electronic database were conducted independently by 2 of the authors (from 1960 through 2013) in July 2014 using defined search criteria. Search terms included risk prediction, predictive model, or prediction model combined with depression, bipolar, manic depressive, generalized anxiety, posttraumatic, PTSD, schizophrenia, or psychosis. Study Selection: We identified 268 articles based on the search terms and 3 criteria: published in English, provided empirical data (as opposed to review articles), and presented results pertaining to developing or validating a risk prediction model in which the outcome was the diagnosis of 1 of the 5 aforementioned mental illnesses. We selected 43 original research reports as a final set of articles to be qualitatively reviewed. Data Extraction: The 2 independent reviewers abstracted 3 types of data (sample characteristics, variables included in the model, and reported model statistics) and reached consensus regarding any discrepant abstracted information. Results: Twelve reports described models developed for prediction of major depressive disorder, 1 for bipolar disorder, 2 for generalized anxiety disorder, 4 for posttraumatic stress disorder, and 24 for psychotic disorders. Most studies reported on sensitivity, specificity, positive predictive value, negative predictive value, and area under the (receiver operating characteristic) curve. Conclusions: Recent studies demonstrate the feasibility of developing risk prediction models for psychiatric disorders (especially psychotic disorders). The field must now advance by (1) conducting more large-scale, longitudinal studies pertaining to depression, bipolar disorder, anxiety disorders, and other psychiatric illnesses; (2) replicating and carrying out external validations of proposed models; (3) further testing potential selective and indicated preventive interventions; and (4) evaluating effectiveness of such interventions in the context of risk stratification using risk prediction models.

Original languageEnglish (US)
Pages (from-to)572-583
Number of pages12
JournalJournal of Clinical Psychiatry
Volume78
Issue number5
DOIs
StatePublished - May 1 2017
Externally publishedYes

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Psychiatry
Bipolar Disorder
Psychotic Disorders
Post-Traumatic Stress Disorders
Anxiety Disorders
Depression
Information Storage and Retrieval
Feasibility Studies
MEDLINE
ROC Curve
Longitudinal Studies
Schizophrenia
Consensus
Anxiety
Databases
Sensitivity and Specificity
Research

ASJC Scopus subject areas

  • Psychiatry and Mental health

Cite this

Bernardini, F., Attademo, L., Cleary, S. D., Luther, C., Shim, R., Quartesan, R., & Compton, M. T. (2017). Risk prediction models in psychiatry: Toward a new frontier for the prevention of mental illnesses. Journal of Clinical Psychiatry, 78(5), 572-583. https://doi.org/10.4088/JCP.15r10003

Risk prediction models in psychiatry : Toward a new frontier for the prevention of mental illnesses. / Bernardini, Francesco; Attademo, Luigi; Cleary, Sean D.; Luther, Charles; Shim, Ruth; Quartesan, Roberto; Compton, Michael T.

In: Journal of Clinical Psychiatry, Vol. 78, No. 5, 01.05.2017, p. 572-583.

Research output: Contribution to journalReview article

Bernardini, F, Attademo, L, Cleary, SD, Luther, C, Shim, R, Quartesan, R & Compton, MT 2017, 'Risk prediction models in psychiatry: Toward a new frontier for the prevention of mental illnesses', Journal of Clinical Psychiatry, vol. 78, no. 5, pp. 572-583. https://doi.org/10.4088/JCP.15r10003
Bernardini, Francesco ; Attademo, Luigi ; Cleary, Sean D. ; Luther, Charles ; Shim, Ruth ; Quartesan, Roberto ; Compton, Michael T. / Risk prediction models in psychiatry : Toward a new frontier for the prevention of mental illnesses. In: Journal of Clinical Psychiatry. 2017 ; Vol. 78, No. 5. pp. 572-583.
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