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 language | English |
|---|---|
| Article number | 345 |
| Pages (from-to) | 1-17 |
| Number of pages | 17 |
| Journal | Frontiers in Psychiatry |
| Volume | 10 |
| Issue number | MAY |
| DOIs | |
| Publication status | Published - 21 May 2019 |
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Keywords
- Clinical high risk
- Individual patient data meta-analysis
- Prognosis
- Psychosis
- Risk prediction
- Schizophrenia
Cite this
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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; Maria Pijnenborg, Gerdina Hendrika.
In: Frontiers in Psychiatry, Vol. 10, No. MAY, 345, 21.05.2019, p. 1-17.Research output: Contribution to Journal › Article › Academic › peer-review
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 - Maria Pijnenborg, Gerdina Hendrika
PY - 2019/5/21
Y1 - 2019/5/21
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.
KW - Clinical high risk
KW - Individual patient data meta-analysis
KW - Prognosis
KW - Psychosis
KW - Risk prediction
KW - Schizophrenia
UR - http://www.scopus.com/inward/record.url?scp=85068143623&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068143623&partnerID=8YFLogxK
U2 - 10.3389/fpsyt.2019.00345
DO - 10.3389/fpsyt.2019.00345
M3 - Article
VL - 10
SP - 1
EP - 17
JO - Frontiers in Psychiatry
JF - Frontiers in Psychiatry
SN - 1664-0640
IS - MAY
M1 - 345
ER -