University of Groningen Individualized Prediction of Transition to Psychosis in 1 , 676 Individuals at Clinical High Risk

Citation for published version (APA): Malda, A., Boonstra, N., Barf, H., de Jong, S., Aleman, A., Addington, J., ... Pijnenborg, G. H. M. (2019). Individualized Prediction of Transition to Psychosis in 1,676 Individuals at Clinical High Risk: Development and Validation of a Multivariable Prediction Model Based on Individual Patient Data Meta-Analysis. Frontiers in Psychiatry, 10, 345. [345]. https://doi.org/10.3389/fpsyt.2019.00345, https://doi.org/10.3389/fpsyt.2019.00345

[1]  J. Higgins,et al.  Cochrane Handbook for Systematic Reviews of Interventions , 2010, International Coaching Psychology Review.

[2]  R. Dobson,et al.  Real World Implementation of a Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk of Psychosis in Clinical Routine: Study Protocol , 2019, Front. Psychiatry.

[3]  Jie Ma,et al.  A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models. , 2019, Journal of clinical epidemiology.

[4]  Ewout W. Steyerberg,et al.  The Science of Prognosis in Psychiatry: A Review , 2018, JAMA psychiatry.

[5]  P. McGuire,et al.  Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk and the Prediction of Psychosis: Second Replication in an Independent National Health Service Trust , 2018, Schizophrenia bulletin.

[6]  Nancy C. Andreasen,et al.  Scale for the Assessment of Positive Symptoms , 2018 .

[7]  P. McGuire,et al.  Lack of evidence to favor specific preventive interventions in psychosis: a network meta‐analysis , 2018, World psychiatry : official journal of the World Psychiatric Association.

[8]  R. Murray,et al.  What causes psychosis? An umbrella review of risk and protective factors , 2018, World psychiatry : official journal of the World Psychiatric Association.

[9]  P. Mcguire,et al.  WHY TRANSITION RISK TO PSYCHOSIS IS NOT DECLINING AT THE OASIS ULTRA HIGH RISK SERVICE: THE HIDDEN ROLE OF STABLE PRETEST RISK ENRICHMENT , 2017 .

[10]  P. Falkai,et al.  Prediction Models of Functional Outcomes for Individuals in the Clinical High-Risk State for Psychosis or With Recent-Onset Depression: A Multimodal, Multisite Machine Learning Analysis. , 2018, JAMA psychiatry.

[11]  A. Riecher-Rössler,et al.  Correlations between self‐rating and observer‐rating of psychopathology in at‐risk mental state and first‐episode psychosis patients: influence of disease stage and gender , 2017, Early intervention in psychiatry.

[12]  P. Fusar-Poli.  Why ultra high risk criteria for psychosis prediction do not work well outside clinical samples and what to do about it , 2017, World psychiatry : official journal of the World Psychiatric Association.

[13]  Paolo Fusar-Poli,et al.  Development and Validation of a Clinically Based Risk Calculator for the Transdiagnostic Prediction of Psychosis , 2017, JAMA psychiatry.

[14]  P. McGuire,et al.  Long-term validity of the At Risk Mental State (ARMS) for predicting psychotic and non-psychotic mental disorders , 2017, European Psychiatry.

[15]  M. Pruessner,et al.  The Clinic for Assessment of Youth at Risk (CAYR): 10 years of service delivery and research targeting the prevention of psychosis in Montreal, Canada , 2017, Early intervention in psychiatry.

[16]  P. Mcguire,et al.  Deconstructing Vulnerability for Psychosis: Meta-Analysis of Environmental Risk Factors for Psychosis in Subjects at Ultra High-Risk , 2017, European Psychiatry.

[17]  A. Riecher-Rössler,et al.  Prediction of transition to psychosis in patients with a clinical high risk for psychosis: a systematic review of methodology and reporting , 2017, Psychological Medicine.

[18]  P. McGuire,et al.  Improving Prognostic Accuracy in Subjects at Clinical High Risk for Psychosis: Systematic Review of Predictive Models and Meta-analytical Sequential Testing Simulation , 2016, Schizophrenia bulletin.

[19]  P. Fusar-Poli.  The Clinical High-Risk State for Psychosis (CHR-P), Version II , 2017, Schizophrenia bulletin.

[20]  P. McGuire,et al.  Deconstructing Pretest Risk Enrichment to Optimize Prediction of Psychosis in Individuals at Clinical High Risk. , 2016, JAMA psychiatry.

[21]  C. Carter,et al.  Personalized Prediction of Psychosis: External Validation of the NAPLS-2 Psychosis Risk Calculator With the EDIPPP Project. , 2016, The American journal of psychiatry.

[22]  Tyrone D. Cannon,et al.  An Individualized Risk Calculator for Research in Prodromal Psychosis. , 2016, The American journal of psychiatry.

[23]  Richard D Riley,et al.  External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges , 2016, BMJ.

[24]  Tae Young Lee,et al.  Towards a Standard Psychometric Diagnostic Interview for Subjects at Ultra High Risk of Psychosis: CAARMS versus SIPS , 2016, Psychiatry journal.

[25]  Marcia K. Johnson,et al.  Cross-trial prediction of treatment outcome in depression: a machine learning approach. , 2016, The lancet. Psychiatry.

[26]  Tae Young Lee,et al.  Heterogeneity of Psychosis Risk Within Individuals at Clinical High Risk: A Meta-analytical Stratification. , 2016, JAMA psychiatry.

[27]  T. McGlashan,et al.  The Dark Side of the Moon: Meta-analytical Impact of Recruitment Strategies on Risk Enrichment in the Clinical High Risk State for Psychosis Paolo Fusar-Poli*,1–3, Frauke Schultze-Lutter4, Marco Cappucciati1,3, Grazia Rutigliano1, Ilaria Bonoldi1–3, Daniel Stahl5, Stephan Borgwardt6, Anita Riecher-R , 2015 .

[28]  F. Crescenzo,et al.  Twelve-month psychosis-predictive value of the ultra-high risk criteria in children and adolescents , 2015, Schizophrenia Research.

[29]  T. McGlashan,et al.  At risk or not at risk? A meta‐analysis of the prognostic accuracy of psychometric interviews for psychosis prediction , 2015, World psychiatry : official journal of the World Psychiatric Association.

[30]  Johannes B. Reitsma,et al.  Individual Participant Data (IPD) Meta-analyses of Diagnostic and Prognostic Modeling Studies: Guidance on Their Use , 2015, PLoS medicine.

[31]  P. McGuire,et al.  Disorder, not just state of risk: Meta-analysis of functioning and quality of life in people at high risk of psychosis , 2015, British Journal of Psychiatry.

[32]  I. Falkenberg,et al.  Why are help-seeking subjects at ultra-high risk for psychosis help-seeking? , 2015, Psychiatry Research.

[33]  A. Pawełczyk,et al.  PORT (Programme of Recognition and Therapy): the first Polish recognition and treatment programme for patients with an at‐risk mental state , 2015, Early intervention in psychiatry.

[34]  Xian-tao Zeng,et al.  The methodological quality assessment tools for preclinical and clinical studies, systematic review and meta‐analysis, and clinical practice guideline: a systematic review , 2015, Journal of evidence-based medicine.

[35]  Christoph Engel,et al.  Breast Cancer Risks and Risk Prediction Models , 2015, Breast Care.

[36]  G. Collins,et al.  Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement , 2015, Annals of Internal Medicine.

[37]  D. Mathalon,et al.  Symptom assessment in early psychosis: The use of well-established rating scales in clinical high-risk and recent-onset populations , 2014, Psychiatry Research.

[38]  L. Bour,et al.  Psychosis prediction: stratification of risk estimation with information-processing and premorbid functioning variables. , 2014, Schizophrenia bulletin.

[39]  Kazunori Matsumoto,et al.  A naturalistic longitudinal study of at-risk mental state with a 2.4year follow-up at a specialized clinic setting in Japan , 2014, Schizophrenia Research.

[40]  H. van Engeland,et al.  Neurocognitive and Clinical Predictors of Long-Term Outcome in Adolescents at Ultra-High Risk for Psychosis: A 6-Year Follow-Up , 2014, PloS one.

[41]  Stephan Ruhrmann,et al.  Improving the clinical prediction of psychosis by combining ultra-high risk criteria and cognitive basic symptoms , 2014, Schizophrenia Research.

[42]  Daniel H. Mathalon,et al.  Converting positive and negative symptom scores between PANSS and SAPS/SANS , 2014, Schizophrenia Research.

[43]  Richard D Riley,et al.  Developing and validating risk prediction models in an individual participant data meta-analysis , 2014, BMC Medical Research Methodology.

[44]  Spiros Denaxas,et al.  Prognostic models for stable coronary artery disease based on electronic health record cohort of 102 023 patients , 2013, European heart journal.

[45]  P. Tugwell,et al.  The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-Analyses , 2014 .

[46]  P. Cuijpers,et al.  Preventing a first episode of psychosis: Meta-analysis of randomized controlled prevention trials of 12month and longer-term follow-ups , 2013, Schizophrenia Research.

[47]  Karel G M Moons,et al.  A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta‐analysis , 2013, Statistics in medicine.

[48]  Hok Pan Yuen,et al.  Long-term follow-up of a group at ultra high risk ("prodromal") for psychosis: the PACE 400 study. , 2013, JAMA psychiatry.

[49]  P. Mcguire,et al.  Outreach and support in South London (OASIS), 2001–2011: Ten years of early diagnosis and treatment for young individuals at high clinical risk for psychosis , 2013, European Psychiatry.

[50]  A. Aleman,et al.  Two subdomains of negative symptoms in psychotic disorders: established and confirmed in two large cohorts. , 2013, Journal of psychiatric research.

[51]  Hyun Kang.  The prevention and handling of the missing data , 2013, Korean journal of anesthesiology.

[52]  H. Yamasue,et al.  A multimodal approach to investigate biomarkers for psychosis in a clinical setting: The integrative neuroimaging studies in schizophrenia targeting for early intervention and prevention (IN-STEP) project , 2013, Schizophrenia Research.

[53]  M. Kempton,et al.  Predicting Psychosis: Meta-analysis of Transition Outcomes in Individuals at High Clinical Risk , 2013 .

[54]  P. Cuijpers,et al.  Cognitive behavioral therapy for subjects at ultrahigh risk for developing psychosis: a randomized controlled clinical trial. , 2012, Schizophrenia bulletin.

[55]  Tyrone D. Cannon,et al.  Negative symptoms in individuals at clinical high risk of psychosis , 2012, Psychiatry Research.

[56]  M. Woodward,et al.  Risk prediction models: II. External validation, model updating, and impact assessment , 2012, Heart.

[57]  P. McGuire,et al.  Disorganization/cognitive and negative symptom dimensions in the at-risk mental state predict subsequent transition to psychosis. , 2012, Schizophrenia bulletin.

[58]  Lu Liu,et al.  A randomized controlled trial of cognitive behavioral therapy for individuals at clinical high risk of psychosis , 2011, Schizophrenia Research.

[59]  J. Y. Park,et al.  Attribution bias in ultra-high risk for psychosis and first-episode schizophrenia , 2010, Schizophrenia Research.

[60]  N. Obuchowski,et al.  Assessing the Performance of Prediction Models: A Framework for Traditional and Novel Measures , 2010, Epidemiology.

[61]  T. van Amelsvoort,et al.  Prescription of antipsychotic medication to patients at ultra high risk of developing psychosis , 2009, International clinical psychopharmacology.

[62]  I. White,et al.  Imputing missing covariate values for the Cox model , 2009, Statistics in medicine.

[63]  Yvonne Vergouwe,et al.  Prognosis and prognostic research: what, why, and how? , 2009, BMJ : British Medical Journal.

[64]  J. Klosterkötter,et al.  Early detection of psychosis – Establishing a service for persons at risk , 2009, European Psychiatry.

[65]  U. Gschwandtner,et al.  [The Basel Screening Instrument for Psychosis (BSIP): development, structure, reliability and validity]. , 2008, Fortschritte der Neurologie-Psychiatrie.

[66]  T. B. Üstün,et al.  Age of onset of mental disorders: a review of recent literature , 2007, Current opinion in psychiatry.

[67]  R. Bentall,et al.  Three-year follow-up of a randomized controlled trial of cognitive therapy for the prevention of psychosis in people at ultrahigh risk. , 2007, Schizophrenia bulletin.

[68]  U. Gschwandtner,et al.  The Basel early‐detection‐of‐psychosis (FEPSY)‐study – design and preliminary results , 2007, Acta psychiatrica Scandinavica.

[69]  A. Yung,et al.  Mapping the Onset of Psychosis: The Comprehensive Assessment of At-Risk Mental States , 2005 .

[70]  Pierre Côté,et al.  Loss to Follow-Up in Cohort Studies: How Much is Too Much? , 2003, European Journal of Epidemiology.

[71]  R. Hoffman,et al.  Symptom Assessment in Schizophrenic Prodromal States , 2004, Psychiatric Quarterly.

[72]  Sunil J Rao,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2003 .

[73]  Godfrey D Pearlson,et al.  Prodromal assessment with the structured interview for prodromal syndromes and the scale of prodromal symptoms: predictive validity, interrater reliability, and training to reliability. , 2003, Schizophrenia bulletin.

[74]  M. First,et al.  Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research version (SCID-I RV) , 2002 .

[75]  P. Royston,et al.  The Lognormal Distribution as a Model for Survival Time in Cancer, With an Emphasis on Prognostic Factors , 2001 .

[76]  K. Nuechterlein,et al.  Symptom dimensions in recent-onset schizophrenia and mania: a principal components analysis of the 24-item Brief Psychiatric Rating Scale , 2000, Psychiatry Research.

[77]  I. Olkin,et al.  Meta-analysis of observational studies in epidemiology - A proposal for reporting , 2000 .

[78]  David Moher,et al.  Meta-analysis of Observational Studies in Epidemiology , 2000 .

[79]  R. C. Hall,et al.  Global assessment of functioning. A modified scale. , 1995, Psychosomatics.

[80]  H. Goldman,et al.  Revising axis V for DSM-IV: a review of measures of social functioning. , 1992, The American journal of psychiatry.

[81]  N. Andreasen.  The Scale for the Assessment of Negative Symptoms (SANS): Conceptual and Theoretical Foundations , 1989, British Journal of Psychiatry.

[82]  R. Sugden.  Multiple Imputation for Nonresponse in Surveys , 1988 .

[83]  S. Kay,et al.  The positive and negative syndrome scale (PANSS) for schizophrenia. , 1987, Schizophrenia bulletin.

[84]  W T Carpenter,et al.  The Quality of Life Scale: an instrument for rating the schizophrenic deficit syndrome. , 1984, Schizophrenia bulletin.

[85]  James Robert Brašić,et al.  A children's global assessment scale (CGAS). , 1983, Archives of general psychiatry.

[86]  W. W. Muir,et al.  Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1980 .

[87]  L. Luborsky.  Clinician's judgments of mental health. , 1962, Archives of general psychiatry.