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Risk Prediction Models in Psychiatry: Toward a New Frontier for the Prevention of Mental Illnesses.

Published on May 24, 2017in The Journal of Clinical Psychiatry4.023
· DOI :10.4088/JCP.15r10003
Francesco Bernardini6
Estimated H-index: 6
(University of Perugia),
Luigi Attademo7
Estimated H-index: 7
(University of Perugia)
+ 4 AuthorsMichael T. Compton44
Estimated H-index: 44
(Hofstra University)
Abstract
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.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.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.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.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.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.
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#1Luca Cattelani (UNIBO: University of Bologna)H-Index: 4
#2Federico Chesani (UNIBO: University of Bologna)H-Index: 21
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#2Thiago Botter-Maio Rocha (UFRGS: Universidade Federal do Rio Grande do Sul)H-Index: 4
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#1Muhammad Asim (SYSU: Sun Yat-sen University)
#2Bo Hao (SYSU: Sun Yat-sen University)H-Index: 1
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#2Yanli Zhang-James (State University of New York Upstate Medical University)H-Index: 13
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