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

Published on May 24, 2017in The Journal of Clinical Psychiatry4.02
· DOI :10.4088/JCP.15r10003
Francesco Bernardini6
Estimated H-index: 6
(University of Perugia),
Luigi Attademo6
Estimated H-index: 6
(University of Perugia)
+ 4 AuthorsMichael T. Compton42
Estimated H-index: 42
(Hofstra University)
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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Cited By13
Published on Feb 12, 2019in Scientific Reports4.01
Jin Hee Lee (Yonsei University), Ho Jang + 1 AuthorsSeongho Min4
Estimated H-index: 4
(Yonsei University)
Suicide is a leading cause of death among adolescents and a major public health concern. Here we developed a risk stratification model for adolescent suicide attempts using sociodemographic characteristics, risk behaviours and psychological variables. Participants were 247,222 subjects in the Korea Youth Risk Behavior Web-based Survey (KYRBS). We developed a suicide index based on the suicide risk estimated in the generalized linear model and proposed the risk stratification model using the R la...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Luca Cattelani3
Estimated H-index: 3
(UNIBO: University of Bologna),
M. Belvederi Murri17
Estimated H-index: 17
(UniGe: University of Genoa)
+ 3 AuthorsPierpaolo Palumbo4
Estimated H-index: 4
(UNIBO: University of Bologna)
Assessing the risk to develop a specific disease is the first step towards prevention, both at individual and population level. The development and validation of Risk Prediction Models (RPMs) is the norm within different fields of medicine but still underused in psychiatry, despite the global impact of mental disorders. In particular, there is a lack of RPMs to assess the risk of developing depression, the first worldwide cause of disability and harbinger of functional decline in old age. We pre...
Published on Aug 23, 2019in Neuroscience Bulletin
Muhammad Asim (SYSU: Sun Yat-sen University), Bo Hao1
Estimated H-index: 1
(SYSU: Sun Yat-sen University)
+ 5 AuthorsHu Zhao9
Estimated H-index: 9
(SYSU: Sun Yat-sen University)
Fear memories are critical for survival. Nevertheless, over-generalization of these memories, depicted by a failure to distinguish threats from safe stimuli, is typical in stress-related disorders. Previous studies have supported a protective role of ketamine against stress-induced depressive behavior. However, the effect of ketamine on fear generalization remains unclear. In this study, we investigated the effects of ketamine on fear generalization in a fear-generalized mouse model. The mice we...
Published on Jun 6, 2019in bioRxiv
Stephen V. Faraone162
Estimated H-index: 162
(State University of New York Upstate Medical University),
Yanli Zhang-James12
Estimated H-index: 12
(State University of New York Upstate Medical University)
+ 3 AuthorsHenrik Larsson45
Estimated H-index: 45
(KI: Karolinska Institutet)
Background: Children with attention-deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at-risk youth would help allocate scarce resources for prevention programs. Methods: Psychiatric and somatic diagnoses, family history of these disorders, measures of socioeconomic distress and information about birth complications were obtained from the national registers in Sweden for 19,787 children with ADHD born between 1989-1993. We trained ...
Published on May 27, 2019in Psychopharmacology3.42
Martin P. Paulus76
Estimated H-index: 76
(Yale University),
Wesley K. Thompson44
Estimated H-index: 44
(UCSD: University of California, San Diego)
Rationale The impact of neuroscience-based approaches for psychiatry on pragmatic clinical decision-making has been limited. Although neuroscience has provided insights into basic mechanisms of neural function, these insights have not improved the ability to generate better assessments, prognoses, diagnoses, or treatment of psychiatric conditions.
Published on Apr 1, 2019in Depression and Anxiety4.93
David Daniel Ebert30
Estimated H-index: 30
Claudia Buntrock9
Estimated H-index: 9
+ 9 AuthorsMatthew K. Nock70
Estimated H-index: 70
(Harvard University)
Background: Major depressive disorder (MDD) in college students is associated with substantial burden. Aims: To assess 1-year incidence of MDD among incoming freshmen and predictors of MDD-incidence in a representative sample of students. Method: Prospective cohort study of first-year college students (baseline: n = 2,519, 1-year follow-up: n = 958). Results: The incidence of MDD within the first year of college was 6.9% (SE = 0.8). The most important individual-level predictors of onset were pr...
Published on Mar 1, 2019in arXiv: Quantitative Methods
Eryu Xia5
Estimated H-index: 5
Yiqin Yu3
Estimated H-index: 3
+ 2 AuthorsWen Sun5
Estimated H-index: 5
Risk assessment services fulfil the task of generating a risk report from personal information and are developed for purposes like disease prognosis, resource utilization prioritization, and informing clinical interventions. A major component of a risk assessment service is a risk prediction model. For a model to be easily integrated into risk assessment services, efforts are needed to design a detailed development roadmap for the intended service at the time of model development. However, metho...
Published on Jan 1, 2019
Adarsh Tripathi8
Estimated H-index: 8
(King George's Medical University),
Kabir Garg1
Estimated H-index: 1
(National Institute of Mental Health and Neurosciences),
Afzal Javed1
Estimated H-index: 1
Psychiatric disorders are among the most common causes of disability and burden worldwide. It has been estimated by the World Health Organization that close to 450 million people worldwide suffer from some sort of psychiatric illness. Even though the psychiatric disorders are usually diagnosed in the early adulthood, it has been found that the usual age of onset is in teens, and then they persist into adulthood, causing major impairments. Thus prevention in mental health is of utmost importance....
Published on Dec 1, 2018in Journal of Neuroimmune Pharmacology3.87
Jingchun Chen1
Estimated H-index: 1
(UNLV: University of Nevada, Las Vegas),
Jian-shing Wu1
Estimated H-index: 1
(UNLV: University of Nevada, Las Vegas)
+ 2 AuthorsXiangning Chen1
Estimated H-index: 1
(UNLV: University of Nevada, Las Vegas)
Schizophrenia is genetically heterogeneous and comorbid with many conditions. In this study, we explored polygenic scores (PGSs) from genetically related conditions and traits to predict schizophrenia diagnosis using both logistic regression and deep neural network (DNN) models. We used the combined Molecular Genetics of Schizophrenia and Swedish Schizophrenia Case Control Study (MGS + SSCCS) data for training and testing the models, and used the Clinical Antipsychotic Trials for Intervention Ef...
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