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Cannon TD. On the Clinical Utility of Individualized Prediction Models for Psychosis in At-Risk Youth. Biol Psychiatry 2024; 96:514-516. [PMID: 37949345 DOI: 10.1016/j.biopsych.2023.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 11/03/2023] [Accepted: 11/03/2023] [Indexed: 11/12/2023]
Affiliation(s)
- Tyrone D Cannon
- Departments of Psychology and Psychiatry, Yale University, New Haven, Connecticut.
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Deng W, Chong B, Addington J, Bearden CE, Cadenhead KS, Cornblatt BA, Keshavan M, Mathalon DH, Perkins DO, Stone W, Walker EF, Woods SW, Cannon TD. Beyond the Descriptive: A Comprehensive, Multi-domain Validation of Symptom Trajectories for Individuals at Clinical High Risk for Psychosis. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00269-6. [PMID: 39260565 DOI: 10.1016/j.bpsc.2024.08.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 08/21/2024] [Accepted: 08/28/2024] [Indexed: 09/13/2024]
Abstract
BACKGROUND Although the Clinical High-Risk for Psychosis (CHR-P) criteria are widely used to ascertain individuals at heightened risk for imminent onset of psychosis, it remains controversial whether CHR-P status define a diagnostic construct in its own right. In a prior study, CHR-P non-converters were observed to follow three distinct trajectories in symptoms and functioning: remission, partial remission, and maintenance of symptoms and functional impairments at subthreshold levels of intensity. METHODS Here, we utilized the North American Prodrome Longitudinal Study Phase 3 (NAPLS3) sample (N = 806) to determine whether: 1) the same trajectory groups can be detected when assessing symptoms at 2-month intervals over an 8-month period and 2) the resulting trajectory groups differ from each other and from healthy controls and converting CHR-P cases in terms of risk factors, comorbidities, and functional outcomes. RESULTS Three distinctive subgroups within the CHR non-converters were identified, largely paralleling those previously observed. Importantly, these extracted groups, along with non-CHR controls and CHR converters, differ from each other significantly with respect to putative etiological risk factors (e.g., predicted risk scores, physiological and self-report measures of stress), affective comorbidities, as well as functional outcomes, providing converging evidence supporting the validity of the identified trajectory groups. CONCLUSIONS This pattern, along with the fact that even the subgroup of CHR-P nonconverters showing a remission trajectory deviated from healthy controls, supports treating the CHR-P syndrome not just as a status that denotes risk for onset of full psychosis, but also as a marker of ongoing distress for a population in need of interventions.
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Affiliation(s)
| | | | | | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences and Psychology, UCLA
| | | | | | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School; Beth Israel Deaconess Hospital
| | | | | | - William Stone
- Department of Psychiatry, Harvard Medical School; Beth Israel Deaconess Hospital
| | | | | | - Tyrone D Cannon
- Department of Psychology, Yale University; Department of Psychiatry, Yale University
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Hou Y, Xia H, He T, Zhang B, Qiu G, Chen A. N2 Responses in Youths With Psychosis Risk Syndrome and Their Association With Clinical Outcomes: A Cohort Follow-Up Study Based on the Three-Stimulus Visual Oddball Paradigm. Am J Psychiatry 2024; 181:330-341. [PMID: 38419496 DOI: 10.1176/appi.ajp.20221013] [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] [Indexed: 03/02/2024]
Abstract
OBJECTIVE Schizophrenia often occurs during youth, and psychosis risk syndrome occurs before the onset of psychosis. The aim of this study was to determine whether the visual event-related potential responses in youths with psychosis risk syndrome were defective in the presence of interference stimuli and associated with their clinical outcomes. METHODS A total of 223 participants, including 122 patients with psychosis risk syndrome, 50 patients with emotional disorders, and 51 healthy control subjects, were assessed. Baseline EEG was recorded during the three-stimulus visual oddball task. The event-related potentials induced by square pictures with different colors were measured. Almost all patients with psychosis risk syndrome were followed up for 12 months and were reclassified into three subgroups: conversion, symptomatic, and remission. The differences in baseline event-related potential responses were compared among the clinical outcome subgroups. RESULTS The average N2 amplitude of the psychosis risk syndrome group was significantly less negative than that in the healthy control group (d=0.53). The baseline average N2 amplitude in the conversion subgroup was significantly less negative than that in the symptomatic (d=0.58) and remission (d=0.50) subgroups and in the healthy control group (d=0.97). The average N2 amplitude did not differ significantly between the symptomatic and remission subgroups (d=0.02). However, it was significantly less negative in the symptomatic and remission subgroups than in the healthy control group (d=0.46 and d=0.38). No statistically significant results were found in the P3 response. CONCLUSIONS Youths with psychosis risk syndrome had significant N2 amplitude defects in attention processing with interference stimuli. N2 amplitude shows potential as a prognostic biomarker of clinical outcome in the psychosis risk syndrome.
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Affiliation(s)
- Yongqing Hou
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Haishuo Xia
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Tianbao He
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Bohua Zhang
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Guiping Qiu
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Antao Chen
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
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Hou Y, Qiu G, Xia H, He T, Liu X, Chen A. The specificity of the auditory P300 responses and its association with clinical outcomes in youth with psychosis risk syndrome. Int J Clin Health Psychol 2024; 24:100437. [PMID: 38292829 PMCID: PMC10825643 DOI: 10.1016/j.ijchp.2024.100437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 01/02/2024] [Indexed: 02/01/2024] Open
Abstract
Background Schizophrenia often occurs in youth, and psychosis risk syndrome (PRS) occurs before the onset of psychosis. Assessing the neuropsychological abnormalities of PRS individuals can help in early identification and active intervention of mental illness. Auditory P300 amplitude defect is an important manifestation of attention processing abnormality in PRS, but it is still unclear whether there are abnormalities in the attention processing of rhythmic compound tone stimuli in PRS individuals, and whether the P300 amplitude induced by these stimuli is specific to PRS individuals and related to their clinical outcomes. Methods In total, 226 participants, including 122 patients with PRS, 51 patients with emotional disorders (ED), and 53 healthy controls (HC) were assessed. Baseline electroencephalography was recorded during the compound tone oddball task. The event-related potentials (ERPs) induced by rhythmic compound tone stimuli of two frequencies (20-Hz, 40-Hz) were measured. Almost all patients with PRS were followed up for 12 months and reclassified into four groups: PRS-conversion, PRS-symptomatic, PRS-emotional disorder, and PRS-complete remission. The differences in baseline ERPs were compared among the clinical outcome groups. Results Regardless of the stimulation frequency, the average P300 amplitude were significantly higher in patients with PRS than in those with ED (p = 0.003, d = 0.48) and in HC (p = 0.002, d = 0.44) group. The average P300 amplitude of PRS-conversion group was significantly higher than that of the PRS-complete remission (p = 0.016, d = 0.72) and HC group (p = 0.001, d = 0.76), and the average P300 amplitude of PRS-symptomatic group was significantly higher than that of the HC group (p = 0.006, d = 0.48). Regardless of the groups (PRS, ED, HC) or the PRS clinical outcome groups, the average P300 amplitude induced by 20-Hz tone stimulation was significantly higher than that induced by 40-Hz stimulation (ps < 0.001, Ƞ2 = 0.074-0.082). The average reaction times of PRS was significantly faster than that of ED (p = 0.01, d = 0.38), and the average reaction times of the participants to 20-Hz target stimulation was significantly faster than that to 40-Hz target stimulation (p < 0.001, d = 0.21). Conclusion The auditory P300 amplitude induced by rhythmic compound tone stimuli is a specific electrophysiological manifestation of PRS, and the auditory P300 amplitude induced by compound tone stimuli shows promise as a putative prognostic biomarker for PRS clinical outcomes, including conversion to psychosis and clinical complete remission.
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Affiliation(s)
- Yongqing Hou
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Mental Health Center of Guangyuan, Sichuan, China
| | - Guiping Qiu
- College of Teacher Education, Ningxia University, Yinchuan, China
| | - Haishuo Xia
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Tianbao He
- Mental Health Center of Guangyuan, Sichuan, China
| | - Xiaoxian Liu
- Faculty of Education, Henan Normal University, Xinxiang, China
| | - Antao Chen
- School of Psychology, Research Center for Exercise and Brain Science, Shanghai University of Sport, Shanghai, China
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Caballero N, Machiraju S, Diomino A, Kennedy L, Kadivar A, Cadenhead KS. Recent Updates on Predicting Conversion in Youth at Clinical High Risk for Psychosis. Curr Psychiatry Rep 2023; 25:683-698. [PMID: 37755654 PMCID: PMC10654175 DOI: 10.1007/s11920-023-01456-2] [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] [Accepted: 09/05/2023] [Indexed: 09/28/2023]
Abstract
PURPOSE OF REVIEW This review highlights recent advances in the prediction and treatment of psychotic conversion. Over the past 25 years, research into the prodromal phase of psychotic illness has expanded with the promise of early identification of individuals at clinical high risk (CHR) for psychosis who are likely to convert to psychosis. RECENT FINDINGS Meta-analyses highlight conversion rates between 20 and 30% within 2-3 years using existing clinical criteria while research into more specific risk factors, biomarkers, and refinement of psychosis risk calculators has exploded, improving our ability to predict psychotic conversion with greater accuracy. Recent studies highlight risk factors and biomarkers likely to contribute to earlier identification and provide insight into neurodevelopmental abnormalities, CHR subtypes, and interventions that can target specific risk profiles linked to neural mechanisms. Ongoing initiatives that assess longer-term (> 5-10 years) outcome of CHR participants can provide valuable information about predictors of later conversion and diagnostic outcomes while large-scale international biomarker studies provide hope for precision intervention that will alter the course of early psychosis globally.
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Affiliation(s)
- Noe Caballero
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Siddharth Machiraju
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Anthony Diomino
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Leda Kennedy
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Armita Kadivar
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Kristin S Cadenhead
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA.
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Worthington MA, Addington J, Bearden CE, Cadenhead KS, Cornblatt BA, Keshavan M, Lympus CA, Mathalon DH, Perkins DO, Stone WS, Walker EF, Woods SW, Zhao Y, Cannon TD. Dynamic Prediction of Outcomes for Youth at Clinical High Risk for Psychosis: A Joint Modeling Approach. JAMA Psychiatry 2023; 80:1017-1025. [PMID: 37531131 PMCID: PMC10398543 DOI: 10.1001/jamapsychiatry.2023.2378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/03/2023] [Indexed: 08/03/2023]
Abstract
Importance Leveraging the dynamic nature of clinical variables in the clinical high risk for psychosis (CHR-P) population has the potential to significantly improve the performance of outcome prediction models. Objective To improve performance of prediction models and elucidate dynamic clinical profiles using joint modeling to predict conversion to psychosis and symptom remission. Design, Setting, and Participants Data were collected as part of the third wave of the North American Prodrome Longitudinal Study (NAPLS 3), which is a 9-site prospective longitudinal study. Participants were individuals aged 12 to 30 years who met criteria for a psychosis-risk syndrome. Clinical, neurocognitive, and demographic variables were collected at baseline and at multiple follow-up visits, beginning at 2 months and up to 24 months. An initial feature selection process identified longitudinal clinical variables that showed differential change for each outcome group across 2 months. With these variables, a joint modeling framework was used to estimate the likelihood of eventual outcomes. Models were developed and tested in a 10-fold cross-validation framework. Clinical data were collected between February 2015 and November 2018, and data were analyzed from February 2022 to December 2023. Main Outcomes and Measures Prediction models were built to predict conversion to psychosis and symptom remission. Participants met criteria for conversion if their positive symptoms reached the fully psychotic range and for symptom remission if they were subprodromal on the Scale of Psychosis-Risk Symptoms for a duration of 6 months or more. Results Of 488 included NAPLS 3 participants, 232 (47.5%) were female, and the mean (SD) age was 18.2 (3.4) years. Joint models achieved a high level of accuracy in predicting conversion (balanced accuracy [BAC], 0.91) and remission (BAC, 0.99) compared with baseline models (conversion: BAC, 0.65; remission: BAC, 0.60). Clinical variables that showed differential change between outcome groups across a 2-month span, including measures of symptom severity and aspects of functioning, were also identified. Further, intra-individual risks for each outcome were more negatively correlated when using joint models (r = -0.92; P < .001) compared with baseline models (r = -0.50; P < .001). Conclusions and Relevance In this study, joint models significantly outperformed baseline models in predicting both conversion and remission, demonstrating that monitoring short-term clinical change may help to parse heterogeneous dynamic clinical trajectories in a CHR-P population. These findings could inform additional study of targeted treatment selection and could move the field closer to clinical implementation of prediction models.
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Affiliation(s)
| | - Jean Addington
- Hotchkiss Brain Institute, Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Carrie E. Bearden
- Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, Department of Psychology, University of California, Los Angeles
| | | | | | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, Boston
| | - Cole A. Lympus
- Department of Psychology, Rutgers University, New Brunswick, New Jersey
| | - Daniel H. Mathalon
- Department of Psychiatry, San Francisco VA Medical Center, University of California, San Francisco
| | - Diana O. Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, Boston
| | - Elaine F. Walker
- Department of Psychology, Emory University, Atlanta, Georgia
- Department of Psychiatry, Emory University, Atlanta, Georgia
| | - Scott W. Woods
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Yize Zhao
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut
| | - Tyrone D. Cannon
- Department of Psychology, Yale University, New Haven, Connecticut
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
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Investigation of social and cognitive predictors in non-transition ultra-high-risk' individuals for psychosis using spiking neural networks. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:10. [PMID: 36792634 PMCID: PMC9931713 DOI: 10.1038/s41537-023-00335-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 01/26/2023] [Indexed: 02/17/2023]
Abstract
Finding predictors of social and cognitive impairment in non-transition Ultra-High-Risk individuals (UHR) is critical in prognosis and planning of potential personalised intervention strategies. Social and cognitive functioning observed in youth at UHR for psychosis may be protective against transition to clinically relevant illness. The current study used a computational method known as Spiking Neural Network (SNN) to identify the cognitive and social predictors of transitioning outcome. Participants (90 UHR, 81 Healthy Control (HC)) completed batteries of neuropsychological tests in the domains of verbal memory, working memory, processing speed, attention, executive function along with social skills-based performance at baseline and 4 × 6-month follow-up intervals. The UHR status was recorded as Remitters, Converters or Maintained. SNN were used to model interactions between variables across groups over time and classify UHR status. The performance of SNN was examined relative to other machine learning methods. Higher interaction between social and cognitive variables was seen for the Maintained, than Remitter subgroup. Findings identified the most important cognitive and social variables (particularly verbal memory, processing speed, attention, affect and interpersonal social functioning) that showed discriminative patterns in the SNN models of HC vs UHR subgroups, with accuracies up to 80%; outperforming other machine learning models (56-64% based on 18 months data). This finding is indicative of a promising direction for early detection of social and cognitive impairment in UHR individuals that may not anticipate transition to psychosis and implicate early initiated interventions to stem the impact of clinical symptoms of psychosis.
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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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