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

Aaltsje Malda*, Nynke Boonstra, Hans Barf, Steven De Jong, Andre Aleman, Jean Addington, Marita Pruessner, Dorien Nieman, Lieuwe De Haan, Anthony Morrison, Anita Riecher-Rössler, Erich Studerus, Stephan Ruhrmann, Frauke Schultze-Lutter, Suk Kyoon An, Shinsuke Koike, Kiyoto Kasai, Barnaby Nelson, Patrick McGorry, Stephen WoodAshleigh Lin, Alison Y. Yung, Magdalena Kotlicka-Antczak, Marco Armando, Stefano Vicari, Masahiro Katsura, Kazunori Matsumoto, Sarah Durston, Tim Ziermans, Lex Wunderink, Helga Ising, Mark Van Der Gaag, Paolo Fusar-Poli, Gerdina Hendrika Maria Pijnenborg

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Background: The Clinical High Risk state for Psychosis (CHR-P) has become the cornerstone of modern preventive psychiatry. The next stage of clinical advancements rests on the ability to formulate a more accurate prognostic estimate at the individual subject level. Individual Participant Data Meta-Analyses (IPD-MA) are robust evidence synthesis methods that can also offer powerful approaches to the development and validation of personalized prognostic models. The aim of the study was to develop and validate an individualized, clinically based prognostic model for forecasting transition to psychosis from a CHR-P stage. Methods: A literature search was performed between January 30, 2016, and February 6, 2016, consulting PubMed, Psychinfo, Picarta, Embase, and ISI Web of Science, using search terms (“ultra high risk” OR “clinical high risk” OR “at risk mental state”) AND [(conver* OR transition* OR onset OR emerg* OR develop*) AND psychosis] for both longitudinal and intervention CHR-P studies. Clinical knowledge was used to a priori select predictors: age, gender, CHR-P subgroup, the severity of attenuated positive psychotic symptoms, the severity of attenuated negative psychotic symptoms, and level of functioning at baseline. The model, thus, developed was validated with an extended form of internal validation. Results: Fifteen of the 43 studies identified agreed to share IPD, for a total sample size of 1,676. There was a high level of heterogeneity between the CHR-P studies with regard to inclusion criteria, type of assessment instruments, transition criteria, preventive treatment offered. The internally validated prognostic performance of the model was higher than chance but only moderate [Harrell’s C-statistic 0.655, 95% confidence interval (CIs), 0.627–0.682]. Conclusion: This is the first IPD-MA conducted in the largest samples of CHR-P ever collected to date. An individualized prognostic model based on clinical predictors available in clinical routine was developed and internally validated, reaching only moderate prognostic performance. Although personalized risk prediction is of great value in the clinical practice, future developments are essential, including the refinement of the prognostic model and its external validation. However, because of the current high diagnostic, prognostic, and therapeutic heterogeneity of CHR-P studies, IPD-MAs in this population may have an limited intrinsic power to deliver robust prognostic models.

Original languageEnglish
Article number345
Pages (from-to)1-17
Number of pages17
JournalFrontiers in Psychiatry
Volume10
Issue numberMAY
DOIs
Publication statusPublished - 21 May 2019

Funding

Pavia, Pavia, Italy, 40 National Institute for Health Research, Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, United Kingdom, 41 Department of Psychotic Disorders, GGZ Drenthe Mental Health Care Center, Assen, Netherlands For the open access publication fees, there is funding received from the University of Groningen, NHL Stenden University of Applied Sciences, GGZ Friesland Mental Health Institute, and GGZ Drenthe Mental Health Institute, that will equally share the costs. ADAPT: JA received funding from NIMH and Alberta Heritage Foundation for Medical Research. CAYR: Research at CAYR was supported by a NARSAD Young Investigator Award to MP. DUPS: This project was supported by a research grant from The Netherlands Organization for Health Research and Development (ZonMw, 2630.0001). EDIE-NL: MG received funding from Netherlands Health Research Council, ZonMW (120510001). EDIE-UK: This research was supported by research grants from the North West National Health Service R&D Executive and the Stanley Medical Research Institute. FEPSY: This project was supported by the Swiss National Science Foundation no. 3200-057216.99, no. 3200-057216.99, and no. PBBSB-106936, the Nora van Meeuwen-Haefliger Stiftung, Basel (CH). FETZ: Data analyses were supported by a grant from the Koeln Fortune Program/ Faculty of Medicine, University of Cologne (projects 8/2005 and 27/2006); the Awareness Program was supported from 2000 to 2005 by a grant from the German Federal Ministry for Education and Research, BMBF (grant 01 GI 0235). GRAPE: This work was supported by a grant of the Korea Healthcare Technology R&D Project, Ministry for Health, Welfare and Family Affairs, Republic of Korea (A090096) and by a National Research Foundation of Korea (NRF) grant funded by the Ministry of Science, ICT & Future Planning, Republic of Korea (No. 2010-0026833, No. 2017R1A2B3008214). INSTEP: This study was supported in part by JSPS KAKENHI Grant Number JP16H06395, 16H0639X, 16K21720 & 17H05921, AMED under Grant Number JP18dm0307001 & JP18dm0307004, UTokyo Center for Integrative Science of Human Behavior (CiSHuB), and the International Research Center for Neurointelligence (WPIIRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS). OASIS: PF-P was supported by the King’s College London Confidence in Concept award from the Medical Research Council (MRC) (MC_PC_16048). This study also represents independent research partially funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. PACE: funding support of National Health and Medical Research Council (NHMRC) Program grants 350241 and 566529 and the Colonial Foundation. BN was supported by an NHMRC Senior Research Fellowship (1137687), SW was supported by an NHMRC Clinical Career Developmental Award (359223), and AY was supported by an NHMRC Senior Research Fellowship (566593). PORT: Research activities regarding ARMS individuals included in the PORT program are financed by the Polish Science National Centre, grant no. NN402 1793 34. ROME: MA was supported by the Brain and Behavior Research Foundation (21278) (formerly NARSAD). SAFE: the Ministry of Education, Culture, Sports, Science and Technology (MEXT) Grants-in-Aid for Scientific Research (KAKENHI) Grant Numbers 17790803, 19591336, 22390219, and 25461747, Japan. DUPS-U: None. The funders had no influence on the design, collection, analysis, and interpretation of the data, writing of the report, and decision to submit this article for publication.

FundersFunder number
Faculty of Medicine, University of Cologne27/2006, 8/2005
International Research Center for Neurointelligence
Koeln Fortune Program
Netherlands Health Research Council120510001
Nora van Meeuwen-Haefliger Stiftung
North West National Health Service R&D Executive
Polish Science National CentreNN402 1793 34
University of Tokyo Institutes for Advanced Study
WPIIRCN
National Institute of Mental Health
Brain and Behavior Research Foundation21278
Stanley Medical Research Institute
King’s College London
South London and Maudsley NHS Foundation Trust
Japan Agency for Medical Research and DevelopmentJP18dm0307001 & JP18dm0307004
National Alliance for Research on Schizophrenia and Depression
Medical Research CouncilMC_PC_16048
National Institute for Health and Care Research
National Health and Medical Research Council566529, 350241
Japan Society for the Promotion of Science17H05921, 16H0639X, 16K21720, JP16H06395
Ministry of Education, Culture, Sports, Science and Technology22390219, 19591336, 17790803, 25461747
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungPBBSB-106936, 3200-057216.99
ZonMw2630.0001
Bundesministerium für Bildung und Forschung01 GI 0235
Alberta Heritage Foundation for Medical Research
Ministry of Science, ICT and Future Planning2017R1A2B3008214, 2010-0026833
Ministry of Health and WelfareA090096
National Research Foundation of Korea
Colonial Foundation359223, 1137687, 566593

    Keywords

    • Clinical high risk
    • Individual patient data meta-analysis
    • Prognosis
    • Psychosis
    • Risk prediction
    • Schizophrenia

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