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 Wood & 14 others Ashleigh 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

Research output: Contribution to journalArticle

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
Pages (from-to)345
JournalFrontiers in Psychiatry
Volume10
DOIs
Publication statusPublished - 2019

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Psychotic Disorders
Meta-Analysis
Preventive Psychiatry
Aptitude
PubMed
Sample Size
Confidence Intervals

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

In: Frontiers in Psychiatry, Vol. 10, 2019, p. 345.

Research output: Contribution to journalArticle

Malda, A, Boonstra, N, Barf, H, de Jong, S, Aleman, A, Addington, J, Pruessner, M, Nieman, D, de Haan, L, Morrison, A, Riecher-Rössler, A, Studerus, E, Ruhrmann, S, Schultze-Lutter, F, An, SK, Koike, S, Kasai, K, Nelson, B, McGorry, P, Wood, S, Lin, A, Yung, AY, Kotlicka-Antczak, M, Armando, M, Vicari, S, Katsura, M, Matsumoto, K, Durston, S, Ziermans, T, Wunderink, L, Ising, H, van der Gaag, M, Fusar-Poli, P & Pijnenborg, GHM 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, vol. 10, pp. 345. https://doi.org/10.3389/fpsyt.2019.00345
Malda, Aaltsje ; Boonstra, Nynke ; Barf, Hans ; de Jong, Steven ; Aleman, Andre ; Addington, Jean ; Pruessner, Marita ; Nieman, Dorien ; de Haan, Lieuwe ; Morrison, Anthony ; Riecher-Rössler, Anita ; Studerus, Erich ; Ruhrmann, Stephan ; Schultze-Lutter, Frauke ; An, Suk Kyoon ; Koike, Shinsuke ; Kasai, Kiyoto ; Nelson, Barnaby ; McGorry, Patrick ; Wood, Stephen ; Lin, Ashleigh ; Yung, Alison Y ; Kotlicka-Antczak, Magdalena ; Armando, Marco ; Vicari, Stefano ; Katsura, Masahiro ; Matsumoto, Kazunori ; Durston, Sarah ; Ziermans, Tim ; Wunderink, Lex ; Ising, Helga ; van der Gaag, Mark ; Fusar-Poli, Paolo ; Pijnenborg, Gerdina Hendrika Maria. / 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. In: Frontiers in Psychiatry. 2019 ; Vol. 10. pp. 345.
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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.",
author = "Aaltsje Malda and Nynke Boonstra and Hans Barf and {de Jong}, Steven and Andre Aleman and Jean Addington and Marita Pruessner and Dorien Nieman and {de Haan}, Lieuwe and Anthony Morrison and Anita Riecher-R{\"o}ssler and Erich Studerus and Stephan Ruhrmann and Frauke Schultze-Lutter and An, {Suk Kyoon} and Shinsuke Koike and Kiyoto Kasai and Barnaby Nelson and Patrick McGorry and Stephen Wood and Ashleigh Lin and Yung, {Alison Y} and Magdalena Kotlicka-Antczak and Marco Armando and Stefano Vicari and Masahiro Katsura and Kazunori Matsumoto and Sarah Durston and Tim Ziermans and Lex Wunderink and Helga Ising and {van der Gaag}, Mark and Paolo Fusar-Poli and Pijnenborg, {Gerdina Hendrika Maria}",
year = "2019",
doi = "10.3389/fpsyt.2019.00345",
language = "English",
volume = "10",
pages = "345",
journal = "Frontiers in Psychiatry",
issn = "1664-0640",
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TY - JOUR

T1 - Individualized Prediction of Transition to Psychosis in 1,676 Individuals at Clinical High Risk

T2 - Development and Validation of a Multivariable Prediction Model Based on Individual Patient Data Meta-Analysis

AU - Malda, Aaltsje

AU - Boonstra, Nynke

AU - Barf, Hans

AU - de Jong, Steven

AU - Aleman, Andre

AU - Addington, Jean

AU - Pruessner, Marita

AU - Nieman, Dorien

AU - de Haan, Lieuwe

AU - Morrison, Anthony

AU - Riecher-Rössler, Anita

AU - Studerus, Erich

AU - Ruhrmann, Stephan

AU - Schultze-Lutter, Frauke

AU - An, Suk Kyoon

AU - Koike, Shinsuke

AU - Kasai, Kiyoto

AU - Nelson, Barnaby

AU - McGorry, Patrick

AU - Wood, Stephen

AU - Lin, Ashleigh

AU - Yung, Alison Y

AU - Kotlicka-Antczak, Magdalena

AU - Armando, Marco

AU - Vicari, Stefano

AU - Katsura, Masahiro

AU - Matsumoto, Kazunori

AU - Durston, Sarah

AU - Ziermans, Tim

AU - Wunderink, Lex

AU - Ising, Helga

AU - van der Gaag, Mark

AU - Fusar-Poli, Paolo

AU - Pijnenborg, Gerdina Hendrika Maria

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

U2 - 10.3389/fpsyt.2019.00345

DO - 10.3389/fpsyt.2019.00345

M3 - Article

VL - 10

SP - 345

JO - Frontiers in Psychiatry

JF - Frontiers in Psychiatry

SN - 1664-0640

ER -