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March 11, 2020

Prevention of Psychosis: Advances in Detection, Prognosis, and Intervention

Author Affiliations
  • 1Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King's College London, London, United Kingdom
  • 2OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom
  • 3Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
  • 4Maudsley Biomedical Research Centre, National Institute for Health Research, South London and Maudsley NHS Foundation Trust, London, United Kingdom
  • 5Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Universidad Complutense, Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
  • 6The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, New York
  • 7The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, New York
  • 8Charité Universitätsmedizin Berlin, Department of Child and Adolescent Psychiatry, Berlin, Germany
  • 9Department of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York
  • 10Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
  • 11Centre for Therapeutic Innovation in Neuropsychiatry, Institut de Recherche Servier, Croissy sur Seine, Paris, France
  • 12Department of Psychiatry, University of Basel, Basel, Switzerland
  • 13Department of Psychiatry, Psychosomatics and Psychotherapy, University of Lübeck, Lübeck, Germany
  • 14Department of Psychiatry, University of Campania L. Vanvitelli, Naples, Italy
  • 15Department of Psychiatry, Psychotherapy and Psychosomatic Medicine with Early Intervention and Recognition Centre, Vivantes Klinikum Am Urban, Charité-Universitätsmedizin, Berlin, Germany
  • 16Vivantes Klinikum im Friedrichshain, Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, Charité-Universitätsmedizin, Berlin, Germany
  • 17Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
  • 18Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, Victoria, Australia
  • 19Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Medical Faculty, Technische Universität Dresden, Dresden, Germany
  • 20Copenhagen Affective Disorder Research Center, Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark
  • 21Department of Psychiatry and Neuropsychology, Maastricht University Medical Center School for Mental Health and Neuroscience, Maastricht, the Netherlands
  • 22Amsterdam University Medical Centers, Academic Medical Center, Department of Psychiatry, Amsterdam, the Netherlands
  • 23Department of Psychiatry and Psychotherapy, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
  • 24Center for Basics in NeuroModulation (NeuroModul), Medical Faculty, University of Freiburg, Germany
  • 25INSERM, IPNP UMR S1266, Laboratoire de Physiopathologie des Maladies Psychiatriques, Université Paris Descartes, Université de Paris, CNRS, GDR3557-Institut de Psychiatrie, Paris, France
  • 26Faculté de Médecine Paris Descartes, GHU Paris–Sainte-Anne, Service Hospitalo-Universitaire, Paris, France
  • 27University Hospital, Department of Psychiatry and Psychotherapy, Ludwig Maximilian University of Munich, Munich, Germany
  • 28Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King's College London, London, United Kingdom
  • 29Center for Psychiatric Neuroscience, Lausanne University Hospital, Lausanne-Prilly, Switzerland
JAMA Psychiatry. 2020;77(7):755-765. doi:10.1001/jamapsychiatry.2019.4779
Key Points

Question  What is the status of current clinical knowledge in the detection, prognosis, and interventions for individuals at risk of psychosis?

Findings  In this review of 42 meta-analyses encompassing 81 outcomes, detecting individuals at risk for psychosis required knowledge of their specific sociodemographic, clinical, functional, cognitive, and neurobiological characteristics, and predicting outcomes was achieved with good accuracy provided that assessment tools were used in clinical samples. Evidence for specific effective interventions for this patient population is currently insufficient.

Meaning  Findings of this review suggest that, although clinical research knowledge for psychosis prevention is substantial and detecting and formulating a prognosis in individuals at risk for psychosis are possible, further research is needed to identify specific effective interventions in individuals with sufficient risk enrichment.


Importance  Detection, prognosis, and indicated interventions in individuals at clinical high risk for psychosis (CHR-P) are key components of preventive psychiatry.

Objective  To provide a comprehensive, evidence-based systematic appraisal of the advancements and limitations of detection, prognosis, and interventions for CHR-P individuals and to formulate updated recommendations.

Evidence Review  Web of Science, Cochrane Central Register of Reviews, and Ovid/PsychINFO were searched for articles published from January 1, 2013, to June 30, 2019, to identify meta-analyses conducted in CHR-P individuals. MEDLINE was used to search the reference lists of retrieved articles. Data obtained from each article included first author, year of publication, topic investigated, type of publication, study design and number, sample size of CHR-P population and comparison group, type of comparison group, age and sex of CHR-P individuals, type of prognostic assessment, interventions, quality assessment (using AMSTAR [Assessing the Methodological Quality of Systematic Reviews]), and key findings with their effect sizes.

Findings  In total, 42 meta-analyses published in the past 6 years and encompassing 81 outcomes were included. For the detection component, CHR-P individuals were young (mean [SD] age, 20.6 [3.2] years), were more frequently male (58%), and predominantly presented with attenuated psychotic symptoms lasting for more than 1 year before their presentation at specialized services. CHR-P individuals accumulated several sociodemographic risk factors compared with control participants. Substance use (33% tobacco use and 27% cannabis use), comorbid mental disorders (41% with depressive disorders and 15% with anxiety disorders), suicidal ideation (66%), and self-harm (49%) were also frequently seen in CHR-P individuals. CHR-P individuals showed impairments in work (Cohen d = 0.57) or educational functioning (Cohen d = 0.21), social functioning (Cohen d = 1.25), and quality of life (Cohen d = 1.75). Several neurobiological and neurocognitive alterations were confirmed in this study. For the prognosis component, the prognostic accuracy of CHR-P instruments was good, provided they were used in clinical samples. Overall, risk of psychosis was 22% at 3 years, and the risk was the highest in the brief and limited intermittent psychotic symptoms subgroup (38%). Baseline severity of attenuated psychotic (Cohen d = 0.35) and negative symptoms (Cohen d = 0.39) as well as low functioning (Cohen d = 0.29) were associated with an increased risk of psychosis. Controlling risk enrichment and implementing sequential risk assessments can optimize prognostic accuracy. For the intervention component, no robust evidence yet exists to favor any indicated intervention over another (including needs-based interventions and control conditions) for preventing psychosis or ameliorating any other outcome in CHR-P individuals. However, because the uncertainty of this evidence is high, needs-based and psychological interventions should still be offered.

Conclusions and Relevance  This review confirmed recent substantial advancements in the detection and prognosis of CHR-P individuals while suggesting that effective indicated interventions need to be identified. This evidence suggests a need for specialized services to detect CHR-P individuals in primary and secondary care settings, to formulate a prognosis with validated psychometric instruments, and to offer needs-based and psychological interventions.

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1 Comment for this article
The "Psychotic Connectome"
Johanna Maria Catharina BLOM, Ph.D. | Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy1
The review by Fusar-Poli et al.[1], is the latest meta-analysis (umbrella review) aimed at offering an all-encompassing view of the current state of the art coming to the conclusion that early detection of young individuals at clinical high-risk for psychosis (CHR-P) may lead to its prevention. This confirms the general notion that genetic vulnerability is not enough and that the interaction with environmental factors, especially substance abuse (cannabis), early adverse events and urban living, enhance the risk of CHR-P. A multimodal approach is suggested. It requires evidence from different domains such as subtle neurocognitive disfunction and biomarkers as clinical predictors of the high-risk status. The analysis is exhaustive and the data show that psychosis does not need to be a chronic disease if signs indicating young individuals at heightened risk are detected early and preventive interventions are put into place in a timely manner, which is of the utmost importance. However, CHR-P young adults represent and enormously heterogenous group and currently identified risk factors lack the capacity to distinguish individual trajectories while no treatment modality has proved to prevent the development of full-blown psychosis. If all the distinct clinical pathways of CHR-P individuals are to be detected, then a paradigm shift is essential[2,3] by accumulating not a series of risk factors but constructing a dynamic network of interacting biological, genetic and psychosocial determinants to explain the individual behavior variances of these young patients[4,5]. Understanding individual behavior is extremely difficult as all behavior (and all traits) are inevitably the result of complex interactions (i.e., nature via nurture). The main challenge is not to understand the role of each factor and context but the relationships and connections among them. New conceptual thinking will result in increasingly explanatory and predictive models which may offer a more realistic image of the strengths and vulnerabilities of young adults at CHR-P by stressing the dynamic nature of these relationships which, incidentally, tend to change over time. This will not only indicate which domains and factors mostly influence the risk and are central to CHR-P but it will have important implications for clinical practice driving differential and personalized strategies in the prevention of psychosis. The “psychotic connectome” will help to recognize interrelated behaviors allowing to isolate the domain(s) most central to the overall risk, and distinguish different trajectories thus improving successful programs[6] fundamental to the surveillance and monitoring of personalized interventions.

1 Fusar-Poli P, Salazar de Pablo G, Correll CU, et al. JAMA Psychiatry. 2020;77(7):755–765. doi:10.1001/jamapsychiatry.2019.4779
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5 Isvoranu A-M, Guloksuz S, Epskamp S, van Os J, Borsboom D, GROUP
Psychological Medicine. 2020; 50:636–643. https://doi.org/10.1017/S003329171900045X.
6 Pani L, Keefe RSE. Schizophr Res Cogn. 2019;18: 100155. doi:10.1016/j.scog.2019.1001552019

Johanna MC Blom 1
Fabio Tascedda, 2 Dept Life Sci., Univ. Modena and Reggio Emilia
Luca Pani, 1, 3 Dept. Psychiatry and Behav. Sci., Univ. of Miami, Miami, 4 VeraSci, Durham, USA