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Clauss JA, Foo CYS, Leonard CJ, Dokholyan KN, Cather C, Holt DJ. Screening for psychotic experiences and psychotic disorders in general psychiatric settings: a systematic review and meta-analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.14.24305796. [PMID: 38699350 PMCID: PMC11065042 DOI: 10.1101/2024.04.14.24305796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Background The absence of systematic screening for psychosis within general psychiatric services contribute to substantial treatment delays and poor long-term outcomes. We conducted a meta-analysis to estimate rates of psychotic experiences, clinical high-risk for psychosis syndrome (CHR-P), and psychotic disorders identified by screening treatment-seeking individuals to inform implementation recommendations for routine psychosis screening in general psychiatric settings. Methods PubMed and Web of Science databases were searched to identify empirical studies that contained information on the point prevalence of psychotic experiences, CHR-P, or psychotic disorders identified by screening inpatient and outpatient samples aged 12-64 receiving general psychiatric care. Psychotic experiences were identified by meeting threshold scores on validated self-reported questionnaires, and psychotic disorders and CHR-P by gold-standard structured interview assessments. A meta-analysis of each outcome was conducted using the Restricted Maximum Likelihood Estimator method of estimating effect sizes in a random effects model. Results 41 independent samples (k=36 outpatient) involving n=25,751 patients (58% female, mean age: 24.1 years) were included. Among a general psychiatric population, prevalence of psychotic experiences was 44.3% (95% CI: 35.8-52.8%; 28 samples, n=21,957); CHR-P was 26.4% (95% CI: 20.0-32.7%; 28 samples, n=14,395); and psychotic disorders was 6.6% (95% CI: 3.3-9.8%; 32 samples, n=20,371). Conclusions High rates of psychotic spectrum illness in general psychiatric settings underscore need for secondary prevention with psychosis screening. These base rates can be used to plan training and resources required to conduct assessments for early detection, as well as build capacity in interventions for CHR-P and early psychosis in non-specialty mental health settings.
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Affiliation(s)
- Jacqueline A. Clauss
- Psychosis Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Cheryl Y. S. Foo
- Psychosis Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
- Center of Excellence for Psychosocial and Systemic Research, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Katherine N. Dokholyan
- Psychosis Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Corinne Cather
- Psychosis Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
- Center of Excellence for Psychosocial and Systemic Research, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Daphne J. Holt
- Psychosis Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
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2
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Chen C, Deng Y, Li Y, Zhang M, Yu T, Xie K, Bao W, Li P, Sun L, Zhang T, Zhu Y, Zhang B. Network Meta-Analysis Indicates Superior Effects of Omega-3 Polyunsaturated Fatty Acids in Preventing the Transition to Psychosis in Individuals at Clinical High-Risk. Int J Neuropsychopharmacol 2024; 27:pyae014. [PMID: 38408281 PMCID: PMC10949445 DOI: 10.1093/ijnp/pyae014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 02/24/2024] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND The efficacy of pharmacological and nutritional interventions in individuals at clinical high risk for psychosis (CHR-P) remains elusive. This study aims to investigate the efficacy of pharmacological and nutritional interventions in CHR-P and whether these interventions can enhance the efficacy of psychological treatments. METHODS We systematically reviewed data from 5 databases until July 24, 2021: PubMed, Web of Science, EMBASE, China National Knowledge Infrastructure, and WanFang Data. The primary outcome was the transition to psychosis. Network meta-analyses were conducted at 3 time points (6, 12, and ≥24 months) considering both pharmacological/nutritional interventions alone and its combination with psychotherapy. RESULTS Out of 11 417 identified references, 21 studies were included, comprising 1983 participants. CHR-P participants receiving omega-3 polyunsaturated fatty acids treatment were associated with a lower probability of transition compared with placebo/control at 6 months (odds ratio [OR] = 0.07, 95% confidence interval [CI] = .01 to .054), 12 months (OR = 0.14, 95% CI = .03 to .66), and ≥24 months (OR = 0.16, 95% CI = .05 to .54). Moreover, risperidone plus psychotherapy was associated with a lower likelihood of transition at 6 months compared with placebo/control plus psychotherapy, but this result was not sustained over longer durations. CONCLUSION Omega-3 polyunsaturated fatty acids helped in preventing transitions to psychosis compared with controls. PROSPERO REGISTRATION NUMBER CRD42021256209.
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Affiliation(s)
- Chengfeng Chen
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Psychiatry, Guangzhou Medical University, Guangzhou, China
| | - Yongyan Deng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yuling Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Psychiatry, Guangzhou Medical University, Guangzhou, China
| | - Meiting Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Psychiatry, Guangzhou Medical University, Guangzhou, China
| | - Tong Yu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Psychiatry, Guangzhou Medical University, Guangzhou, China
| | - Kun Xie
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Psychiatry, Guangzhou Medical University, Guangzhou, China
| | - Wuyou Bao
- Institute of Mental Health, Tianjin Anding Hospital, Tianjin Medical University, Tianjin, China
| | - Peiying Li
- Institute of Mental Health, Tianjin Anding Hospital, Tianjin Medical University, Tianjin, China
| | - Ling Sun
- Institute of Mental Health, Tianjin Anding Hospital, Tianjin Medical University, Tianjin, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yikang Zhu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bin Zhang
- Institute of Mental Health, Tianjin Anding Hospital, Tianjin Medical University, Tianjin, China
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3
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Livingston NR, Fusar-Poli P, Modinos G. Letter to the Editor on 'Baseline benzodiazepine exposure is associated with greater risk of transition in clinical high-risk for psychosis (CHR-P): a meta-analysis'. Psychol Med 2024; 54:215-216. [PMID: 37921000 DOI: 10.1017/s0033291723003203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2023]
Affiliation(s)
- Nicholas R Livingston
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Paolo Fusar-Poli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Brain and Behavioural Science, University of Pavia, Pavia, Italy
| | - Gemma Modinos
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
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4
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Raballo A, Poletti M, Preti A. Baseline benzodiazepine exposure is associated with greater risk of transition in clinical high-risk for psychosis (CHR-P): a meta-analysis. Psychol Med 2023:1-7. [PMID: 37609894 DOI: 10.1017/s0033291723002180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
BACKGROUND Emerging meta-analytical evidence indicates that baseline exposure to antipsychotics and to antidepressants in individuals at clinical high-risk for psychosis (CHR-P) have opposite prognostic effects as regards imminent transition to psychosis, with antipsychotics associated with higher risk and antidepressants associated with a lower risk in comparison to not-exposed individuals. Despite their common use, baseline exposure to benzodiazepines (BDZ) in CHR-P has surprisingly received poor attention as a potential risk modulator for transition to psychosis. The current systematic review and meta-analysis were performed to fix such a knowledge gap. METHODS Systematic scrutiny of Medline and Cochrane library, performed up to 31 December 2022, searching for English-language studies on CHR-P reporting numeric data about the sample, the transition outcome at a predefined follow-up time and raw data on BDZ baseline exposure in relation to such outcome. RESULTS Of 1893 identified records, five studies were included in the systematic review and meta-analysis. The proportion of participants with exposure to BDZ at baseline ranged from 5.5% (one study) to 46.2%, with an average of 16.8%. At the end of the period of observation, i.e., the follow-up as reported in the study, 28.4% [95% confidence interval (CI) 19.7-39.1%] participants developed psychosis among the BDZ-exposed against 9.3% (7.3 to 11.9%) among the controls. CHR-P participants who were already under BDZ treatment at baseline had more than double chance of transition to psychosis than CHR-P participants who were BDZ-naïve. The risk ratio (RR) was 2.42 (95% CI 1.38-4.23) in the common effects model (z = 3.09; p = 0.002), and 2.40 (1.53 to 3.77) in the random-effects model (z = 5.40; p = 0.006; tau-squared = 0.0). There was no relevant heterogeneity: Cochran's Q = 1.49; df = 4; p = 0.828; I2 = 0.0% (95% CI 0.0-79%). Quality was good in four studies. CONCLUSIONS Ongoing BDZ exposure at inception in CHR-P is associated with a higher risk of transition to psychosis at follow up. This meta-analytic association, which echoes a similar effect of baseline antipsychotic exposure, plausibly indicates that the clinicians' prescription of pharmacological intervention captures some form of prognostically-relevant information (e.g. an anxiety permeated mental state requiring BDZ prescription) that are not adequately encompassed by current CHR-P categorical criteria.
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Affiliation(s)
- Andrea Raballo
- Chair of Psychiatry, Faculty of Biomedical Sciences, University of Southern Switzerland, Lugano, Switzerland
- Cantonal Sociopsychiatric Organisation, Mendrisio, Switzerland
| | - Michele Poletti
- Department of Mental Health and Pathological Addiction, Child and Adolescent Neuropsychiatry Service, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Antonio Preti
- Department of Neuroscience, University of Turin, Turin, Italy
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5
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Raballo A, Poletti M, Preti A. Do antidepressants prevent transition to psychosis in individuals at clinical high-risk (CHR-P)? Systematic review and meta-analysis. Psychol Med 2023; 53:4550-4560. [PMID: 35655405 DOI: 10.1017/s0033291722001428] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Emerging meta-analytical evidence indicates that baseline exposure to antipsychotics in individuals at clinical high-risk for psychosis (CHR-P) is associated with a higher risk of an imminent transition to psychosis. Despite their tolerability profile and potential beneficial effects, baseline exposure to antidepressants (AD) in CHR-P has surprisingly received far less attention as a potential risk modulator for transition to psychosis. The current systematic review and meta-analysis were performed to fix such a knowledge gap. METHODS Systematic scrutiny of Medline and Cochrane library, performed up to 1 August 2021, searching for English-language studies on CHR-P reporting numeric data about the sample, the transition outcome at a predefined follow-up time and raw data on AD baseline exposure in relation to such outcome. RESULTS Of 1942 identified records, 16 studies were included in the systematic review and meta-analysis. 26% of the participants were already exposed to AD at baseline; at the end of the follow-up 13.5% (95% CI 10.2-17.1%) of them (n = 448) transitioned to psychosis against 21.0% (18.9 to 23.3%) of non-AD exposed CHR-P (n = 1371). CHR-P participants who were already under AD treatment at baseline had a lower risk of transition than non-AD exposed CHR-P. The RR was 0.71 (95% CI 0.56-0.90) in the fixed-effects model (z = -2.79; p = 0.005), and 0.78 (0.58-1.05) in the random-effects model (z = -1.77; p = 0.096; tau-squared = 0.059). There was no relevant heterogeneity (Cochran's Q = 18.45; df = 15; p = 0.239; I2 = 18.7%). CONCLUSIONS Ongoing AD exposure at inception in CHR-P is associated to a reduced risk of transition to psychosis at follow up.
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Affiliation(s)
- Andrea Raballo
- Section of Psychiatry, Clinical Psychology and Rehabilitation, Department of Medicine, University of Perugia, Perugia, Italy
- Center for Translational, Phenomenological and Developmental Psychopathology (CTPDP), Perugia University Hospital, Perugia, Italy
| | - Michele Poletti
- Department of Mental Health and Pathological Addiction, Child and Adolescent Neuropsychiatry Service, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Antonio Preti
- Department of Neuroscience, University of Turin, Turin, Italy
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Oliver D, Arribas M, Radua J, Salazar de Pablo G, De Micheli A, Spada G, Mensi MM, Kotlicka-Antczak M, Borgatti R, Solmi M, Shin JI, Woods SW, Addington J, McGuire P, Fusar-Poli P. Prognostic accuracy and clinical utility of psychometric instruments for individuals at clinical high-risk of psychosis: a systematic review and meta-analysis. Mol Psychiatry 2022; 27:3670-3678. [PMID: 35665763 PMCID: PMC9708585 DOI: 10.1038/s41380-022-01611-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/21/2022] [Accepted: 04/28/2022] [Indexed: 02/08/2023]
Abstract
Accurate prognostication of individuals at clinical high-risk for psychosis (CHR-P) is an essential initial step for effective primary indicated prevention. We aimed to summarise the prognostic accuracy and clinical utility of CHR-P assessments for primary indicated psychosis prevention. Web of Knowledge databases were searched until 1st January 2022 for longitudinal studies following-up individuals undergoing a psychometric or diagnostic CHR-P assessment, reporting transition to psychotic disorders in both those who meet CHR-P criteria (CHR-P + ) or not (CHR-P-). Prognostic accuracy meta-analysis was conducted following relevant guidelines. Primary outcome was prognostic accuracy, indexed by area-under-the-curve (AUC), sensitivity and specificity, estimated by the number of true positives, false positives, false negatives and true negatives at the longest available follow-up time. Clinical utility analyses included: likelihood ratios, Fagan's nomogram, and population-level preventive capacity (Population Attributable Fraction, PAF). A total of 22 studies (n = 4 966, 47.5% female, age range 12-40) were included. There were not enough meta-analysable studies on CHR-P diagnostic criteria (DSM-5 Attenuated Psychosis Syndrome) or non-clinical samples. Prognostic accuracy of CHR-P psychometric instruments in clinical samples (individuals referred to CHR-P services or diagnosed with 22q.11.2 deletion syndrome) was excellent: AUC = 0.85 (95% CI: 0.81-0.88) at a mean follow-up time of 34 months. This result was driven by outstanding sensitivity (0.93, 95% CI: 0.87-0.96) and poor specificity (0.58, 95% CI: 0.50-0.66). Being CHR-P + was associated with a small likelihood ratio LR + (2.17, 95% CI: 1.81-2.60) for developing psychosis. Being CHR-P- was associated with a large LR- (0.11, 95%CI: 0.06-0.21) for developing psychosis. Fagan's nomogram indicated a low positive (0.0017%) and negative (0.0001%) post-test risk in non-clinical general population samples. The PAF of the CHR-P state is 10.9% (95% CI: 4.1-25.5%). These findings consolidate the use of psychometric instruments for CHR-P in clinical samples for primary indicated prevention of psychosis. Future research should improve the ability to rule in psychosis risk.
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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, UK.
| | - Maite Arribas
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - 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 (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute, Stockholm, Sweden
| | - 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
- Child and Adolescent Mental Health Services, South London & Maudsley NHS Trust, London, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andrea De Micheli
- 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 National Health Service (NHS) Foundation Trust, 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
| | - Martina Maria Mensi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- IRCCS Mondino Foundation, Childhood and Adolescent Neuropsychiatry Unit, Pavia, Italy
| | - Magdalena Kotlicka-Antczak
- Early Psychosis Diagnosis and Treatment Lab, Department of Affective and Psychotic Disorders, Medical University of Lodz, Lodz, Poland
| | - Renato Borgatti
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- IRCCS Mondino Foundation, Childhood and Adolescent Neuropsychiatry Unit, Pavia, Italy
| | - 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, The Ottawa Hospital, Ottawa, ON, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute (OHRI), University of Ottawa, Ottawa, ON, Canada
| | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Jean Addington
- Department of Psychiatry, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Philip McGuire
- OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, UK
- 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 National Health Service (NHS) Foundation Trust, 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
- OASIS Service, South London and Maudsley National Health Service (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 National Health Service (NHS) Foundation Trust, London, UK
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7
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Takahashi T, Wood SJ, Yung AR, Nelson B, Lin A, Yuen HP, Phillips LJ, Suzuki M, McGorry PD, Velakoulis D, Pantelis C. Pineal morphology of the clinical high-risk state for psychosis and different psychotic disorders. Schizophr Res 2022; 244:1-7. [PMID: 35487129 DOI: 10.1016/j.schres.2022.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 04/13/2022] [Accepted: 04/16/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Pineal volume reductions have been reported in schizophrenia and clinical high-risk states for the development of psychosis, supporting the role of melatonin dysregulation in the pathophysiology of psychosis. However, it remains unclear whether pineal volume is associated with the later onset of psychosis in individuals at clinical high-risk (CHR) of psychosis or if pineal atrophy is specific to schizophrenia among different psychotic disorders. METHODS This magnetic resonance imaging study examined the volume of and cyst prevalence in the pineal gland in 135 individuals at CHR of psychosis [52 (38.5%) subsequently developed psychosis], 162 with first-episode psychosis (FEP), 89 with chronic schizophrenia, and 87 healthy controls. The potential contribution of the pineal morphology to clinical characteristics was also examined in the CHR and FEP groups. RESULTS Pineal volumes did not differ significantly between the CHR, FEP, and chronic schizophrenia groups, but were significantly smaller than that in healthy controls. However, pineal volumes were not associated with the later onset of psychosis in the CHR group or FEP sub-diagnosis (i.e., schizophrenia, schizophreniform disorder, affective psychosis, and other psychoses). No significant differences were observed in the prevalence of pineal cysts between the groups, and it also did not correlate with clinical characteristics in the CHR and FEP groups. CONCLUSION These results suggest that pineal atrophy is a general vulnerability marker of psychosis, while pineal cysts do not appear to contribute to the pathophysiology of psychosis.
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Affiliation(s)
- Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan.
| | - Stephen J Wood
- Orygen, Melbourne, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia; School of Psychology, University of Birmingham, Birmingham, UK
| | - Alison R Yung
- Orygen, Melbourne, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia; Institute for Mental and Physical Health and Clinical Translation (IMPACT), Deakin University, Geelong, Australia; School of Health Sciences, University of Manchester, Manchester, UK
| | - Barnaby Nelson
- Orygen, Melbourne, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Ashleigh Lin
- Telethon Kids Institute, The University of Western Australia, Perth, Australia
| | | | - Lisa J Phillips
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Patrick D McGorry
- Orygen, Melbourne, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia; Neuropsychiatry, Royal Melbourne Hospital, Melbourne Health, Melbourne, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia; Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia; North Western Mental Health, Western Hospital Sunshine, St. Albans, Victoria, Australia
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8
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Pieters LE, Nadesalingam N, Walther S, van Harten PN. A systematic review of the prognostic value of motor abnormalities on clinical outcome in psychosis. Neurosci Biobehav Rev 2021; 132:691-705. [PMID: 34813828 DOI: 10.1016/j.neubiorev.2021.11.027] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 11/09/2021] [Accepted: 11/17/2021] [Indexed: 02/07/2023]
Abstract
Schizophrenia spectrum disorders have heterogeneous outcomes and currently no marker predicts the course of illness. Motor abnormalities (MAs) are inherent to psychosis, the risk of psychosis, symptom severity, and brain alterations. However, the prognostic value of MAs is still unresolved. Here, we provide a systematic review of longitudinal studies on the prognostic role of MAs spanning individuals at clinical high risk for psychosis (CHR), patients with first-episode psychosis (FEP), and chronic schizophrenia. We included 68 studies for a total of 23,630 subjects that assessed neurological soft signs (NSS), hypo- or hyperkinetic movement disorders and/or catatonia as a prognostic factor on clinical and functional outcomes. We found increased levels of MAs, in particular NSS, parkinsonism, and dyskinesia, were related to deteriorating symptomatic and poor functional outcome over time. Collectively, the findings emphasize the clinical, prognostic and scientific relevance of MA assessment and detection in individuals with or at risk of psychosis. In the future, instrumental measures of MA are expected to further augment detection, early intervention and treatment strategies in psychosis.
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Affiliation(s)
- Lydia E Pieters
- Psychiatric Center GGz Centraal, Amersfoort, Research Department, Postbus 3051, 3800 DB Amersfoort, The Netherlands; Department of Psychiatry, School for Mental Health and Neuroscience, Maastricht University Medical Center, P.O. Box 616, 6200 MD Maastricht, The Netherlands
| | - Niluja Nadesalingam
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bolligenstrasse 111, CH-3000 Bern 60, Switzerland
| | - Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bolligenstrasse 111, CH-3000 Bern 60, Switzerland
| | - Peter N van Harten
- Psychiatric Center GGz Centraal, Amersfoort, Research Department, Postbus 3051, 3800 DB Amersfoort, The Netherlands; Department of Psychiatry, School for Mental Health and Neuroscience, Maastricht University Medical Center, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
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9
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Salazar de Pablo G, Woods SW, Drymonitou G, de Diego H, Fusar-Poli P. Prevalence of Individuals at Clinical High-Risk of Psychosis in the General Population and Clinical Samples: Systematic Review and Meta-Analysis. Brain Sci 2021; 11:brainsci11111544. [PMID: 34827543 PMCID: PMC8615691 DOI: 10.3390/brainsci11111544] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 10/30/2021] [Accepted: 11/02/2021] [Indexed: 11/16/2022] Open
Abstract
(1) The consistency and magnitude of the prevalence of Clinical High-Risk for Psychosis (CHR-P) individuals are undetermined, limiting efficient detection of cases. We aimed to evaluate the prevalence of CHR-P individuals systematically assessed in the general population or clinical samples. (2) PRISMA/MOOSE-compliant (PROSPERO: CRD42020168672) meta-analysis of multiple databases until 21/01/21: a random-effects model meta-analysis, heterogeneity analysis, publication bias and quality assessment, sensitivity analysis—according to the gold-standard CHR-P and pre-screening instruments—leave-one-study-out analyses, and meta-regressions were conducted. (3) 35 studies were included, with 37,135 individuals tested and 1554 CHR-P individuals identified (median age = 19.3 years, Interquartile range (IQR) = 15.8–22.1; 52.2% females, IQR = 38.7–64.4). In the general population (k = 13, n = 26,835 individuals evaluated), the prevalence of the CHR-P state was 1.7% (95% Confidence Interval (CI) = 1.0–2.9%). In clinical samples (k = 22, n = 10,300 individuals evaluated), the prevalence of the CHR-P state was 19.2% (95% CI = 12.9–27.7%). Using a pre-screening instrument was associated with false negatives (5.6%, 95% CI = 2.2–13.3%) and a lower CHR-P prevalence (11.5%, 95% CI = 6.2–20.5%) compared to using CHR-P instruments only (28.5%, 95% CI = 23.0–34.7%, p = 0.003). (4) The prevalence of the CHR-P state is low in the general population and ten times higher in clinical samples. The prevalence of CHR-P may increase with a higher proportion of females in the general population and with a younger population in clinical samples. The CHR-P state may be unrecognized in routine clinical practice. These findings can refine detection and preventive strategies.
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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 SE5 8AB, 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, 28040 Madrid, Spain;
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London WC2R 2LS, UK
- Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
| | - Scott W. Woods
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA;
| | | | - Héctor de Diego
- 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, 28040 Madrid, Spain;
| | - 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 8AB, UK;
- OASIS Service, South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
- Correspondence:
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10
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Raballo A, Poletti M, Preti A. Individualized Diagnostic and Prognostic Models for Psychosis Risk Syndromes: Do Not Underestimate Antipsychotic Exposure. Biol Psychiatry 2021; 90:e33-e35. [PMID: 34001370 DOI: 10.1016/j.biopsych.2021.01.020] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 03/12/2021] [Indexed: 10/21/2022]
Affiliation(s)
- Andrea Raballo
- Section of Psychiatry, Clinical Psychology and Rehabilitation, Department of Medicine, University of Perugia, Italy; Center for Translational, Phenomenological and Developmental Psychopathology, Perugia University Hospital, Perugia, Italy.
| | - Michele Poletti
- Child and Adolescent Neuropsychiatry Service, Department of Mental Health and Pathological Addiction, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Antonio Preti
- Department of Neuroscience, University of Turin, Turin, Italy
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11
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Raballo A, Poletti M, Preti A. Negative Prognostic Effect of Baseline Antipsychotic Exposure in Clinical High Risk for Psychosis (CHR-P): Is Pre-Test Risk Enrichment the Hidden Culprit? Int J Neuropsychopharmacol 2021; 24:710-720. [PMID: 34036323 PMCID: PMC8453273 DOI: 10.1093/ijnp/pyab030] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 04/19/2021] [Accepted: 05/21/2021] [Indexed: 12/22/2022] Open
Abstract
INTRODUCTION Sample enrichment is a key factor in contemporary early-detection strategies aimed at the identification of help-seekers at increased risk of imminent transition to psychosis. We undertook a meta-analytic investigation to ascertain the role of sample enrichment in the recently highlighted negative prognostic effect of baseline antipsychotic (AP) exposure in clinical high-risk (CHR-P) of psychosis individuals. METHODS Systematic review and meta-analysis of all published studies on CHR-P were identified according to a validated diagnostic procedure. The outcome was the proportion of transition to psychosis, which was calculated according to the Freeman-Tukey double arcsine transformation. RESULTS Thirty-three eligible studies were identified, including 16 samples with details on AP exposure at baseline and 17 samples with baseline AP exposure as exclusion criterion for enrollment. Those with baseline exposure to AP (n = 395) had higher transition rates (29.9%; 95% CI: 25.1%-34.8%) than those without baseline exposure to AP in the same study (n = 1289; 17.2%; 15.1%-19.4%) and those coming from samples that did not include people who were exposed to AP at baseline (n = 2073; 16.2%; 14.6%-17.8%; P < .05 in both the fixed-effects and the random-effects models). Heterogeneity within studies was substantial, with values above 75% in all comparisons. CONCLUSIONS Sample enrichment is not a plausible explanation for the higher risk of transition to psychosis of CHR-P individuals who were already exposed to AP at the enrollment in specialized early-detection programs. Baseline exposure to AP at CHR-P assessment is a major index of enhanced, imminent risk of psychosis.
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Affiliation(s)
- Andrea Raballo
- Section of Psychiatry, Clinical Psychology and Rehabilitation, Department of Medicine, University of Perugia, Perugia, Italy,Center for Translational, Phenomenological and Developmental Psychopathology (CTPDP), Perugia University Hospital, Perugia, Italy,Correspondence: Andrea Raballo, MD, PhD, Section of Psychiatry, Clinical Psychology and Rehabilitation, Department of Medicine, University of Perugia Piazzale Lucio Severi 1, 06132, Perugia, Italy ()
| | - Michele Poletti
- Department of Mental Health and Pathological Addiction, Child and Adolescent Neuropsychiatry Service, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Antonio Preti
- Department of Neuroscience, University of Turin, Turin, Italy
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Worthington MA, Cannon TD. Prediction and Prevention in the Clinical High-Risk for Psychosis Paradigm: A Review of the Current Status and Recommendations for Future Directions of Inquiry. Front Psychiatry 2021; 12:770774. [PMID: 34744845 PMCID: PMC8569129 DOI: 10.3389/fpsyt.2021.770774] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 09/27/2021] [Indexed: 11/13/2022] Open
Abstract
Prediction and prevention of negative clinical and functional outcomes represent the two primary objectives of research conducted within the clinical high-risk for psychosis (CHR-P) paradigm. Several multivariable "risk calculator" models have been developed to predict the likelihood of developing psychosis, although these models have not been translated to clinical use. Overall, less progress has been made in developing effective interventions. In this paper, we review the existing literature on both prediction and prevention in the CHR-P paradigm and, primarily, outline ways in which expanding and combining these paths of inquiry could lead to a greater improvement in individual outcomes for those most at risk.
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Affiliation(s)
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT, United States.,Department of Psychiatry, Yale University, New Haven, CT, United States
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Individualized Diagnostic and Prognostic Models for Patients With Psychosis Risk Syndromes: A Meta-analytic View on the State of the Art. Biol Psychiatry 2020; 88:349-360. [PMID: 32305218 DOI: 10.1016/j.biopsych.2020.02.009] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/25/2020] [Accepted: 02/06/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND The clinical high risk (CHR) paradigm has facilitated research into the underpinnings of help-seeking individuals at risk for developing psychosis, aiming at predicting and possibly preventing transition to the overt disorder. Statistical methods such as machine learning and Cox regression have provided the methodological basis for this research by enabling the construction of diagnostic models (i.e., distinguishing CHR individuals from healthy individuals) and prognostic models (i.e., predicting a future outcome) based on different data modalities, including clinical, neurocognitive, and neurobiological data. However, their translation to clinical practice is still hindered by the high heterogeneity of both CHR populations and methodologies applied. METHODS We systematically reviewed the literature on diagnostic and prognostic models built on Cox regression and machine learning. Furthermore, we conducted a meta-analysis on prediction performances investigating heterogeneity of methodological approaches and data modality. RESULTS A total of 44 articles were included, covering 3707 individuals for prognostic studies and 1052 individuals for diagnostic studies (572 CHR patients and 480 healthy control subjects). CHR patients could be classified against healthy control subjects with 78% sensitivity and 77% specificity. Across prognostic models, sensitivity reached 67% and specificity reached 78%. Machine learning models outperformed those applying Cox regression by 10% sensitivity. There was a publication bias for prognostic studies yet no other moderator effects. CONCLUSIONS Our results may be driven by substantial clinical and methodological heterogeneity currently affecting several aspects of the CHR field and limiting the clinical implementability of the proposed models. We discuss conceptual and methodological harmonization strategies to facilitate more reliable and generalizable models for future clinical practice.
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Carrión RE, Auther AM, McLaughlin D, Olsen R, Addington J, Bearden CE, Cadenhead KS, Cannon TD, Mathalon DH, McGlashan TH, Perkins DO, Seidman LJ, Tsuang MT, Walker EF, Woods SW, Cornblatt BA. The Global Functioning: Social and Role Scales-Further Validation in a Large Sample of Adolescents and Young Adults at Clinical High Risk for Psychosis. Schizophr Bull 2019; 45:763-772. [PMID: 30351423 PMCID: PMC6581127 DOI: 10.1093/schbul/sby126] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVE Traditional measures for assessing functioning with adult patients with schizophrenia have been shown to be insufficient for assessing the issues that occur in adolescents and young adults at clinical high risk (CHR) for psychosis. The current study provides an expanded validation of the Global Functioning: Social (GF:Social) and Role (GF:Role) scales developed specifically for use with CHR individuals and explores the reliability and accuracy of the ratings, the validity of the scores in comparison to other established clinical measures, stability of functioning over a 2-year period, and psychosis predictive ability. METHODS Seven hundred fifty-five CHR individuals and 277 healthy control (HC) participants completed the GF:Social and Role scales at baseline as part of the North American Prodrome Longitudinal Study (NAPLS2). RESULTS Inter-rater reliability and accuracy were high for both scales. Correlations between the GF scores and other established clinical measures demonstrated acceptable convergent and discriminant validity. In addition, GF:Social and Role scores were unrelated to positive symptoms. CHR participants showed large impairments in social and role functioning over 2-years, relative to the HCs, even after adjusting for age, IQ, and attenuated positive symptoms. Finally, social decline prior to baseline was more pronounced in CHR converters, relative to non-converters. CONCLUSIONS The GF scales can be administered in a large-scale multi-site study with excellent inter-rater reliability and accuracy. CHR individuals showed social and role functioning impairments over time that were not confounded by positive symptom severity levels. The results of this study demonstrate that social decline is a particularly effective predictor of conversion outcome.
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Affiliation(s)
- Ricardo E Carrión
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY,Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY,To whom correspondence should be addressed; Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, 75-59, 263rd Street, Glen Oaks, NY 11004, US; tel: 718-470-8878, fax: 718-470-8131, e-mail:
| | - Andrea M Auther
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY
| | - Danielle McLaughlin
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY
| | - Ruth Olsen
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY
| | - Jean Addington
- Hotchkiss Brain Institute, Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior and Department of Psychology, University of California, Los Angeles, Los Angeles, CA
| | | | - Tyrone D Cannon
- Department of Psychology, Yale University, School of Medicine, New Haven, CT,Department of Psychiatry, Yale University, School of Medicine, New Haven, CT
| | - Daniel H Mathalon
- Department of Psychiatry, University of California, San Francisco, CA
| | - Thomas H McGlashan
- Department of Psychiatry, Yale University, School of Medicine, New Haven, CT
| | - Diana O Perkins
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Larry J Seidman
- Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, Boston, MA
| | - Ming T Tsuang
- Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, Boston, MA
| | | | - Scott W Woods
- Department of Psychiatry, Yale University, School of Medicine, New Haven, CT
| | - Barbara A Cornblatt
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY,Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY,Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY
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15
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Short clinically-based prediction model to forecast transition to psychosis in individuals at clinical high risk state. Eur Psychiatry 2019; 58:72-79. [DOI: 10.1016/j.eurpsy.2019.02.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 02/26/2019] [Accepted: 02/27/2019] [Indexed: 12/19/2022] Open
Abstract
AbstractObjective:The predictive accuracy of the Clinical High Risk criteria for Psychosis (CHR-P) regarding the future development of the disorder remains suboptimal. It is therefore necessary to incorporate refined risk estimation tools which can be applied at the individual subject level. The aim of the study was to develop an easy-to use, short refined risk estimation tool to predict the development of psychosis in a new CHR-P cohort recruited in European country with less established early detection services.Methods:A cohort of 105 CHR-P individuals was assessed with the Comprehensive Assessment of At Risk Mental States12/2006, and then followed for a median period of 36 months (25th-75th percentile:10–59 months) for transition to psychosis. A multivariate Cox regression model predicting transition was generated with preselected clinical predictors and was internally validated with 1000 bootstrap resamples.Results:Speech disorganization and unusual thought content were selected as potential predictors of conversion on the basis of published literature. The prediction model was significant (p < 0.0001) and confirmed that both speech disorganization (HR = 1.69; 95%CI: 1.39–2.05) and unusual thought content (HR = 1.51; 95%CI: 1.27–1.80) were significantly associated with transition. The prognostic accuracy of the model was adequate (Harrell’s c- index = 0.79), even after optimism correction through internal validation procedures (Harrell’s c-index = 0.78).Conclusions:The clinical prediction model developed, and internally validated, herein to predict transition from a CHR-P to psychosis may be a promising tool for use in clinical settings. It has been incorporated into an online tool available at:https://link.konsta.com.pl/psychosis. Future external replication studies are needed.
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Kim HK, Park HY, Seo E, Bang M, Song YY, Lee SY, Kim KR, Park JY, Kang JI, Lee E, An SK. Factors Associated With Psychosocial Functioning and Outcome of Individuals With Recent-Onset Schizophrenia and at Ultra-High Risk for Psychosis. Front Psychiatry 2019; 10:459. [PMID: 31293463 PMCID: PMC6606785 DOI: 10.3389/fpsyt.2019.00459] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Accepted: 06/11/2019] [Indexed: 01/31/2023] Open
Abstract
Background: Patients with schizophrenia have impairments in social functioning and are readmitted to healthcare institutions frequently. Individuals at ultra-high risk (UHR) for psychosis already present poor social functioning; among those individuals, the conversion rate from the putative prodromal phase to overt psychosis is 20%-30% within 1-2 years. Here, we analyzed the factor structure of self-related variables and neuro- and socio-cognitive function, and investigated whether these factors were associated with psychosocial function and prognostic outcome in individuals with recent-onset schizophrenia (ROSPR) or at UHR for psychosis. Methods: We evaluated 60 individuals at UHR for psychosis, 47 individuals with ROSPR, and 71 healthy controls using a comprehensive neurocognitive test battery and self-reported attribution scales, self-esteem, resilience, aberrant subjective experiences of schizotypy (physical anhedonia, social anhedonia, magical ideation, and perceptual aberration), and basic symptoms. We assessed psychosocial function with the Quality of Life Scale (QLS). Results: Factor analysis of all subjects revealed a four-factor structure comprising social-cognitive bias, reflective self, neurocognition, and pre-reflective self factors. Multiple regression analysis at baseline revealed that the factor structure predicted QLS. In the UHR group, social-cognitive bias, reflective self, neurocognition, and negative symptoms were significant determinants, explaining 38.0% of total QLS score variance. In the ROSPR group, reflective self and negative symptoms were significant determinants, explaining 54.4% of total QLS score variance. During follow-up, 13 individuals at UHR for psychosis developed psychosis (cumulative prevalence: 31.2% ± 7.6% at 6 years), with neurocognition score at baseline remaining a significant predictor of conversion [χ2(1) = 4.009, p = 0.045; hazard ratio 0.56, 95% confidence interval 0.31-0.99, p = 0.048]. Five patients with schizophrenia were (re)admitted during follow-up (cumulative prevalence: 16.1% ± 7.1% at 6 years); no factor was found to predict (re)admission. Conclusion: Factor analysis revealed an intrinsic four-factor structure of social-cognitive bias, reflective self, neurocognition, and pre-reflective self. The four factors were associated with social functioning at baseline and prodrome-to-psychosis conversion during follow-up, indicating the clinical significance of the four-factor structure. These findings provide a framework for understanding schizophrenia.
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Affiliation(s)
- Hyun Kyu Kim
- Department of Psychiatry, Yonsei University College of Medicine, Severance Hospital, Seoul, South Korea.,Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Hye Yoon Park
- Department of Psychiatry, Yonsei University College of Medicine, Severance Hospital, Seoul, South Korea.,Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Eunchong Seo
- Department of Psychiatry, Yonsei University College of Medicine, Severance Hospital, Seoul, South Korea.,Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Minji Bang
- Department of Psychiatry, CHA Bundang Medical Center, CHA University, Seongnam, South Korea
| | - Yun Young Song
- Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Su Young Lee
- Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea.,Department of Psychiatry, Myongji Hospital, Hanyang University College of Medicine, Goyang, South Korea
| | - Kyung Ran Kim
- Department of Psychiatry, Yonsei University College of Medicine, Severance Hospital, Seoul, South Korea.,Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Jin Young Park
- Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea.,Department of Psychiatry, Yonsei University College of Medicine, Gangnam Severance Hospital, Seoul, South Korea
| | - Jee In Kang
- Department of Psychiatry, Yonsei University College of Medicine, Severance Hospital, Seoul, South Korea.,Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Eun Lee
- Department of Psychiatry, Yonsei University College of Medicine, Severance Hospital, Seoul, South Korea.,Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Suk Kyoon An
- Department of Psychiatry, Yonsei University College of Medicine, Severance Hospital, Seoul, South Korea.,Section of Self, Affect and Neuroscience, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, South Korea.,Graduate Program in Cognitive Science, Yonsei University, Seoul, South Korea
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17
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Deriu V, Moro MR, Benoit L. Early intervention for everyone? A review of cross-cultural issues and their treatment in ultra-high-risk (UHR) cohorts. Early Interv Psychiatry 2018; 12:796-810. [PMID: 29708310 DOI: 10.1111/eip.12671] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Revised: 02/06/2018] [Accepted: 03/13/2018] [Indexed: 12/15/2022]
Abstract
AIM Over the past 20 years, early management of psychosis has become both a research and policy priority. In Western countries, psychotic disorders appear more prevalent in migrant and minority ethnic groups than in native or dominant groups. Moreover, disparities exist in health conditions and access to care among immigrants and minority ethnic groups, compared with native-born and majority groups. Appropriate early detection tools are necessary for the different groups. METHODS This systematic review provides a synthesis of the assessment and discussion of transcultural issues in ultra-high-risk (UHR) cohorts. The Medline database was searched via PubMed for peer-reviewed articles published in English from 1995 to 2017. All 79 studies included are prospective UHR cohort studies that used the Comprehensive Assessment of At-Risk Mental States (CAARMS). RESULTS In UHR cohort studies that used the CAARMS, transcultural data (native language, ethnicity, place of birth, migration) are rarely collected, and inadequate ability to speak the dominant language is a common exclusion criterion. When they are included, the CAARMS scores differ between some minorities and the native-born majority group. CONCLUSIONS This systematic review demonstrates barriers to the access to participation in early intervention research for migrants and ethnic minorities. This selection bias may result in lower validity for the CAARMS among these populations and thus in inadequate intervention programmes. Along with targeted studies, minorities' access to participation in UHR cohorts should be improved through 3 tools: interpreters at recruitment and for administration of CAARMS, a guide to cultural formulation and transcultural data collection.
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Affiliation(s)
| | - Marie Rose Moro
- Head of department at Maison de Solenn, Hôpital Cochin (AP-HP), Paris, France.,Professor of Child and Adolescent Psychiatry, Faculty of Medicine, Université Paris Descartes, Paris, France
| | - Laelia Benoit
- Maison de Solenn, Hôpital Cochin (AP-HP), Unité INSERM/CESP, Paris, France
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Oliver D, Kotlicka-Antczak M, Minichino A, Spada G, McGuire P, Fusar-Poli P. Meta-analytical prognostic accuracy of the Comprehensive Assessment of at Risk Mental States (CAARMS): The need for refined prediction. Eur Psychiatry 2018; 49:62-68. [PMID: 29413807 DOI: 10.1016/j.eurpsy.2017.10.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 10/04/2017] [Accepted: 10/04/2017] [Indexed: 10/18/2022] Open
Abstract
Primary indicated prevention is reliant on accurate tools to predict the onset of psychosis. The gold standard assessment for detecting individuals at clinical high risk (CHR-P) for psychosis in the UK and many other countries is the Comprehensive Assessment for At Risk Mental States (CAARMS). While the prognostic accuracy of CHR-P instruments has been assessed in general, this is the first study to specifically analyse that of the CAARMS. As such, the CAARMS was used as the index test, with the reference index being psychosis onset within 2 years. Six independent studies were analysed using MIDAS (STATA 14), with a total of 1876 help-seeking subjects referred to high risk services (CHR-P+: n=892; CHR-P-: n=984). Area under the curve (AUC), summary receiver operating characteristic curves (SROC), quality assessment, likelihood ratios, and probability modified plots were computed, along with sensitivity analyses and meta-regressions. The current meta-analysis confirmed that the 2-year prognostic accuracy of the CAARMS is only acceptable (AUC=0.79 95% CI: 0.75-0.83) and not outstanding as previously reported. In particular, specificity was poor. Sensitivity of the CAARMS is inferior compared to the SIPS, while specificity is comparably low. However, due to the difficulties in performing these types of studies, power in this meta-analysis was low. These results indicate that refining and improving the prognostic accuracy of the CAARMS should be the mainstream area of research for the next era. Avenues of prediction improvement are critically discussed and presented to better benefit patients and improve outcomes of first episode psychosis.
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Affiliation(s)
- D Oliver
- Early Psychosis: Interventions & Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
| | - M Kotlicka-Antczak
- Medical University of Lodz, Department of Affective and Psychotic Disorders, Lodz, Poland
| | - A Minichino
- Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
| | - G Spada
- Early Psychosis: Interventions & Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom
| | - P McGuire
- Department of Psychosis Studies, IoPPN, King's College London, London SE5 8AF, United Kingdom; OASIS Service, South London and the Maudsley NHS National Health Service Foundation Trust, London, United Kingdom; National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health, IoPPN, King's College London, SE5 8AF, United Kingdom
| | - P Fusar-Poli
- Early Psychosis: Interventions & Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom; OASIS Service, South London and the Maudsley NHS National Health Service Foundation Trust, London, United Kingdom; National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health, IoPPN, King's College London, SE5 8AF, United Kingdom
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Fusar-Poli P, Rutigliano G, Stahl D, Davies C, Bonoldi I, Reilly T, McGuire P. Development and Validation of a Clinically Based Risk Calculator for the Transdiagnostic Prediction of Psychosis. JAMA Psychiatry 2017; 74:493-500. [PMID: 28355424 PMCID: PMC5470394 DOI: 10.1001/jamapsychiatry.2017.0284] [Citation(s) in RCA: 187] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 02/08/2017] [Indexed: 12/23/2022]
Abstract
Importance The overall effect of At Risk Mental State (ARMS) services for the detection of individuals who will develop psychosis in secondary mental health care is undetermined. Objective To measure the proportion of individuals with a first episode of psychosis detected by ARMS services in secondary mental health services, and to develop and externally validate a practical web-based individualized risk calculator tool for the transdiagnostic prediction of psychosis in secondary mental health care. Design, Setting, and Participants Clinical register-based cohort study. Patients were drawn from electronic, real-world, real-time clinical records relating to 2008 to 2015 routine secondary mental health care in the South London and the Maudsley National Health Service Foundation Trust. The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and the Maudsley National Health Service Foundation Trust in the period between January 1, 2008, and December 31, 2015. Data analysis began on September 1, 2016. Main Outcomes and Measures Risk of development of nonorganic International Statistical Classification of Diseases and Related Health Problems, Tenth Revision psychotic disorders. Results A total of 91 199 patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within South London and the Maudsley National Health Service Foundation Trust were included in the derivation (n = 33 820) or external validation (n = 54 716) data sets. The mean age was 32.97 years, 50.88% were men, and 61.05% were white race/ethnicity. The mean follow-up was 1588 days. The overall 6-year risk of psychosis in secondary mental health care was 3.02 (95% CI, 2.88-3.15), which is higher than the 6-year risk in the local general population (0.62). Compared with the ARMS designation, all of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses showed a lower risk of psychosis, with the exception of bipolar mood disorders (similar risk) and brief psychotic episodes (higher risk). The ARMS designation accounted only for a small proportion of transitions to psychosis (n = 52 of 1001; 5.19% in the derivation data set), indicating the need for transdiagnostic prediction of psychosis in secondary mental health care. A prognostic risk stratification model based on preselected variables, including index diagnosis, age, sex, age by sex, and race/ethnicity, was developed and externally validated, showing good performance and potential clinical usefulness. Conclusions and Relevance This online individualized risk calculator can be of clinical usefulness for the transdiagnostic prediction of psychosis in secondary mental health care. The risk calculator can help to identify those patients at risk of developing psychosis who require an ARMS assessment and specialized care. The use of this calculator may eventually facilitate the implementation of an individualized provision of preventive focused interventions and improve outcomes of first episode psychosis.
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Affiliation(s)
- Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
- Outreach and Support in South London Service, South London and the Maudsley National Health Service Foundation Trust, London, England
- National Institute for Health Research Biomedical Research Centre for Mental Health, IoPPN, King’s College London, London, England
| | - Grazia Rutigliano
- Early Psychosis: Interventions and Clinical Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Daniel Stahl
- National Institute for Health Research Biomedical Research Centre for Mental Health, IoPPN, King’s College London, London, England
- Department of Biostatistics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, England
| | - Cathy Davies
- Early Psychosis: Interventions and Clinical Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
| | - Ilaria Bonoldi
- Early Psychosis: Interventions and Clinical Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
- Outreach and Support in South London Service, South London and the Maudsley National Health Service Foundation Trust, London, England
| | - Thomas Reilly
- Early Psychosis: Interventions and Clinical Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, England
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