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Feng C, Liu Q, Huang C, Li T, Wang L, Liu F, Eickhoff SB, Qu C. Common neural dysfunction of economic decision-making across psychiatric conditions. Neuroimage 2024; 294:120641. [PMID: 38735423 DOI: 10.1016/j.neuroimage.2024.120641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 04/29/2024] [Accepted: 05/09/2024] [Indexed: 05/14/2024] Open
Abstract
Adaptive decision-making, which is often impaired in various psychiatric conditions, is essential for well-being. Recent evidence has indicated that decision-making capacity in multiple tasks could be accounted for by latent dimensions, enlightening the question of whether there is a common disruption of brain networks in economic decision-making across psychiatric conditions. Here, we addressed the issue by combining activation/lesion network mapping analyses with a transdiagnostic brain imaging meta-analysis. Our findings indicate that there were transdiagnostic alterations in the thalamus and ventral striatum during the decision or outcome stage of decision-making. The identified regions represent key nodes in a large-scale network, which is composed of multiple heterogeneous brain regions and plays a causal role in motivational functioning. The findings suggest that disturbances in the network associated with emotion- and reward-related processing play a key role in dysfunctions of decision-making observed in various psychiatric conditions. This study provides the first meta-analytic evidence of common neural alterations linked to deficits in economic decision-making.
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Affiliation(s)
- Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China; School of Psychology, South China Normal University, Guangzhou, 510631, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China.
| | - Qingxia Liu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China; School of Psychology, South China Normal University, Guangzhou, 510631, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Chuangbing Huang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China; School of Psychology, South China Normal University, Guangzhou, 510631, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Ting Li
- Institute of Brain and Psychological Science, Sichuan Normal University, Chengdu, 610066, China
| | - Li Wang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China; School of Psychology, South China Normal University, Guangzhou, 510631, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Feilong Liu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China; School of Psychology, South China Normal University, Guangzhou, 510631, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, 52428, Germany
| | - Chen Qu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China; School of Psychology, South China Normal University, Guangzhou, 510631, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China.
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Arribas M, Oliver D, Patel R, Kornblum D, Shetty H, Damiani S, Krakowski K, Provenzani U, Stahl D, Koutsouleris N, McGuire P, Fusar-Poli P. A transdiagnostic prodrome for severe mental disorders: an electronic health record study. Mol Psychiatry 2024:10.1038/s41380-024-02533-5. [PMID: 38710907 DOI: 10.1038/s41380-024-02533-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 03/08/2024] [Accepted: 03/13/2024] [Indexed: 05/08/2024]
Abstract
Effective prevention of severe mental disorders (SMD), including non-psychotic unipolar mood disorders (UMD), non-psychotic bipolar mood disorders (BMD), and psychotic disorders (PSY), rely on accurate knowledge of the duration, first presentation, time course and transdiagnosticity of their prodromal stages. Here we present a retrospective, real-world, cohort study using electronic health records, adhering to RECORD guidelines. Natural language processing algorithms were used to extract monthly occurrences of 65 prodromal features (symptoms and substance use), grouped into eight prodromal clusters. The duration, first presentation, and transdiagnosticity of the prodrome were compared between SMD groups with one-way ANOVA, Cohen's f and d. The time course (mean occurrences) of prodromal clusters was compared between SMD groups with linear mixed-effects models. 26,975 individuals diagnosed with ICD-10 SMD were followed up for up to 12 years (UMD = 13,422; BMD = 2506; PSY = 11,047; median[IQR] age 39.8[23.7] years; 55% female; 52% white). The duration of the UMD prodrome (18[36] months) was shorter than BMD (26[35], d = 0.21) and PSY (24[38], d = 0.18). Most individuals presented with multiple first prodromal clusters, with the most common being non-specific ('other'; 88% UMD, 85% BMD, 78% PSY). The only first prodromal cluster that showed a medium-sized difference between the three SMD groups was positive symptoms (f = 0.30). Time course analysis showed an increase in prodromal cluster occurrences approaching SMD onset. Feature occurrence across the prodromal period showed small/negligible differences between SMD groups, suggesting that most features are transdiagnostic, except for positive symptoms (e.g. paranoia, f = 0.40). Taken together, our findings show minimal differences in the duration and first presentation of the SMD prodromes as recorded in secondary mental health care. All the prodromal clusters intensified as individuals approached SMD onset, and all the prodromal features other than positive symptoms are transdiagnostic. These results support proposals to develop transdiagnostic preventive services for affective and psychotic disorders detected in secondary mental healthcare.
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Affiliation(s)
- Maite Arribas
- Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
| | - Dominic Oliver
- Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- NIHR Oxford Health Biomedical Research Centre, Oxford, OX3 7JX, UK
- OPEN Early Detection Service, Oxford Health NHS Foundation Trust, Oxford, OX3 7JX, UK
| | - Rashmi Patel
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | | | - Hitesh Shetty
- NIHR Maudsley Biomedical Research Centre, London, UK
| | - Stefano Damiani
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Kamil Krakowski
- Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Umberto Provenzani
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Daniel Stahl
- NIHR Maudsley Biomedical Research Centre, London, UK
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 8AF, UK
| | - Nikolaos Koutsouleris
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Max-Planck Institute of Psychiatry, Munich, Germany
| | - Philip McGuire
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- NIHR Oxford Health Biomedical Research Centre, Oxford, OX3 7JX, UK
- OPEN Early Detection Service, Oxford Health NHS Foundation Trust, Oxford, OX3 7JX, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Outreach and Support in South-London (OASIS) Service, South London and Maudsley (SLaM) NHS Foundation Trust, London, SE11 5DL, UK
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Pini S, Milrod B, Baldwin DS, Schiele MA, Massimetti G, Costa B, Martini C, Bandelow B, Domschke K, Abelli M. The relationship of separation anxiety with the age of onset of panic disorder. Early Interv Psychiatry 2023; 17:1172-1179. [PMID: 37051643 DOI: 10.1111/eip.13419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 01/16/2023] [Accepted: 03/28/2023] [Indexed: 04/14/2023]
Abstract
AIM This study aimed to investigate whether separation anxiety (SA) constitutes a dimension related to age at onset of panic disorder (PD), in homogeneous subgroups of outpatients with PD, based on their age of onset and symptom severity. METHODS A sample of 232 outpatients with PD was assessed with the Panic Disorder Severity Scale (PDSS) and the Sheehan Disability Scale (SDS) for functional impairments. Separation anxiety was evaluated using structured interviews and questionnaires. We applied a K-Means Cluster Analysis based on the standardized "PD age of onset" and "the PDSS total score" to identify distinct but homogeneous groups. RESULTS We identified three groups of patients: group 1 ("PD early onset/severe", N = 97, 42%, onset 23.2 ± 6.7 years), group 2 ("PD early onset/not severe", N = 76, 33%, onset 23.4 ± 6.0 years) and group 3 ("PD adult onset/not severe", N = 59, 25%, onset 42.8 ± 7.0 years). Patients with early onset/severe PD had significantly higher scores on all SA measures than PD late-onset/not severe. Regression analyses showed that SA scores, but not PDSS scores, were predictive of impairment in SDS work/school, social life, and family functioning domains. CONCLUSIONS Our data indicate a significant relationship between SA and PD with an earlier age of onset and an impact on individual functioning. This may have important implications for implementing preventive interventions targeting early risk factors for the subsequent onset of PD.
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Affiliation(s)
- Stefano Pini
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Barbara Milrod
- Albert Einstein College of Medicine, PRIME, (Psychiatric Research Institute of Montefiore Einstein), New York, New York, USA
| | - David S Baldwin
- Clinical and Experimental Sciences, Faculty of Medicine, Academic Centre, College Keep, University of Southampton, Southampton, UK
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Miriam A Schiele
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Gabriele Massimetti
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Barbara Costa
- Department of Pharmacy, University of Pisa, Pisa, Italy
| | | | - Borwin Bandelow
- Department of Psychiatry and Psychotherapy, University Medical Center Gottingen, Göttingen, Germany
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center for Basics in NeuroModulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Marianna Abelli
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
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Goerigk S, Reinhard MA, Barton BB, Burkhardt G, Ehring T, Bertsch K, Amann BL, Sarubin N, Seidl E, Falkai P, Musil R, Jobst A, Padberg F. Transdiagnostic analysis of adverse childhood experiences and their association with psychopathology-A TRANS-D conform study. Psychiatry Res 2023; 329:115545. [PMID: 37879200 DOI: 10.1016/j.psychres.2023.115545] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 10/08/2023] [Accepted: 10/14/2023] [Indexed: 10/27/2023]
Abstract
Transdiagnostic approaches challenge traditional psychiatric classification systems. Adverse childhood experiences (ACE) represent a transdiagnostic risk factor for psychopathology with dose dependency. As different qualities of ACE typically co-occur, we identified ACE patterns to assess their power for predicting psychopathology compared to traditional diagnoses. Following TRANS-D guidelines, we categorized participants (N=360) with persistent depressive disorder (PDD), borderline personality disorder (BPD), or healthy control status (HC) into subcategories defined by ACE pattern, using the Childhood Trauma Questionnaire (CTQ). Improvement of the transdiagnostic vs. diagnostic approach in predicting psychopathology was evaluated in a cross-validated predictive modeling framework focusing on the clinical sample of PDD and BPD patients. Results were externally validated in another transdiagnostic sample (N=138). Seven pattern-based subcategories with distinct ACE profiles were identified in the primary sample and replicated in the validation sample. Patterns cut across diagnostic groups. Predictive modeling showed that diagnoses could not predict depressive symptoms and loneliness. Transdiagnostic constructs systematically predicted all measures. This study showcases ACE as a promising construct for transdiagnostic research. Our data-driven framework identified robust ACE subcategories mapping onto general and interpersonal psychopathology. Patterns of CTQ-based information may provide an approach to integrating information on co-occurring ACE to inform diagnostics and treatment.
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Affiliation(s)
- Stephan Goerigk
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; Department of Psychological Methodology and Assessment, Ludwig-Maximilians-University, Leopoldstrasse 13, Munich 80802, Germany; Charlotte Fresenius Hochschule, Infanteriestrasse 11A, Munich 80797, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany.
| | - Matthias A Reinhard
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany
| | - Barbara B Barton
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany
| | - Gerrit Burkhardt
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany
| | - Thomas Ehring
- DZPG (German Center for Mental Health), Partner Site, Munich, Germany; Department of Psychology, Ludwig-Maximilians-University, Leopoldstrasse 13, Munich 80802, Germany
| | - Katja Bertsch
- DZPG (German Center for Mental Health), Partner Site, Munich, Germany; Department of Psychology, Ludwig-Maximilians-University, Leopoldstrasse 13, Munich 80802, Germany
| | - Benedikt L Amann
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany; Centre Fòrum Research Unit, Parc De Salut Mar, IMIM (Hospital del Mar Medical Research Institute), Pompeu Fabra University, Barcelona, Spain; Instituto Carlos III, CIBERSAM, Madrid, Spain
| | - Nina Sarubin
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; Department of Psychological Methodology and Assessment, Ludwig-Maximilians-University, Leopoldstrasse 13, Munich 80802, Germany; Charlotte Fresenius Hochschule, Infanteriestrasse 11A, Munich 80797, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany
| | - Elias Seidl
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany; Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, Ludwig-Maximilians-University, Lindwurmstrasse 4, Munich 80337, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany; Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, Munich 80804, Germany
| | - Richard Musil
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany
| | - Andrea Jobst
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany
| | - Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Nussbaumstrasse 7, Munich 80336, Germany; DZPG (German Center for Mental Health), Partner Site, Munich, Germany
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Uher R, Pavlova B, Radua J, Provenzani U, Najafi S, Fortea L, Ortuño M, Nazarova A, Perroud N, Palaniyappan L, Domschke K, Cortese S, Arnold PD, Austin JC, Vanyukov MM, Weissman MM, Young AH, Hillegers MH, Danese A, Nordentoft M, Murray RM, Fusar‐Poli P. Transdiagnostic risk of mental disorders in offspring of affected parents: a meta-analysis of family high-risk and registry studies. World Psychiatry 2023; 22:433-448. [PMID: 37713573 PMCID: PMC10503921 DOI: 10.1002/wps.21147] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/17/2023] Open
Abstract
The offspring of parents with mental disorders are at increased risk for developing mental disorders themselves. The risk to offspring may extend transdiagnostically to disorders other than those present in the parents. The literature on this topic is vast but mixed. To inform targeted prevention and genetic counseling, we performed a comprehensive, PRISMA 2020-compliant meta-analysis. We systematically searched the literature published up to September 2022 to retrieve original family high-risk and registry studies reporting on the risk of mental disorders in offspring of parents with any type of mental disorder. We performed random-effects meta-analyses of the relative risk (risk ratio, RR) and absolute risk (lifetime, up to the age at assessment) of mental disorders, defined according to the ICD or DSM. Cumulative incidence by offspring age was determined using meta-analytic Kaplan-Meier curves. We measured heterogeneity with the I2 statistic, and risk of bias with the Quality In Prognosis Studies (QUIPS) tool. Sensitivity analyses addressed the impact of study design (family high-risk vs. registry) and specific vs. transdiagnostic risks. Transdiagnosticity was appraised with the TRANSD criteria. We identified 211 independent studies that reported data on 3,172,115 offspring of parents with psychotic, bipolar, depressive, disruptive, attention-deficit/hyperactivity, anxiety, substance use, eating, obsessive-compulsive, and borderline personality disorders, and 20,428,575 control offspring. The RR and lifetime risk of developing any mental disorder were 3.0 and 55% in offspring of parents with anxiety disorders; 2.6 and 17% in offspring of those with psychosis; 2.1 and 55% in offspring of those with bipolar disorder; 1.9 and 51% in offspring of those with depressive disorders; and 1.5 and 38% in offspring of those with substance use disorders. The offspring's RR and lifetime risk of developing the same mental disorder diagnosed in their parent were 8.4 and 32% for attention-deficit/hyperactivity disorder; 5.8 and 8% for psychosis; 5.1 and 5% for bipolar disorder; 2.8 and 9% for substance use disorders; 2.3 and 14% for depressive disorders; 2.3 and 1% for eating disorders; and 2.2 and 31% for anxiety disorders. There were 37 significant transdiagnostic associations between parental mental disorders and the RR of developing a different mental disorder in the offspring. In offspring of parents with psychosis, bipolar and depressive disorder, the risk of the same disorder onset emerged at 16, 5 and 6 years, and cumulated to 3%, 19% and 24% by age 18; and to 8%, 36% and 46% by age 28. Heterogeneity ranged from 0 to 0.98, and 96% of studies were at high risk of bias. Sensitivity analyses restricted to prospective family high-risk studies confirmed the pattern of findings with similar RR, but with greater absolute risks compared to analyses of all study types. This study demonstrates at a global, meta-analytic level that offspring of affected parents have strongly elevated RR and lifetime risk of developing any mental disorder as well as the same mental disorder diagnosed in the parent. The transdiagnostic risks suggest that offspring of parents with a range of mental disorders should be considered as candidates for targeted primary prevention.
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Affiliation(s)
- Rudolf Uher
- Dalhousie UniversityDepartment of PsychiatryHalifaxNSCanada
- Nova Scotia Health AuthorityHalifaxNSCanada
| | - Barbara Pavlova
- Dalhousie UniversityDepartment of PsychiatryHalifaxNSCanada
- Nova Scotia Health AuthorityHalifaxNSCanada
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Instituto de Salud Carlos IIIUniversity of BarcelonaBarcelonaSpain
| | - Umberto Provenzani
- Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly
| | - Sara Najafi
- Dalhousie UniversityDepartment of PsychiatryHalifaxNSCanada
- Nova Scotia Health AuthorityHalifaxNSCanada
| | - Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Instituto de Salud Carlos IIIUniversity of BarcelonaBarcelonaSpain
| | - Maria Ortuño
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Instituto de Salud Carlos IIIUniversity of BarcelonaBarcelonaSpain
| | - Anna Nazarova
- Dalhousie UniversityDepartment of PsychiatryHalifaxNSCanada
- Nova Scotia Health AuthorityHalifaxNSCanada
| | - Nader Perroud
- Service of Psychiatric Specialties, Department of PsychiatryUniversity Hospitals of GenevaGenevaSwitzerland
- Department of PsychiatryUniversity of GenevaGenevaSwitzerland
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of PsychiatryMcGill UniversityMontrealQBCanada
- Robarts Research InstituteWestern UniversityLondonONCanada
- Department of Medical BiophysicsWestern UniversityLondonONCanada
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center, Faculty of MedicineUniversity of FreiburgFreiburgGermany
| | - Samuele Cortese
- School of Psychology, and Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of MedicineUniversity of SouthamptonSouthamptonUK
- Solent NHS TrustSouthamptonUK
- Division of Psychiatry and Applied PsychologyUniversity of NottinghamNottinghamUK
- Hassenfeld Children's Hospital at NYU LangoneNew YorkNYUSA
| | - Paul D. Arnold
- Mathison Centre for Mental Health Research & EducationUniversity of CalgaryCalgaryALCanada
| | - Jehannine C. Austin
- Departments of Psychiatry and Medical GeneticsUniversity of British ColumbiaVancouverBCCanada
| | - Michael M. Vanyukov
- Departments of Pharmaceutical Sciences, Psychiatry, and Human GeneticsUniversity of PittsburghPittsburghPAUSA
| | - Myrna M. Weissman
- Department of Psychiatry, Vagelos College of Physicians and SurgeonsColumbia UniversityNew YorkNYUSA
- Division of Translational EpidemiologyNew York State Psychiatric InstituteNew YorkNYUSA
- Mailman School of Public HealthColumbia UniversityNew YorkNYUSA
| | - Allan H. Young
- Centre for Affective Disorders, Institute of Psychiatry, Psychology, and NeuroscienceKing's College LondonLondonUK
| | - Manon H.J. Hillegers
- Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center, Sophia Children's HospitalRotterdamThe Netherlands
| | - Andrea Danese
- Social, Genetic and Developmental Psychiatry Centre and Department of Child and Adolescent PsychiatryInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- National and Specialist CAMHS Clinic for Trauma, Anxiety, and DepressionSouth London and Maudsley NHS Foundation TrustLondonUK
| | - Merete Nordentoft
- Copenhagen Research Center for Mental Health, Mental Health ServicesCapital Region of DenmarkCopenhagenDenmark
- Department of Clinical Medicine, Faculty of Health SciencesUniversity of CopenhagenCopenhagenDenmark
| | - Robin M. Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Paolo Fusar‐Poli
- Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly
- Early Psychosis: Intervention and Clinical‐detection (EPIC) lab, Department of Psychosis StudiesKing's College LondonLondonUK
- Outreach and Support in South‐London (OASIS) NHS Foundation Trust, South London and Maudsley NHS Foundation TrustLondonUK
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6
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Dragioti E, Radua J, Solmi M, Gosling CJ, Oliver D, Lascialfari F, Ahmed M, Cortese S, Estradé A, Arrondo G, Gouva M, Fornaro M, Batiridou A, Dimou K, Tsartsalis D, Carvalho AF, Shin JI, Berk M, Stringhini S, Correll CU, Fusar-Poli P. Impact of mental disorders on clinical outcomes of physical diseases: an umbrella review assessing population attributable fraction and generalized impact fraction. World Psychiatry 2023; 22:86-104. [PMID: 36640414 PMCID: PMC9840513 DOI: 10.1002/wps.21068] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/25/2022] [Indexed: 01/15/2023] Open
Abstract
Empirical evidence indicates a significant bidirectional association between mental disorders and physical diseases, but the prospective impact of men-tal disorders on clinical outcomes of physical diseases has not been comprehensively outlined. In this PRISMA- and COSMOS-E-compliant umbrella review, we searched PubMed, PsycINFO, Embase, and Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports, up to March 15, 2022, to identify systematic reviews with meta-analysis that examined the prospective association between any mental disorder and clinical outcomes of physical diseases. Primary outcomes were disease-specific mortality and all-cause mortality. Secondary outcomes were disease-specific incidence, functioning and/or disability, symptom severity, quality of life, recurrence or progression, major cardiac events, and treatment-related outcomes. Additional inclusion criteria were further applied to primary studies. Random effect models were employed, along with I2 statistic, 95% prediction intervals, small-study effects test, excess significance bias test, and risk of bias (ROBIS) assessment. Associations were classified into five credibility classes of evidence (I to IV and non-significant) according to established criteria, complemented by sensitivity and subgroup analyses to examine the robustness of the main analysis. Statistical analysis was performed using a new package for conducting umbrella reviews (https://metaumbrella.org). Population attributable fraction (PAF) and generalized impact fraction (GIF) were then calculated for class I-III associations. Forty-seven systematic reviews with meta-analysis, encompassing 251 non-overlapping primary studies and reporting 74 associations, were included (68% were at low risk of bias at the ROBIS assessment). Altogether, 43 primary outcomes (disease-specific mortality: n=17; all-cause mortality: n=26) and 31 secondary outcomes were investigated. Although 72% of associations were statistically significant (p<0.05), only two showed convincing (class I) evidence: that between depressive disorders and all-cause mortality in patients with heart failure (hazard ratio, HR=1.44, 95% CI: 1.26-1.65), and that between schizophrenia and cardiovascular mortality in patients with cardiovascular diseases (risk ratio, RR=1.54, 95% CI: 1.36-1.75). Six associations showed highly suggestive (class II) evidence: those between depressive disorders and all-cause mortality in patients with diabetes mellitus (HR=2.84, 95% CI: 2.00-4.03) and with kidney failure (HR=1.41, 95% CI: 1.31-1.51); that between depressive disorders and major cardiac events in patients with myocardial infarction (odds ratio, OR=1.52, 95% CI: 1.36-1.70); that between depressive disorders and dementia in patients with diabetes mellitus (HR=2.11, 95% CI: 1.77-2.52); that between alcohol use disorder and decompensated liver cirrhosis in patients with hepatitis C (RR=3.15, 95% CI: 2.87-3.46); and that between schizophrenia and cancer mortality in patients with cancer (standardized mean ratio, SMR=1.74, 95% CI: 1.41-2.15). Sensitivity/subgroup analyses confirmed these results. The largest PAFs were 30.56% (95% CI: 27.67-33.49) for alcohol use disorder and decompensated liver cirrhosis in patients with hepatitis C, 26.81% (95% CI: 16.61-37.67) for depressive disorders and all-cause mortality in patients with diabetes mellitus, 13.68% (95% CI: 9.87-17.58) for depressive disorders and major cardiac events in patients with myocardial infarction, 11.99% (95% CI: 8.29-15.84) for schizophrenia and cardiovascular mortality in patients with cardiovascular diseases, and 11.59% (95% CI: 9.09-14.14) for depressive disorders and all-cause mortality in patients with kidney failure. The GIFs confirmed the preventive capacity of these associations. This umbrella review demonstrates that mental disorders increase the risk of a poor clinical outcome in several physical diseases. Prevention targeting mental disorders - particularly alcohol use disorders, depressive disorders, and schizophrenia - can reduce the incidence of adverse clinical outcomes in people with physical diseases. These findings can inform clinical practice and trans-speciality preventive approaches cutting across psychiatric and somatic medicine.
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Affiliation(s)
- Elena Dragioti
- Pain and Rehabilitation Centre and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Research Laboratory Psychology of Patients, Families and Health Professionals, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Joaquim Radua
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Imaging of Mood- and Anxiety-Related Disorders Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer, CIBERSAM, University of Barcelona, Barcelona, Spain
- Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden
| | - Marco Solmi
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada
- Department of Mental Health, Ottawa Hospital, Ottawa, ON, Canada
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Corentin J Gosling
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- DysCo Lab, Paris Nanterre University, Nanterre, France
- Laboratoire de Psychopathologie et Processus de Santé, Université Paris Cité, Boulogne-Billancourt, France
| | - Dominic Oliver
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Filippo Lascialfari
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Muhammad Ahmed
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, and Solent NHS Trust, Southampton, UK
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
- Hassenfeld Children's Hospital at NYU Langone, New York, NY, USA
| | - Andrés Estradé
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Gonzalo Arrondo
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Mind-Brain Group, Institute for Culture and Society, University of Navarra, Pamplona, Spain
| | - Mary Gouva
- Research Laboratory Psychology of Patients, Families and Health Professionals, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Michele Fornaro
- Section of Psychiatry, Department of Neuroscience, Reproductive Science and Odontostomatology, Federico II University of Naples, Naples, Italy
| | - Agapi Batiridou
- Research Laboratory Psychology of Patients, Families and Health Professionals, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Konstantina Dimou
- Research Laboratory Psychology of Patients, Families and Health Professionals, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | | | - Andre F Carvalho
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine and Barwon Health, Deakin University, Geelong, VIC, Australia
| | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea
- Department of Pediatrics, Severance Children's Hospital, Seoul, South Korea
| | - Michael Berk
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine and Barwon Health, Deakin University, Geelong, VIC, Australia
| | - Silvia Stringhini
- Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland
- University Centre for General Medicine and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Health and Community Medicine, University of Geneva, Geneva, Switzerland
| | - Christoph U Correll
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
- Department of Psychiatry, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
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7
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Hogg B, Gardoki-Souto I, Valiente-Gómez A, Rosa AR, Fortea L, Radua J, Amann BL, Moreno-Alcázar A. Psychological trauma as a transdiagnostic risk factor for mental disorder: an umbrella meta-analysis. Eur Arch Psychiatry Clin Neurosci 2022; 273:397-410. [PMID: 36208317 DOI: 10.1007/s00406-022-01495-5] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 09/27/2022] [Indexed: 01/08/2023]
Abstract
This umbrella review is the first to systematically examine psychological trauma as a transdiagnostic risk factor across psychiatric conditions. We searched Pubmed, Scopus, and PsycNET databases from inception until 01/05/2021 for systematic reviews/meta-analyses evaluating the association between psychological trauma and at least one diagnosed mental disorder. We re-calculated the odds ratio (OR), then classified the association as convincing, highly suggestive, suggestive, or weak, based on the number of cases and controls with and without psychological trauma, random-effects p value, the 95% confidence interval of the largest study, heterogeneity between studies, 95% prediction interval, small-study effect, and excess significance bias. Additional outcomes were the association between specific trauma types and specific mental disorders, and a sensitivity analysis for childhood trauma. Transdiagnosticity was assessed using TRANSD criteria. The review was pre-registered in Prospero CRD42020157308 and followed PRISMA/MOOSE guidelines. Fourteen reviews met inclusion criteria, comprising 16,277 cases and 77,586 controls. Psychological trauma met TRANSD criteria as a transdiagnostic factor across different diagnostic criteria and spectra. There was highly suggestive evidence of an association between psychological trauma at any time-point and any mental disorder (OR = 2.92) and between childhood trauma and any mental disorder (OR = 2.90). Regarding specific trauma types, convincing evidence linked physical abuse (OR = 2.36) and highly suggestive evidence linked sexual abuse (OR = 3.47) with a range of mental disorders, and convincing evidence linked emotional abuse to anxiety disorders (OR = 3.05); there were no data for emotional abuse with other disorders. These findings highlight the importance of preventing early traumatic events and providing trauma-informed care in early intervention and psychiatric services.
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Affiliation(s)
- Bridget Hogg
- Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction (INAD), Parc de Salut Mar, C/Llull 410, 08019, Barcelona, Spain.,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain.,PhD Programme, Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain
| | - Itxaso Gardoki-Souto
- Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction (INAD), Parc de Salut Mar, C/Llull 410, 08019, Barcelona, Spain.,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain.,PhD Programme, Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Alicia Valiente-Gómez
- Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction (INAD), Parc de Salut Mar, C/Llull 410, 08019, Barcelona, Spain.,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain
| | - Adriane Ribeiro Rosa
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brazil.,Department of Pharmacology, Federal University of Rio Grande Do Sul (UFRGS), Porto Alegre, RS, Brazil.,Postgraduate Program in Psychiatry and Behavioral Sciences, Federal University of Rio Grande Do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Lydia Fortea
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain.,Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain.,Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Joaquim Radua
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain.,Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain.,Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, King's College London, Psychology & Neuroscience, London, UK.,Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Benedikt L Amann
- Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction (INAD), Parc de Salut Mar, C/Llull 410, 08019, Barcelona, Spain. .,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain. .,Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain. .,Department of Psychiatry and Psychotherapy, Klinikum Der Universität München, Munich, Germany.
| | - Ana Moreno-Alcázar
- Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction (INAD), Parc de Salut Mar, C/Llull 410, 08019, Barcelona, Spain.,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain
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8
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Feng C, Huang W, Xu K, Stewart JL, Camilleri JA, Yang X, Wei P, Gu R, Luo W, Eickhoff SB. Neural substrates of motivational dysfunction across neuropsychiatric conditions: Evidence from meta-analysis and lesion network mapping. Clin Psychol Rev 2022; 96:102189. [PMID: 35908312 PMCID: PMC9720091 DOI: 10.1016/j.cpr.2022.102189] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 04/13/2022] [Accepted: 07/18/2022] [Indexed: 02/03/2023]
Abstract
Motivational dysfunction constitutes one of the fundamental dimensions of psychopathology cutting across traditional diagnostic boundaries. However, it is unclear whether there is a common neural circuit responsible for motivational dysfunction across neuropsychiatric conditions. To address this issue, the current study combined a meta-analysis on psychiatric neuroimaging studies of reward/loss anticipation and consumption (4308 foci, 438 contrasts, 129 publications) with a lesion network mapping approach (105 lesion cases). Our meta-analysis identified transdiagnostic hypoactivation in the ventral striatum (VS) for clinical/at-risk conditions compared to controls during the anticipation of both reward and loss. Moreover, the VS subserves a key node in a distributed brain network which encompasses heterogeneous lesion locations causing motivation-related symptoms. These findings do not only provide the first meta-analytic evidence of shared neural alternations linked to anticipatory motivation-related deficits, but also shed novel light on the role of VS dysfunction in motivational impairments in terms of both network integration and psychological functions. Particularly, the current findings suggest that motivational dysfunction across neuropsychiatric conditions is rooted in disruptions of a common brain network anchored in the VS, which contributes to motivational salience processing rather than encoding positive incentive values.
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Affiliation(s)
- Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education (South China Normal University), Guangzhou, China,Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China,Corresponding authors at: Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China; Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China. (C. Feng), (R. Gu)
| | - Wenhao Huang
- Beijing Key Laboratory of Learning and Cognition, and School of Psychology, Capital Normal University, Beijing, China,Department of Decision Neuroscience and Nutrition, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke, Germany
| | - Kangli Xu
- The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
| | | | - Julia A. Camilleri
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Xiaofeng Yang
- The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
| | - Ping Wei
- Beijing Key Laboratory of Learning and Cognition, and School of Psychology, Capital Normal University, Beijing, China
| | - Ruolei Gu
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China,Corresponding authors at: Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China; Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China. (C. Feng), (R. Gu)
| | - Wenbo Luo
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, China
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
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9
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Arrondo G, Solmi M, Dragioti E, Eudave L, Ruiz-Goikoetxea M, Ciaurriz-Larraz AM, Magallon S, Carvalho AF, Cipriani A, Fusar-Poli P, Larsson H, Correll CU, Cortese S. Associations between mental and physical conditions in children and adolescents: An umbrella review. Neurosci Biobehav Rev 2022; 137:104662. [PMID: 35427644 DOI: 10.1016/j.neubiorev.2022.104662] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 04/02/2022] [Accepted: 04/08/2022] [Indexed: 12/20/2022]
Abstract
We mapped the evidence on the type and strength of associations between a broad range of mental and physical conditions in children and adolescents, by carrying out an umbrella review, i.e., a quantitative synthesis of previous systematic reviews and meta-analyses. We also assessed to which extent the links between mental and physical conditions vary across disorders or, by contrast, are transdiagnostic. Based on a pre-established protocol, we retained 45 systematic reviews/meta-analyses, encompassing around 12.5 million of participants. In analyses limited to the most rigorous estimates, we found evidence for the following associations: ADHD-asthma, ADHD-obesity, and depression-asthma. A transdiagnostic association was confirmed between asthma and anxiety/ASD/depression/bipolar disorder, between obesity and ADHD/ASD/depression, and between dermatitis and ASD/ADHD. We conclude that obesity and allergic conditions are likely to be associated with mental disorders in children and adolescents. Our results can help clinicians explore potential links between mental and physical conditions in children/adolescent and provide a road map for future studies aimed at shading light on the underlying factors.
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Affiliation(s)
- Gonzalo Arrondo
- Mind-Brain Group, Institute for Culture and Society, University of Navarra, Pamplona, Spain; Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK.
| | - Marco Solmi
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK; Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada; Department of Mental Health, The Ottawa Hospital, Ottawa, ON, Canada; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Elena Dragioti
- Pain and Rehabilitation Centre and Department of Health, Medicine and Caring Sciences, Linköping University, Linkoping, Sweden; Research Laboratory Psychology of Patients, Families & Health Professionals, Department of Nursing, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Luis Eudave
- Faculty of Education and Psychology, University of Navarra, Pamplona, Spain
| | | | | | - Sara Magallon
- Faculty of Education and Psychology, University of Navarra, Pamplona, Spain
| | - Andre F Carvalho
- Innovation in Mental and Physical Health and Clinical Treatment (IMPACT) Strategic Research Centre, Deakin University, Geelong, VIC, Australia
| | - Andrea Cipriani
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK; OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Christoph U Correll
- The Zucker Hillside Hospital, Division of Psychiatry Research, Northwell Health, Glen Oaks, New York, NY, USA; Department of Psychiatry and Molecular Medicine, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, New York, NY, USA; Department of Child and Adolescent Psychiatry, Charité Universitäts medizin, Berlin, Germany
| | - Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK; Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK; Solent NHS Trust, Southampton, UK; Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK; Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York City, NY, US
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10
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Solmi M, Radua J, Olivola M, Croce E, Soardo L, Salazar de Pablo G, Il Shin J, Kirkbride JB, Jones P, Kim JH, Kim JY, Carvalho AF, Seeman MV, Correll CU, Fusar-Poli P. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Mol Psychiatry 2022; 27:281-295. [PMID: 34079068 PMCID: PMC8960395 DOI: 10.1038/s41380-021-01161-7] [Citation(s) in RCA: 861] [Impact Index Per Article: 430.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 04/28/2021] [Accepted: 05/05/2021] [Indexed: 02/06/2023]
Abstract
Promotion of good mental health, prevention, and early intervention before/at the onset of mental disorders improve outcomes. However, the range and peak ages at onset for mental disorders are not fully established. To provide robust, global epidemiological estimates of age at onset for mental disorders, we conducted a PRISMA/MOOSE-compliant systematic review with meta-analysis of birth cohort/cross-sectional/cohort studies, representative of the general population, reporting age at onset for any ICD/DSM-mental disorders, identified in PubMed/Web of Science (up to 16/05/2020) (PROSPERO:CRD42019143015). Co-primary outcomes were the proportion of individuals with onset of mental disorders before age 14, 18, 25, and peak age at onset, for any mental disorder and across International Classification of Diseases 11 diagnostic blocks. Median age at onset of specific disorders was additionally investigated. Across 192 studies (n = 708,561) included, the proportion of individuals with onset of any mental disorders before the ages of 14, 18, 25 were 34.6%, 48.4%, 62.5%, and peak age was 14.5 years (k = 14, median = 18, interquartile range (IQR) = 11-34). For diagnostic blocks, the proportion of individuals with onset of disorder before the age of 14, 18, 25 and peak age were as follows: neurodevelopmental disorders: 61.5%, 83.2%, 95.8%, 5.5 years (k = 21, median=12, IQR = 7-16), anxiety/fear-related disorders: 38.1%, 51.8%, 73.3%, 5.5 years (k = 73, median = 17, IQR = 9-25), obsessive-compulsive/related disorders: 24.6%, 45.1%, 64.0%, 14.5 years (k = 20, median = 19, IQR = 14-29), feeding/eating disorders/problems: 15.8%, 48.1%, 82.4%, 15.5 years (k = 11, median = 18, IQR = 15-23), conditions specifically associated with stress disorders: 16.9%, 27.6%, 43.1%, 15.5 years (k = 16, median = 30, IQR = 17-48), substance use disorders/addictive behaviours: 2.9%, 15.2%, 48.8%, 19.5 years (k = 58, median = 25, IQR = 20-41), schizophrenia-spectrum disorders/primary psychotic states: 3%, 12.3%, 47.8%, 20.5 years (k = 36, median = 25, IQR = 20-34), personality disorders/related traits: 1.9%, 9.6%, 47.7%, 20.5 years (k = 6, median = 25, IQR = 20-33), and mood disorders: 2.5%, 11.5%, 34.5%, 20.5 years (k = 79, median = 31, IQR = 21-46). No significant difference emerged by sex, or definition of age of onset. Median age at onset for specific mental disorders mapped on a time continuum, from phobias/separation anxiety/autism spectrum disorder/attention deficit hyperactivity disorder/social anxiety (8-13 years) to anorexia nervosa/bulimia nervosa/obsessive-compulsive/binge eating/cannabis use disorders (17-22 years), followed by schizophrenia, personality, panic and alcohol use disorders (25-27 years), and finally post-traumatic/depressive/generalized anxiety/bipolar/acute and transient psychotic disorders (30-35 years), with overlap among groups and no significant clustering. These results inform the timing of good mental health promotion/preventive/early intervention, updating the current mental health system structured around a child/adult service schism at age 18.
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Affiliation(s)
- Marco Solmi
- grid.5608.b0000 0004 1757 3470Neurosciences Department, University of Padua, Padua, Italy ,grid.5608.b0000 0004 1757 3470Neuroscience Centre, University of Padua, Padua, Italy ,grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Joaquim Radua
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.10403.360000000091771775Imaging Mood- and Anxiety-Related Disorders (IMARD) group, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Mental Health Research Networking Center (CIBERSAM), Barcelona, Spain ,grid.465198.7Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Solna, Sweden
| | - Miriam Olivola
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Enrico Croce
- grid.8484.00000 0004 1757 2064Department of Biomedical and Specialty Surgical Sciences, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Livia Soardo
- grid.8982.b0000 0004 1762 5736Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Gonzalo Salazar de Pablo
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.13097.3c0000 0001 2322 6764Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.4795.f0000 0001 2157 7667Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), CIBERSAM, Madrid, Spain
| | - Jae Il Shin
- grid.15444.300000 0004 0470 5454Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea
| | - James B. Kirkbride
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Peter Jones
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Cambridge, England ,CAMEO Early Intervention Service, Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, England
| | - Jae Han Kim
- grid.15444.300000 0004 0470 5454Yonsei University College of Medicine, Seoul, South Korea
| | - Jong Yeob Kim
- grid.15444.300000 0004 0470 5454Yonsei University College of Medicine, Seoul, South Korea
| | - Andrè F. Carvalho
- grid.414257.10000 0004 0540 0062IMPACT (Innovation in Mental and Physical Health and Clinical Treatment) Strategic Research Centre, School of Medicine, Barwon Health, Deakin University, Geelong, VIC, Australia
| | - Mary V. Seeman
- grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Christoph U. Correll
- grid.440243.50000 0004 0453 5950Department of Psychiatry, Zucker Hillside Hospital, Glen Oaks, NY USA ,grid.512756.20000 0004 0370 4759Department of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY USA ,grid.250903.d0000 0000 9566 0634Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY USA ,grid.6363.00000 0001 2218 4662Department of Child and Adolescent Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Paolo Fusar-Poli
- Department of Psychosis Studies, Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. .,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. .,OASIS service, South London and Maudsley NHS Foundation Trust, London, UK. .,National Institute for Health Research, Maudsley Biomedical Research Centre, London, UK.
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11
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Fusar-Poli P, Salazar de Pablo G, Rajkumar RP, López-Díaz Á, Malhotra S, Heckers S, Lawrie SM, Pillmann F. Diagnosis, prognosis, and treatment of brief psychotic episodes: a review and research agenda. Lancet Psychiatry 2022; 9:72-83. [PMID: 34856200 DOI: 10.1016/s2215-0366(21)00121-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 03/01/2021] [Accepted: 03/18/2021] [Indexed: 12/25/2022]
Abstract
Brief psychotic episodes represent an intriguing paradox in clinical psychiatry because they elude the standard knowledge that applies to the persisting psychotic disorders such as schizophrenia. This Review describes key diagnostic considerations such as conceptual foundations, current psychiatric classification versus research-based operationalisations, epidemiology, and sociocultural variations; prognostic aspects including the risk of psychosis recurrence, types of psychotic recurrences, other clinical outcomes, prognostic factors; and therapeutic issues such as treatment guidelines and unmet need of care. The advances and challenges associated with the scientific evidence are used to set a research agenda in this area. We conclude that brief psychotic episodes can be reconceptualised within a clinical staging model to promote innovative translational research and improve our understanding and treatment of psychotic disorders.
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Affiliation(s)
- Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
| | - Gonzalo Salazar de Pablo
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, London, UK; Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón, CIBERSAM, Madrid, Spain
| | - Ravi Philip Rajkumar
- Department of Psychiatry, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
| | - Álvaro López-Díaz
- University Hospital Virgen Macarena, Seville, Spain; Institute of Biomedicine of Seville, Seville, Spain
| | | | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Frank Pillmann
- WO Center of Psychiatry, Halle, Germany; Martin Luther University, Halle-Wittenberg, Germany
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12
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Cascino G, Marciello F, Abbate-Daga G, Balestrieri M, Bertelli S, Carpiniello B, Corrivetti G, Favaro A, Renna C, Ricca V, Salvo P, Segura-Garcia C, Todisco P, Volpe U, Zeppegno P, Monteleone P, Monteleone AM. How Is the History of Early Traumatic Exposure Associated With the Psychopathological Outcomes of COVID-19 Related Lockdown and Subsequent Re-opening in People With Eating Disorders? Front Psychiatry 2021; 12:789344. [PMID: 34955933 PMCID: PMC8692284 DOI: 10.3389/fpsyt.2021.789344] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 11/15/2021] [Indexed: 12/14/2022] Open
Abstract
The negative impact of COVID-19 pandemic on people with Eating Disorders (EDs) has been documented. The aim of this study was to evaluate whether a history of traumatic experiences during childhood or adolescence was associated with a higher degree of psychopathological worsening during COVID-19 related lockdown and in the following re-opening period in this group of people. People with EDs undergoing a specialist ED treatment in different Italian services before the spreading of COVID-19 pandemic (n = 312) filled in an online survey to retrospectively evaluate ED specific and general psychopathology changes after COVID-19 quarantine. Based on the presence of self-reported traumatic experiences, the participants were split into three groups: patients with EDs and no traumatic experiences, patients with EDs and childhood traumatic experiences, patients with EDs and adolescent traumatic experiences. Both people with or without early traumatic experiences reported retrospectively a worsening of general and ED-specific psychopathology during the COVID 19-induced lockdown and in the following re-opening period. Compared to ED participants without early traumatic experiences, those with a self-reported history of early traumatic experiences reported heightened anxious and post-traumatic stress symptoms, ineffectiveness, body dissatisfaction, and purging behaviors. These differences were seen before COVID-19 related restrictions as well as during the lockdown period and after the easing of COVID-19 related restrictions. In line with the "maltreated ecophenotype" theory, these results may suggest a clinical vulnerability of maltreated people with EDs leading to a greater severity in both general and ED-specific symptomatology experienced during the exposure to the COVID-19 pandemic.
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Affiliation(s)
- Giammarco Cascino
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Salerno, Italy
| | - Francesca Marciello
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Salerno, Italy
| | - Giovanni Abbate-Daga
- Department of Neuroscience, Eating Disorders Center for Treatment and Research, University of Turin, Turin, Italy
| | | | - Sara Bertelli
- Department of Mental Health, ASST Santi Paolo e Carlo, Milan, Italy
| | - Bernardo Carpiniello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | | | - Angela Favaro
- Department of Neuroscience, University of Padova, Padua, Italy
| | - Caterina Renna
- Mental Health Department, Center for the Treatment and Research on Eating Disorders, ASL Lecce, Lecce, Italy
| | - Valdo Ricca
- Psychiatry Unit, Department of Neurological and Psychiatric Sciences, University of Florence, Florence, Italy
| | - Pierandrea Salvo
- Eating Disorders Centre Portogruaro, AULSS 4 Veneto Orientale, San Donà di Piave, Italy
| | - Cristina Segura-Garcia
- Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Patrizia Todisco
- Eating Disorders Unit, Casa di Cura “Villa Margherita”, Arcugnano, Italy
| | - Umberto Volpe
- Section of Clinical Psychiatry, Department of Clinical Neurosciences/DIMSC, Università Politecnica delle Marche, Ancona, Italy
| | - Patrizia Zeppegno
- Department of Translational Medicine, Psychiatry Institute, Università del Piemonte Orientale, Novara, Italy
| | - Palmiero Monteleone
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Salerno, Italy
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13
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Provenzani U, Salazar de Pablo G, Arribas M, Pillmann F, Fusar-Poli P. Clinical outcomes in brief psychotic episodes: a systematic review and meta-analysis. Epidemiol Psychiatr Sci 2021; 30:e71. [PMID: 35698876 PMCID: PMC8581951 DOI: 10.1017/s2045796021000548] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 09/23/2021] [Accepted: 09/24/2021] [Indexed: 12/25/2022] Open
Abstract
AIMS Patients with brief psychotic episodes (BPE) have variable and fluctuating clinical outcomes which challenge psychiatric care. Our meta-analysis aims at providing a comprehensive summary of several clinical outcomes in this patient group. METHODS A multistep systematic PRISMA/MOOSE-compliant literature search was performed for articles published from inception until 1st March 2021. Web of Science database was searched, complemented by manual search of original articles reporting relevant outcomes (psychotic recurrence, prospective diagnostic change or stability, remission, quality of life, functional status, mortality and their predictors) for patients diagnosed with acute and transient psychotic disorders (ATPD), brief psychotic disorders (BPD), brief intermittent psychotic symptoms (BIPS) and brief limited intermittent psychotic symptoms (BLIPS). Random-effects methods and Q-statistics were employed, quality assessment with Newcastle-Ottawa Scale, assessment of heterogeneity with I2 index, sensitivity analyses (acute polymorphic psychotic disorders, APPD) and multiple meta-regressions, assessment of publication bias with funnel plot, Egger's test and meta-regression (psychotic recurrence and sample size). RESULTS A total of 91 independent articles (n = 94 samples) encompassed 37 ATPD, 24 BPD, 19 BLIPS and 14 BIPS samples, totalling 15 729 individuals (mean age: 30.89 ± 7.33 years, mean female ratio: 60%, 59% conducted in Europe). Meta-analytical risk of psychotic recurrence for all BPE increased from 15% (95% confidence interval (CI) 12-18) at 6 months, 25% (95% CI 22-30) at 12 months, 30% (95% CI 27-33) at 24 months and 33% (95% CI 30-37) at ⩾36 months follow-up, with no differences between ATPD, BPD, BLIPS and BIPS after 2 years of follow-up. Across all BPE, meta-analytical proportion of prospective diagnostic stability (average follow-up 47 months) was 49% (95% CI 42-56); meta-analytical proportion of diagnostic change (average follow-up 47 months) to schizophrenia spectrum psychoses was 19% (95% CI 16-23), affective spectrum psychoses 5% (95% CI 3-7), other psychotic disorders 7% (95% CI 5-9) and other (non-psychotic) mental disorders 14% (95% CI 11-17). Prospective diagnostic change within APPD without symptoms of schizophrenia was 34% (95% CI 24-46) at a mean follow-up of 51 months: 18% (95% CI 11-30) for schizophrenia spectrum psychoses and 17% (95% CI 10-26) for other (non-psychotic) mental disorders. Meta-analytical proportion of baseline employment was 48% (95% CI 38-58), whereas there were not enough data to explore the other outcomes. Heterogeneity was high; female ratio and study quality were negatively and positively associated with risk of psychotic recurrence, respectively. There were no consistent factor predicting clinical outcomes. CONCLUSIONS Short-lived psychotic episodes are associated with a high risk of psychotic recurrences, in particular schizophrenia spectrum disorders. Other clinical outcomes remain relatively underinvestigated. There are no consistent prognostic/predictive factors.
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Affiliation(s)
- U. Provenzani
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - G. Salazar de Pablo
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - M. Arribas
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - F. Pillmann
- AWO Center of Psychatry, Halle, Germany
- Martin Luther University Halle-Wittenberg, Halle, Germany
| | - P. Fusar-Poli
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Outreach and Support in South London (OASIS) service, South London and Maudsley NHS Foundation Trust, London, UK
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14
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Giordano GM. Worldwide initiatives aimed to train professionals in the use of the ICD-11. Ann Gen Psychiatry 2021; 20:49. [PMID: 34727935 PMCID: PMC8561919 DOI: 10.1186/s12991-021-00370-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Accepted: 09/04/2021] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND The chapter on mental disorders of the 11th revision of the International Classification of Diseases (ICD-11) has been now finalized. Training of mental health professionals in the use of the chapter is taking place worldwide. Information is provided on the ICD-11 training courses taking place recently, including that co-organized by the Naples World Health Organization (WHO) Collaborating Centre on Research and Training in Mental Health and the European Psychiatric Association; those which will be held in the next few months, such as the one co-organized by the World Psychiatric Association and the Global Mental Health Academy, to be held online from 8 to 29 November 2021; and the training course set up by the WHO Collaborating Centre on Mental Health at the Columbia University, in collaboration with the WHO Department of Mental Health and Substance Use, which can be accessed only by the members of the WHO Global Clinical Practice Network. CONCLUSION Psychiatrists of all countries of the world are encouraged to become familiar with the ICD-11 chapter on mental disorders, which will be adopted shortly by most countries worldwide.
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Affiliation(s)
- Giulia M Giordano
- WHO Collaborating Centre for Research and Training in Mental Health, University of Campania L. Vanvitelli, Naples, Italy.
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15
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Arango C, Dragioti E, Solmi M, Cortese S, Domschke K, Murray RM, Jones PB, Uher R, Carvalho AF, Reichenberg A, Shin JI, Andreassen OA, Correll CU, Fusar-Poli P. Risk and protective factors for mental disorders beyond genetics: an evidence-based atlas. World Psychiatry 2021; 20:417-436. [PMID: 34505386 PMCID: PMC8429329 DOI: 10.1002/wps.20894] [Citation(s) in RCA: 121] [Impact Index Per Article: 40.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Decades of research have revealed numerous risk factors for mental disorders beyond genetics, but their consistency and magnitude remain uncer-tain. We conducted a "meta-umbrella" systematic synthesis of umbrella reviews, which are systematic reviews of meta-analyses of individual studies, by searching international databases from inception to January 1, 2021. We included umbrella reviews on non-purely genetic risk or protective factors for any ICD/DSM mental disorders, applying an established classification of the credibility of the evidence: class I (convincing), class II (highly suggestive), class III (suggestive), class IV (weak). Sensitivity analyses were conducted on prospective studies to test for temporality (reverse causation), TRANSD criteria were applied to test transdiagnosticity of factors, and A Measurement Tool to Assess Systematic Reviews (AMSTAR) was employed to address the quality of meta-analyses. Fourteen eligible umbrella reviews were retrieved, summarizing 390 meta-analyses and 1,180 associations between putative risk or protective factors and mental disorders. We included 176 class I to III evidence associations, relating to 142 risk/protective factors. The most robust risk factors (class I or II, from prospective designs) were 21. For dementia, they included type 2 diabetes mellitus (risk ratio, RR from 1.54 to 2.28), depression (RR from 1.65 to 1.99) and low frequency of social contacts (RR=1.57). For opioid use disorders, the most robust risk factor was tobacco smoking (odds ratio, OR=3.07). For non-organic psychotic disorders, the most robust risk factors were clinical high risk state for psychosis (OR=9.32), cannabis use (OR=3.90), and childhood adversities (OR=2.80). For depressive disorders, they were widowhood (RR=5.59), sexual dysfunction (OR=2.71), three (OR=1.99) or four-five (OR=2.06) metabolic factors, childhood physical (OR=1.98) and sexual (OR=2.42) abuse, job strain (OR=1.77), obesity (OR=1.35), and sleep disturbances (RR=1.92). For autism spectrum disorder, the most robust risk factor was maternal overweight pre/during pregnancy (RR=1.28). For attention-deficit/hyperactivity disorder (ADHD), they were maternal pre-pregnancy obesity (OR=1.63), maternal smoking during pregnancy (OR=1.60), and maternal overweight pre/during pregnancy (OR=1.28). Only one robust protective factor was detected: high physical activity (hazard ratio, HR=0.62) for Alzheimer's disease. In all, 32.9% of the associations were of high quality, 48.9% of medium quality, and 18.2% of low quality. Transdiagnostic class I-III risk/protective factors were mostly involved in the early neurodevelopmental period. The evidence-based atlas of key risk and protective factors identified in this study represents a benchmark for advancing clinical characterization and research, and for expanding early intervention and preventive strategies for mental disorders.
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Affiliation(s)
- Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Health Research Institute (IiGSM), School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
- Biomedical Research Center for Mental Health (CIBERSAM), Madrid, Spain
| | - Elena Dragioti
- Pain and Rehabilitation Centre and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Marco Solmi
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Neuroscience, University of Padua, Padua, Italy
- Department of Psychiatry, University of Ottawa and Department of Mental Health, Ottawa Hospital, Ottawa, ON, Canada
| | - Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
- Hassenfeld Children's Hospital at NYU Langone, New York, NY, USA
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center and Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center for Basics in NeuroModulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Robin M Murray
- Department of Psychosis Studies, King's College London, London, UK
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- CAMEO Early Intervention Service, Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, UK
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Nova Scotia Health, Halifax, NS, Canada
- IWK Health Centre, Halifax, NS, Canada
- Department of Medical Neuroscience, Dalhousie University, Halifax, NS, Canada
| | - Andre F Carvalho
- IMPACT Strategic Research Centre, School of Medicine, Barwon Health, Deakin University, Geelong, VIC, Australia
- Department of Psychiatry, University of Toronto, and Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Abraham Reichenberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Seaver Center for Autism Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jae Ii Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea
- Department of Pediatrics, Severance Children's Hospital, Seoul, South Korea
| | - Ole A Andreassen
- NORMENT - Institute of Clinical Medicine, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Christoph U Correll
- Department of Psychiatry, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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16
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Schirmbeck F, van der Burg NC, Blankers M, Vermeulen JM, McGuire P, Valmaggia LR, Kempton MJ, van der Gaag M, Riecher-Rössler A, Bressan RA, Barrantes-Vidal N, Nelson B, Amminger GP, McGorry P, Pantelis C, Krebs MO, Ruhrmann S, Sachs G, Rutten BPF, van Os J, Nordentoft M, Glenthøj B, Fusar-Poli P, de Haan L. Impact of Comorbid Affective Disorders on Longitudinal Clinical Outcomes in Individuals at Ultra-high Risk for Psychosis. Schizophr Bull 2021; 48:100-110. [PMID: 34417795 PMCID: PMC8781381 DOI: 10.1093/schbul/sbab088] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Diagnoses of anxiety and/or depression are common in subjects at Ultra-High Risk for Psychosis (UHR) and associated with extensive functional impairment. Less is known about the impact of affective comorbidities on the prospective course of attenuated psychotic symptoms (APS). METHOD Latent class mixed modelling identified APS trajectories in 331 UHR subjects assessed at baseline, 6, 12, and 24 months follow-up. The prognostic value of past, baseline, and one-year DSM-IV depressive or anxiety disorders on trajectories was investigated using logistic regression, controlling for confounders. Cox proportional hazard analyses investigated associations with transition risk. RESULTS 46.8% of participants fulfilled the criteria for a past depressive disorder, 33.2% at baseline, and 15.1% at one-year follow-up. Any past, baseline, or one-year anxiety disorder was diagnosed in 42.9%, 37.2%, and 27.0%, respectively. Participants were classified into one of three latent APS trajectory groups: (1) persistently low, (2) increasing, and (3) decreasing. Past depression was associated with a higher risk of belonging to the increasing trajectory group, compared to the persistently low (OR = 3.149, [95%CI: 1.298-7.642]) or decreasing group (OR = 3.137, [1.165-8.450]). In contrast, past (OR = .443, [.179-1.094]) or current (OR = .414, [.156-1.094]) anxiety disorders showed a trend-level association with a lower risk of belonging to the increasing group compared to the persistently low group. Past depression was significantly associated with a higher risk of transitioning to psychosis (HR = 2.123, [1.178-3.828]). CONCLUSION A past depressive episode might be a particularly relevant risk factor for an unfavorable course of APS in UHR individuals. Early affective disturbances may be used to advance detection, prognostic, and clinical strategies.
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Affiliation(s)
- Frederike Schirmbeck
- Department of Psychiatry, Amsterdam University Medical Center, Meibergdreef, University of Amsterdam, Amsterdam, the Netherlands,Arkin Institute for Mental Health, Amsterdam, the Netherlands,To whom correspondence should be addressed; Meibergdreef 5, 1105 AZ, Amsterdam, the Netherlands; tel: (0)20 8913639, fax: (0)20 8913702, e-mail:
| | - Nadine C van der Burg
- Department of Psychiatry, Amsterdam University Medical Center, Meibergdreef, University of Amsterdam, Amsterdam, the Netherlands,GGZ Centraal, Amersfoort, the Netherlands
| | - Matthijs Blankers
- Department of Psychiatry, Amsterdam University Medical Center, Meibergdreef, University of Amsterdam, Amsterdam, the Netherlands,Arkin Institute for Mental Health, Amsterdam, the Netherlands,Trimbos Institute, Institute of Mental Health and Addiction, Utrecht, the Netherlands
| | - Jentien M Vermeulen
- Department of Psychiatry, Amsterdam University Medical Center, Meibergdreef, University of Amsterdam, Amsterdam, the Netherlands
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Lucia R Valmaggia
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Mark van der Gaag
- Department of Clinical Psychology, Faculty of Behavioural and Movement Sciences, Amsterdam Public Mental Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands,Psychosis Research Institute, Parnassia Group, The Hague, the Netherlands
| | | | - Rodrigo A Bressan
- Depto Psiquiatria, Escola Paulista de Medicina, LiNC-Lab Interdisciplinar Neurociências Clínicas, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
| | - Neus Barrantes-Vidal
- Departament de Psicologia Clínica i de la Salut, Universitat Autònoma de Barcelona, Barcelona, Spain,Fundació Sanitària Sant Pere Claver, Spanish Mental Health Research Network (CIBERSAM), Spain
| | - Barnaby Nelson
- Orygen, Parkville, Victoria, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | | | - Patrick McGorry
- Orygen, Parkville, Victoria, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Christos Pantelis
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne & Melbourne Health, Carlton South, Victoria, Australia
| | - Marie-Odile Krebs
- University of Paris, GHU-Paris, Sainte-Anne, C’JAAD, Inserm U1266, Institut de Psychiatrie (CNRS 3557), Paris, France
| | - Stephan Ruhrmann
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Gabriele Sachs
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Jim van Os
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands,Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Merete Nordentoft
- Mental Health Center Copenhagen and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Center Glostrup, Mental Health Services in the Capital Region of Copenhagen, University of Copenhagen, Copenhagen, Denmark
| | - Birte Glenthøj
- Centre for Neuropsychiatric Schizophrenia Research (CNSR) & Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | | | - Paolo Fusar-Poli
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy,Department of Psychosis Studies, Early Psychosis: Intervention and Clinical-detection (EPIC) Lab, Institute of Psychiatry Psychology & Neuroscience, King’s College London, London, UK
| | - Lieuwe de Haan
- Department of Psychiatry, Amsterdam University Medical Center, Meibergdreef, University of Amsterdam, Amsterdam, the Netherlands,Arkin Institute for Mental Health, Amsterdam, the Netherlands
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17
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Van Everdingen C, Bob Peerenboom P, Van Der Velden K, Delespaul PAEG. A Comprehensive Assessment to Enable Recovery of the Homeless: The HOP-TR Study. Front Public Health 2021; 9:661517. [PMID: 34307275 PMCID: PMC8299205 DOI: 10.3389/fpubh.2021.661517] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 06/09/2021] [Indexed: 12/24/2022] Open
Abstract
Background: Homelessness is an increasing problem in Western European countries. In the Netherlands, policy reforms and austerity measures induced an urgent need for management information on local homeless citizens. Municipal authorities initiated cross-sectional reviews of Homeless Service (HS) users. The resulting Homeless People Treatment and Recovery (HOP-TR) study developed a health and needs assessment strategy over different domains to comprehensively assess individuals and care networks with the perspective on recovery. Methods: Dutch HS users were selected using a naturalistic meta-snowball sampling. Semi-structured interviews provided the primary data source. The interview content was partly derived from the InterRAI Community Mental Health questionnaire and the “Homelessness Supplement.” Using the raw interview data, algorithmic summary scores were computed and integrating clinical parameters assessed. The data describe health and needs in a rights-based, recovery-oriented frame of reference. The mental health approach is transdiagnostic. The positive health framework is used for structuring health and needs aspects in relation to the symptomatic (physical and mental health), social (daily living, social participation), and personal (quality of life, meaning) dimensions of recovery. Results: Recruitment (between 2015 and 2017) resulted in a saturated sample of 436 HS users in 16 facilities and seven cities. Most participants were long-term or intermittently homeless. The sample characteristics reveal the multi domain character of needs and the relevance of a broad, comprehensive approach. Local authorities used the reports to reflect and discuss needs, care provision, access, and network cooperation. These dialogs incited to improve the quality of care at various ecosystem levels. Discussion: This paper describes new recruitment strategies and data collections of comprehensive data domains, to improve our knowledge in the field of homelessness. Traditional epidemiological literature on homelessness is often domain specific and relies on administrative sources. The HOP-TR study uses an analytical epidemiological approach. It shifts the assessment focus from problem-centered marginalization processes toward a comprehensive, three-dimensional recovery-oriented vision of health. Different perspectives are integrated to explore the interaction of homeless people with care networks.
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Affiliation(s)
- Coline Van Everdingen
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, Netherlands
| | | | - Koos Van Der Velden
- Department of Primary and Community Care, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Philippe A E G Delespaul
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, Netherlands.,Department of Adult Psychiatry, Mondriaan Mental Health Trust, Heerlen, Netherlands
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18
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Solmi M, Radua J, Stubbs B, Ricca V, Moretti D, Busatta D, Carvalho AF, Dragioti E, Favaro A, Monteleone AM, Shin JI, Fusar-Poli P, Castellini G. Risk factors for eating disorders: an umbrella review of published meta-analyses. ACTA ACUST UNITED AC 2021; 43:314-323. [PMID: 32997075 PMCID: PMC8136381 DOI: 10.1590/1516-4446-2020-1099] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 06/12/2020] [Indexed: 02/07/2023]
Abstract
Objective: To grade the evidence about risk factors for eating disorders (anorexia nervosa, bulimia nervosa, and binge eating disorder) with an umbrella review approach. Methods: This was a systematic review of observational studies on risk factors for eating disorders published in PubMed/PsycInfo/Embase until December 11th, 2019. We recalculated random-effect meta-analyses, heterogeneity, small-study effect, excess significance bias and 95% prediction intervals, grading significant evidence (p < 0.05) from convincing to weak according to established criteria. Quality was assessed with the Assessment of Multiple Systematic Reviews 2 (AMSTAR-2) tool. Results: Of 2,197 meta-analyses, nine were included, providing evidence on 50 risk factors, 29,272 subjects with eating disorders, and 1,679,385 controls. Although no association was supported by convincing evidence, highly suggestive evidence supported the association between childhood sexual abuse and bulimia nervosa (k = 29, 1,103 cases with eating disorders, 8,496 controls, OR, 2.73, 95%CI 1.96-3.79, p = 2.1 x 10-9, AMSTAR-2 moderate quality) and between appearance-related teasing victimization and any eating disorder (k = 10, 1,341 cases with eating disorders, 3,295 controls, OR 2.91, 95%CI 2.05-4.12, p = 1.8x10-9, AMSTAR-2 moderate quality). Suggestive, weak, or no evidence supported 11, 29, and 8 associations, respectively. Conclusions: The most credible evidence indicates that early traumatic and stressful events are risk factors for eating disorders. Larger collaborative prospective cohort studies are needed to identify risk factors for eating disorders, particularly anorexia nervosa.
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Affiliation(s)
- Marco Solmi
- Dipartimento di Neuroscienze, Università di Padova, Padova, Italy.,Padua Neuroscience Center, Università di Padova, Padova, Italy.,Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Joaquim Radua
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Barcelona, Spain.,Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Brendon Stubbs
- Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, United Kingdom.,Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Positive Ageing Research Institute, Anglia Ruskin University, Cambridge, United Kingdom
| | - Valdo Ricca
- Unità di Psichiatria, Dipartimento Scienze della Salute, Università degli studi di Firenze, Firenze, Italy
| | - Davide Moretti
- Unità di Psichiatria, Dipartimento Scienze della Salute, Università degli studi di Firenze, Firenze, Italy
| | - Daniele Busatta
- Unità di Psichiatria, Dipartimento Scienze della Salute, Università degli studi di Firenze, Firenze, Italy
| | - Andre F Carvalho
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Elena Dragioti
- Pain and Rehabilitation Center, Department of Medicine and Health Sciences, Linköping University, Linköping, Sweden
| | - Angela Favaro
- Dipartimento di Neuroscienze, Università di Padova, Padova, Italy.,Padua Neuroscience Center, Università di Padova, Padova, Italy
| | | | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,OASIS Service, South London and Maudsley NHS Foundation Trust, London, United Kingdom.,Dipartimento di Scienze del Sistema Nervoso e del Comportamento, Università di Pavia, Pavia, Italy
| | - Giovanni Castellini
- Unità di Psichiatria, Dipartimento Scienze della Salute, Università degli studi di Firenze, Firenze, Italy
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19
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Fusar‐Poli P, Correll CU, Arango C, Berk M, Patel V, Ioannidis JP. Preventive psychiatry: a blueprint for improving the mental health of young people. World Psychiatry 2021; 20:200-221. [PMID: 34002494 PMCID: PMC8129854 DOI: 10.1002/wps.20869] [Citation(s) in RCA: 170] [Impact Index Per Article: 56.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Preventive approaches have latterly gained traction for improving mental health in young people. In this paper, we first appraise the conceptual foundations of preventive psychiatry, encompassing the public health, Gordon's, US Institute of Medicine, World Health Organization, and good mental health frameworks, and neurodevelopmentally-sensitive clinical staging models. We then review the evidence supporting primary prevention of psychotic, bipolar and common mental disorders and promotion of good mental health as potential transformative strategies to reduce the incidence of these disorders in young people. Within indicated approaches, the clinical high-risk for psychosis paradigm has received the most empirical validation, while clinical high-risk states for bipolar and common mental disorders are increasingly becoming a focus of attention. Selective approaches have mostly targeted familial vulnerability and non-genetic risk exposures. Selective screening and psychological/psychoeducational interventions in vulnerable subgroups may improve anxiety/depressive symptoms, but their efficacy in reducing the incidence of psychotic/bipolar/common mental disorders is unproven. Selective physical exercise may reduce the incidence of anxiety disorders. Universal psychological/psychoeducational interventions may improve anxiety symptoms but not prevent depressive/anxiety disorders, while universal physical exercise may reduce the incidence of anxiety disorders. Universal public health approaches targeting school climate or social determinants (demographic, economic, neighbourhood, environmental, social/cultural) of mental disorders hold the greatest potential for reducing the risk profile of the population as a whole. The approach to promotion of good mental health is currently fragmented. We leverage the knowledge gained from the review to develop a blueprint for future research and practice of preventive psychiatry in young people: integrating universal and targeted frameworks; advancing multivariable, transdiagnostic, multi-endpoint epidemiological knowledge; synergically preventing common and infrequent mental disorders; preventing physical and mental health burden together; implementing stratified/personalized prognosis; establishing evidence-based preventive interventions; developing an ethical framework, improving prevention through education/training; consolidating the cost-effectiveness of preventive psychiatry; and decreasing inequalities. These goals can only be achieved through an urgent individual, societal, and global level response, which promotes a vigorous collaboration across scientific, health care, societal and governmental sectors for implementing preventive psychiatry, as much is at stake for young people with or at risk for emerging mental disorders.
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Affiliation(s)
- Paolo Fusar‐Poli
- Early Psychosis: Interventions and Clinical‐detection (EPIC) Lab, Department of Psychosis StudiesInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUK,OASIS Service, South London and Maudsley NHS Foundation TrustLondonUK,Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly
| | - Christoph U. Correll
- Department of PsychiatryZucker Hillside Hospital, Northwell HealthGlen OaksNYUSA,Department of Psychiatry and Molecular MedicineZucker School of Medicine at Hofstra/NorthwellHempsteadNYUSA,Center for Psychiatric NeuroscienceFeinstein Institute for Medical ResearchManhassetNYUSA,Department of Child and Adolescent PsychiatryCharité Universitätsmedizin BerlinBerlinGermany
| | - Celso Arango
- Department of Child and Adolescent PsychiatryInstitute of Psychiatry and Mental Health, Hospital General Universitario Gregorio MarañónMadridSpain,Health Research Institute (IiGSM), School of MedicineUniversidad Complutense de MadridMadridSpain,Biomedical Research Center for Mental Health (CIBERSAM)MadridSpain
| | - Michael Berk
- Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin UniversityBarwon HealthGeelongVICAustralia,Department of PsychiatryUniversity of MelbourneMelbourneVICAustralia,Orygen Youth HealthUniversity of MelbourneMelbourneVICAustralia,Florey Institute for Neuroscience and Mental HealthUniversity of MelbourneMelbourneVICAustralia
| | - Vikram Patel
- Department of Global Health and Social MedicineHarvard University T.H. Chan School of Public HealthBostonMAUSA,Department of Global Health and PopulationHarvard T.H. Chan School of Public HealthBostonMAUSA
| | - John P.A. Ioannidis
- Stanford Prevention Research Center, Department of MedicineStanford UniversityStanfordCAUSA,Department of Biomedical Data ScienceStanford UniversityStanfordCAUSA,Department of Epidemiology and Population HealthStanford UniversityStanfordCAUSA
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20
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Puntis S, Oliver D, Fusar-Poli P. Third external replication of an individualised transdiagnostic prediction model for the automatic detection of individuals at risk of psychosis using electronic health records. Schizophr Res 2021; 228:403-409. [PMID: 33556673 DOI: 10.1016/j.schres.2021.01.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 01/03/2021] [Accepted: 01/18/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Primary indicated prevention is a key target for reducing the incidence and burden of schizophrenia and related psychotic disorders. An individualised, clinically-based transdiagnostic model for the detection of individuals at risk of psychosis has been developed and validated in two large, urban healthcare providers. We tested its external validity in a geographically and demographically different non-urban population. METHOD Retrospective EHR cohort study. All individuals accessing secondary healthcare provided by Oxford Health NHS Foundation Trust between 1st January 2011 and 30th November 2019 and receiving a primary index diagnosis of a non-psychotic or non-organic mental disorder were considered eligible. The previously developed model was applied to this database and its external prognostic accuracy was measured with Harrell's C. FINDINGS The study included n = 33,710 eligible individuals, with an average age of 27.7 years (SD = 19.8), mostly white (92.0%) and female (57.3%). The mean follow-up was 1863.9 days (SD = 948.9), with 868 transitions to psychosis and a cumulative incidence of psychosis at 6 years of 2.9% (95%CI: 2.7-3.1). Compared to the urban development database, Oxford Health was characterised by a relevant case mix, lower incidence of psychosis, different distribution of baseline predictors, higher proportion of white females, and a lack of specialised clinical services for at risk individuals. Despite these differences the model retained an adequate prognostic performance (Harrell's C = 0.79, 95%CI: 0.78-0.81), with no major miscalibration. INTERPRETATION The transdiagnostic, individualised, clinically-based risk calculator is transportable outside urban healthcare providers. Further research should test transportability of this risk prediction model in an international setting.
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Affiliation(s)
- Stephen Puntis
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, United Kingdom.
| | - Dominic Oliver
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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21
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Fusar-Poli P, Oliver D, Spada G, Estrade A, McGuire P. The case for improved transdiagnostic detection of first-episode psychosis: Electronic health record cohort study. Schizophr Res 2021; 228:547-554. [PMID: 33234425 DOI: 10.1016/j.schres.2020.11.031] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 07/30/2020] [Accepted: 11/16/2020] [Indexed: 01/03/2023]
Abstract
BACKGROUND Improving outcomes of a First Episode of Psychosis (FEP) relies on the ability to detect most individuals with emerging psychosis and treat them in specialised Early Intervention (EI) services. Efficacy of current detection strategies is undetermined. METHODS RECORD-compliant clinical, 6-year, retrospective, transdiagnostic, lifespan-inclusive, Electronic Health Record (EHR) cohort study, representing real-world secondary mental healthcare in South London and Maudsley (SLaM) NHS. All individuals accessing SLaM in the period 2007-2017 and receiving any ICD-10 diagnosis other than persistent psychosis were included. Descriptive statistics, Kaplan-Meier curves, logistic regression, epidemiological incidence of psychosis in the general population were used to address pathways to care and detection power of EI services for FEP. RESULTS A total of 106,706 individuals underwent the 6-year follow-up: they were mostly single (72.57%) males (50.51%) of white ethnicity (60.01%), aged on average 32.96 years, with an average Health Of the Nation Outcome Scale score of 11.12 and mostly affected with F40-48 Neurotic/stress-related/somatoform disorders (27.46%). Their transdiagnostic risk of developing a FEP cumulated to 0.072 (95%CI 0.067-0.077) at 6 years. Those individuals who developed a FEP (n = 1841) entered healthcare mostly (79.02%) through inpatient mental health services (29.76%), community mental health services (29.54%) or accident and emergency departments (19.50%); at the time of FEP onset, most of them (46.43%) were under the acute care pathway. Individuals contacting accident and emergency departments had an increased risk of FEP (OR 2.301, 95%CI 2.095-2.534, P < 0.001). The proportion of SLaM FEP cases that were eligible and under the care of EI services was 0.456 at any time. The epidemiological proportion of FEP cases in the sociodemographically-matched general population that was detected by EI service was 0.373. CONCLUSIONS More than half of individuals who develop a FEP remain undetected by current pathways to care and EI services. Improving detection strategies should become a mainstream area in the future generation of early psychosis research.
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Affiliation(s)
- Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Dominic Oliver
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Giulia Spada
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
| | - Andres Estrade
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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22
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Salazar de Pablo G, Estradé A, Cutroni M, Andlauer O, Fusar-Poli P. Establishing a clinical service to prevent psychosis: What, how and when? Systematic review. Transl Psychiatry 2021; 11:43. [PMID: 33441556 PMCID: PMC7807021 DOI: 10.1038/s41398-020-01165-x] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 11/27/2020] [Accepted: 12/03/2020] [Indexed: 01/29/2023] Open
Abstract
The first rate-limiting step to successfully translate prevention of psychosis in to clinical practice is to establish specialised Clinical High Risk for Psychosis (CHR-P) services. This study systematises the knowledge regarding CHR-P services and provides guidelines for translational implementation. We conducted a PRISMA/MOOSE-compliant (PROSPERO-CRD42020163640) systematic review of Web of Science to identify studies until 4/05/2020 reporting on CHR-P service configuration, outreach strategy and referrals, service user characteristics, interventions, and outcomes. Fifty-six studies (1998-2020) were included, encompassing 51 distinct CHR-P services across 15 countries and a catchment area of 17,252,666 people. Most services (80.4%) consisted of integrated multidisciplinary teams taking care of CHR-P and other patients. Outreach encompassed active (up to 97.6%) or passive (up to 63.4%) approaches: referrals came mostly (90%) from healthcare agencies. CHR-P individuals were more frequently males (57.2%). Most (70.6%) services accepted individuals aged 12-35 years, typically assessed with the CAARMS/SIPS (83.7%). Baseline comorbid mental conditions were reported in two-third (69.5%) of cases, and unemployment in one third (36.6%). Most services provided up to 2-years (72.4%), of clinical monitoring (100%), psychoeducation (81.1%), psychosocial support (73%), family interventions (73%), individual (67.6%) and group (18.9%) psychotherapy, physical health interventions (37.8%), antipsychotics (87.1%), antidepressants (74.2%), anxiolytics (51.6%), and mood stabilisers (38.7%). Outcomes were more frequently ascertained clinically (93.0%) and included: persistence of symptoms/comorbidities (67.4%), transition to psychosis (53.5%), and functional status (48.8%). We provide ten practical recommendations for implementation of CHR-P services. Health service knowledge summarised by the current study will facilitate translational efforts for implementation of CHR-P services worldwide.
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Affiliation(s)
- Gonzalo Salazar de Pablo
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), CIBERSAM, Madrid, Spain
| | - Andrés Estradé
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Clinical and Health Psychology, Catholic University, Montevideo, Uruguay
| | - Marcello Cutroni
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Olivier Andlauer
- Heads UP Service, East London NHS Foundation Trust, London, UK
- Centre for Psychiatry, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK.
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK.
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23
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Oliver D, Spada G, Colling C, Broadbent M, Baldwin H, Patel R, Stewart R, Stahl D, Dobson R, McGuire P, Fusar-Poli P. Real-world implementation of precision psychiatry: Transdiagnostic risk calculator for the automatic detection of individuals at-risk of psychosis. Schizophr Res 2021; 227:52-60. [PMID: 32571619 PMCID: PMC7875179 DOI: 10.1016/j.schres.2020.05.007] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/01/2020] [Accepted: 05/04/2020] [Indexed: 12/31/2022]
Abstract
BACKGROUND Risk estimation models integrated into Electronic Health Records (EHRs) can deliver innovative approaches in psychiatry, but clinicians' endorsement and their real-world usability are unknown. This study aimed to investigate the real-world feasibility of implementing an individualised, transdiagnostic risk calculator to automatically screen EHRs and detect individuals at-risk for psychosis. METHODS Feasibility implementation study encompassing an in-vitro phase (March 2018 to May 2018) and in-vivo phase (May 2018 to April 2019). The in-vitro phase addressed implementation barriers and embedded the risk calculator (predictors: age, gender, ethnicity, index cluster diagnosis, age*gender) into the local EHR. The in-vivo phase investigated the real-world feasibility of screening individuals accessing secondary mental healthcare at the South London and Maudsley NHS Trust. The primary outcome was adherence of clinicians to automatic EHR screening, defined by the proportion of clinicians who responded to alerts from the risk calculator, over those contacted. RESULTS In-vitro phase: implementation barriers were identified/overcome with clinician and service user engagement, and the calculator was successfully integrated into the local EHR through the CogStack platform. In-vivo phase: 3722 individuals were automatically screened and 115 were detected. Clinician adherence was 74% without outreach and 85% with outreach. One-third of clinicians responded to the first email (37.1%) or phone calls (33.7%). Among those detected, cumulative risk of developing psychosis was 12% at six-month follow-up. CONCLUSION This is the first implementation study suggesting that combining precision psychiatry and EHR methods to improve detection of individuals with emerging psychosis is feasible. Future psychiatric implementation research is urgently needed.
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Affiliation(s)
- Dominic Oliver
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Giulia Spada
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Craig Colling
- National Institute for Health Research, Maudesley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Matthew Broadbent
- National Institute for Health Research, Maudesley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Helen Baldwin
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; National Institute for Health Research, Maudesley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Rashmi Patel
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Robert Stewart
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; South London and Maudsley Foundation Trust, London, United Kingdom
| | - Daniel Stahl
- Department of Biostatistics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Richard Dobson
- National Institute for Health Research, Maudesley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Institute of Health Informatics Research, University College London, London, United Kingdom; Health Data Research UK London, University College London, London, United Kingdom
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; National Institute for Health Research, Maudesley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
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24
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Oliver D, Spada G, Englund A, Chesney E, Radua J, Reichenberg A, Uher R, McGuire P, Fusar-Poli P. Real-world digital implementation of the Psychosis Polyrisk Score (PPS): A pilot feasibility study. Schizophr Res 2020; 226:176-183. [PMID: 32340785 PMCID: PMC7774585 DOI: 10.1016/j.schres.2020.04.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 04/08/2020] [Accepted: 04/12/2020] [Indexed: 12/31/2022]
Abstract
BACKGROUND The Psychosis Polyrisk Score (PPS) is a potential biomarker integrating non-purely genetic risk/protective factors for psychosis that may improve identification of individuals at risk and prediction of their outcomes at the individual subject level. Biomarkers that are easy to administer are direly needed in early psychosis to facilitate clinical implementation. This study digitally implements the PPS and pilots its feasibility of use in the real world. METHODS The PPS was implemented digitally and prospectively piloted across individuals referred for a CHR-P assessment (n = 16) and healthy controls (n = 66). Distribution of PPS scores was further simulated in the general population. RESULTS 98.8% of individuals referred for a CHR-P assessment and healthy controls completed the PPS assessment with only one drop-out. 96.3% of participants completed the assessment in under 15 min. Individuals referred for a CHR-P assessment had high PPS scores (mean = 6.2, SD = 7.23) than healthy controls (mean = -1.79, SD = 6.78, p < 0.001). In simulated general population data, scores were normally distributed ranging from -15 (lowest risk, RR = 0.03) to 39.5 (highest risk, RR = 8912.51). DISCUSSION The PPS is a promising biomarker which has been implemented digitally. The PPS can be easily administered to both healthy controls and individuals at potential risk for psychosis on a range of devices. It is feasible to use the PPS in real world settings to assess individuals with emerging mental disorders. The next phase of research should be to include the PPS in large-scale international cohort studies to evaluate its ability to refine the prognostication of outcomes.
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Affiliation(s)
- Dominic Oliver
- Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom
| | - Giulia Spada
- Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom
| | - Amir Englund
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Edward Chesney
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Joaquim Radua
- Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,Imaging of Mood- and Anxiety-Related Disorders (IMARD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain,Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - Abraham Reichenberg
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States,Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States,Frieman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Philip McGuire
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
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Solmi M, Bodini L, Cocozza S, Seeman MV, Vieta E, Dragioti E, Carvalho AF, Fusar-Poli P. Aripiprazole monotherapy as transdiagnostic intervention for the treatment of mental disorders: An umbrella review according to TRANSD criteria. Eur Neuropsychopharmacol 2020; 41:16-27. [PMID: 33077324 DOI: 10.1016/j.euroneuro.2020.09.635] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/12/2020] [Accepted: 09/21/2020] [Indexed: 12/26/2022]
Abstract
Aripiprazole is approved in different countries as treatment for several mental disorders, but its transdiagnostic potential has not yet been assessed according to established criteria such as the recently proposed TRANSD criteria. The present work aims to test whether aripiprazole monotherapy could be considered a transdiagnostic intervention. An umbrella review of meta-analyses of randomized controlled trials (RCTs) of aripiprazole monotherapy vs placebo was conducted for any disorder defined according to standard diagnostic criteria. Primary outcomes were levels of psychiatric disease-specific symptoms. TRANSD criteria were applied to assess transdiagnosticity, while the AMSTAR -2 tool was used to assess the quality of eligible meta-analyses. Four pairwise meta-analyses and three network meta-analyses were included, consisting of 25 RCTs of aripiprazole monotherapy vs. placebo (N=5469). Aripiprazole outperformed placebo on primary outcomes in Alzheimer's disease with behavioral disturbance (AD) (neuropsychiatric symptoms SMD 0.20, 95%CI 0.05-0.35, max 15 mg/day), autism spectrum disorder (ASD) (severity of symptoms SMD 0.39, 95%CI 0.30-0.48, max 15 mg/day), bipolar I disorder (BD) (severity of manic symptoms SMD 0.30, 95%CI 0.12-0.47, max 30 mg/day), and schizophrenia/schizoaffective disorder (response rate RR 0.84, 95%CI 0.78-0.92, max 30 mg/day). TRANSD criteria were met (pooled SMD 0.25, 95%CI 0.09-0.41) across these disorders Quality was high in all the included meta-analyses according to AMSTAR-2. According to TRANSD criteria, aripiprazole monotherapy is a (dose-specific) transdiagnostic intervention to treat psychiatric disease-specific symptoms across 5 diagnoses (AD, ASD, BD (mania), schizophrenia/schizoaffective disorder), across four DSM-5 diagnostic groups (neurocognitive disorders, neurodevelopmental disorders, bipolar and related disorders, schizophrenia spectrum and other psychotic disorders).
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Affiliation(s)
- Marco Solmi
- Neurosciences Department, University of Padua, Padua, Italy; Neuroscience Centre, University of Padua, Padua, Italy; Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Luca Bodini
- Università degli Studi di Milano, Bicocca, Italy
| | - Susanna Cocozza
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Mary V Seeman
- Department of Psychiatry, University of Toronto, and the Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Eduard Vieta
- IDIBAPS, CIBERSAM, Clinical Institute of Neuroscience, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Elena Dragioti
- Pain and Rehabilitation Centre, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Andre F Carvalho
- Department of Psychiatry, University of Toronto, and the Centre for Addiction and Mental Health, Toronto, ON, Canada; IMPACT (Innovation in Mental and Physical Health and Clinical Treatment) Strategic Research Centre, School of Medicine, Barwon Health, Deakin University, Geelong, VIC, Australia
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK; National Institute for Health Research, Maudsley Biomedical Research Centre, London, UK
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Environmental risk factors, protective factors, and peripheral biomarkers for ADHD: an umbrella review. Lancet Psychiatry 2020; 7:955-970. [PMID: 33069318 DOI: 10.1016/s2215-0366(20)30312-6] [Citation(s) in RCA: 95] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 05/07/2020] [Accepted: 06/12/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Many potential environmental risk factors, environmental protective factors, and peripheral biomarkers for ADHD have been investigated, but the consistency and magnitude of their effects are unclear. We aimed to systematically appraise the published evidence of association between potential risk factors, protective factors, or peripheral biomarkers, and ADHD. METHODS In this umbrella review of meta-analyses, we searched PubMed including MEDLINE, Embase, and the Cochrane Database of Systematic Reviews, from database inception to Oct 31, 2019, and screened the references of relevant articles. We included systematic reviews that provided meta-analyses of observational studies that examined associations of potential environmental risk factors, environmental protective factors, or peripheral biomarkers with diagnosis of ADHD. We included meta-analyses that used categorical ADHD diagnosis criteria according to DSM, hyperkinetic disorder according to ICD, or criteria that were less rigorous than DSM or ICD, such as self-report. We excluded articles that did not examine environmental risk factors, environmental protective factors, or peripheral biomarkers of ADHD; articles that did not include a meta-analysis; and articles that did not present enough data for re-analysis. We excluded non-human studies, primary studies, genetic studies, and conference abstracts. We calculated summary effect estimates (odds ratio [OR], relative risk [RR], weighted mean difference [WMD], Cohen's d, and Hedges' g), 95% CI, heterogeneity I2 statistic, 95% prediction interval, small study effects, and excess significance biases. We did analyses under credibility ceilings, and assessed the quality of the meta-analyses with AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews 2). This study is registered with PROSPERO, number CRD42019145032. FINDINGS We identified 1839 articles, of which 35 were eligible for inclusion. These 35 articles yielded 63 meta-analyses encompassing 40 environmental risk factors and environmental protective factors (median cases 16 850, median population 91 954) and 23 peripheral biomarkers (median cases 175, median controls 187). Evidence of association was convincing (class I) for maternal pre-pregnancy obesity (OR 1·63, 95% CI 1·49 to 1·77), childhood eczema (1·31, 1·20 to 1·44), hypertensive disorders during pregnancy (1·29, 1·22 to 1·36), pre-eclampsia (1·28, 1·21 to 1·35), and maternal acetaminophen exposure during pregnancy (RR 1·25, 95% CI 1·17 to 1·34). Evidence of association was highly suggestive (class II) for maternal smoking during pregnancy (OR 1·6, 95% CI 1·45 to 1·76), childhood asthma (1·51, 1·4 to 1·63), maternal pre-pregnancy overweight (1·28, 1·21 to 1·35), and serum vitamin D (WMD -6·93, 95% CI -9·34 to -4·51). INTERPRETATION Maternal pre-pregnancy obesity and overweight; pre-eclampsia, hypertension, acetaminophen exposure, and smoking during pregnancy; and childhood atopic diseases were strongly associated with ADHD. Previous familial studies suggest that maternal pre-pregnancy obesity, overweight, and smoking during pregnancy are confounded by familial or genetic factors, and further high-quality studies are therefore required to establish causality. FUNDING None.
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Cortese S, Solmi M, Arrondo G, Cipriani A, Fusar-Poli P, Larsson H, Correll C. Association between mental disorders and somatic conditions: protocol for an umbrella review. EVIDENCE-BASED MENTAL HEALTH 2020; 23:135-139. [PMID: 32900790 PMCID: PMC10231570 DOI: 10.1136/ebmental-2020-300158] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
INTRODUCTION Although several systematic reviews (SRs)/meta-analyses (MAs) on the association between specific mental disorders and specific somatic conditions are available, an overarching evidence synthesis across mental disorders and somatic conditions is currently lacking. We will conduct an umbrella review of SRs/MAs to test: 1) the strength of the association between individual mental disorders and individual somatic conditions in children/adolescents and adults; 2) to which extent associations are specific to individual mental and somatic conditions . METHODS AND ANALYSIS We will search a broad set of electronic databases and contact study authors. We will include SRs with MA or SRs reporting the effect size from individual studies on the association between a number of somatic and mental conditions (as per the International Classification of Diseases, 11th Revision). We will follow an algorithm to select only one SR or MA when more than one are available on the same association. We will rate the quality of included SRs/MAs using the AMSTAR-2 tool. We will assess to which extent mental disorders are selectively associated with specific somatic conditions or if there are transdiagnostic, across-spectra or diagnostic spectrum-specific associations between mental disorders and somatic conditions based on the Transparent, Reporting, Appraising, Numerating, Showing (TRANSD) recommendations. DISCUSSION The present umbrella review will shed light on the association between mental health disorders and somatic conditions, providing useful data for the care of patients with mental health disorders, in particular for early detection and intervention. This work might also add insight to the pathophysiology of mental health conditions, and contribute to the current debate on the value of a transdiagnostic approach in psychiatry.
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Affiliation(s)
- Samuele Cortese
- Centre for Innovation in Mental Health (CIMH), School of Psychology, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Solent NHS Trust, Southampton, UK
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
- National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, NIHR MindTech MedTech Co-operative, Nottingham, UK
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, New York, USA
| | - Marco Solmi
- Neuroscience Department, Psychiatry Unit, Padua Neuroscience Center, University of Padua, Padua, Italy
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Gonzalo Arrondo
- Mind-Brain Group. Institute for Culture and Society, University of Navarra, Pamplona, Spain
| | - Andrea Cipriani
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
- Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Christoph Correll
- The Zucker Hillside Hospital, Division of Psychiatry Research, Northwell Health, Glen Oaks, New York, New York, USA
- Department of Psychiatry and Molecular Medicine, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, New York, New York, USA
- Department of Child and Adolescent Psychiatry, Charité Universitäts medizin, Berlin, Germany
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Salazar de Pablo G, Studerus E, Vaquerizo-Serrano J, Irving J, Catalan A, Oliver D, Baldwin H, Danese A, Fazel S, Steyerberg EW, Stahl D, Fusar-Poli P. Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice. Schizophr Bull 2020; 47:284-297. [PMID: 32914178 PMCID: PMC7965077 DOI: 10.1093/schbul/sbaa120] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND The impact of precision psychiatry for clinical practice has not been systematically appraised. This study aims to provide a comprehensive review of validated prediction models to estimate the individual risk of being affected with a condition (diagnostic), developing outcomes (prognostic), or responding to treatments (predictive) in mental disorders. METHODS PRISMA/RIGHT/CHARMS-compliant systematic review of the Web of Science, Cochrane Central Register of Reviews, and Ovid/PsycINFO databases from inception until July 21, 2019 (PROSPERO CRD42019155713) to identify diagnostic/prognostic/predictive prediction studies that reported individualized estimates in psychiatry and that were internally or externally validated or implemented. Random effect meta-regression analyses addressed the impact of several factors on the accuracy of prediction models. FINDINGS Literature search identified 584 prediction modeling studies, of which 89 were included. 10.4% of the total studies included prediction models internally validated (n = 61), 4.6% models externally validated (n = 27), and 0.2% (n = 1) models considered for implementation. Across validated prediction modeling studies (n = 88), 18.2% were diagnostic, 68.2% prognostic, and 13.6% predictive. The most frequently investigated condition was psychosis (36.4%), and the most frequently employed predictors clinical (69.5%). Unimodal compared to multimodal models (β = .29, P = .03) and diagnostic compared to prognostic (β = .84, p < .0001) and predictive (β = .87, P = .002) models were associated with increased accuracy. INTERPRETATION To date, several validated prediction models are available to support the diagnosis and prognosis of psychiatric conditions, in particular, psychosis, or to predict treatment response. Advancements of knowledge are limited by the lack of implementation research in real-world clinical practice. A new generation of implementation research is required to address this translational gap.
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Affiliation(s)
- Gonzalo Salazar de Pablo
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK,Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón, CIBERSAM, Madrid, Spain,Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Erich Studerus
- Division of Personality and Developmental Psychology, Department of Psychology, University of Basel, Basel, Switzerland
| | - Julio Vaquerizo-Serrano
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK,Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón, CIBERSAM, Madrid, Spain,Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Jessica Irving
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK
| | - Ana Catalan
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK,Department of Psychiatry, Basurto University Hospital, Bilbao, Spain,Mental Health Group, BioCruces Health Research Institute, Bizkaia, Spain,Neuroscience Department, University of the Basque Country UPV/EHU, Leioa, Spain
| | - Dominic Oliver
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK
| | - Helen Baldwin
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK
| | - Andrea Danese
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK,National and Specialist CAMHS Clinic for Trauma, Anxiety, and Depression, South London and Maudsley NHS Foundation Trust, London, UK
| | - Seena Fazel
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Ewout W Steyerberg
- Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands,Department of Public Health, Erasmus MC, Rotterdam, the Netherlands
| | - Daniel Stahl
- Biostatistics Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, UK,OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy,National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK,To whom correspondence should be addressed; tel: +44-0-20-7848-0900, fax:+44-0-20-7848-0976, e-mail:
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