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Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis
Continued cannabis use (CCu) is an important predictor for poor long-term outcomes in psychosis and clinically high-risk patients, but no generalizable model has hitherto been tested for its ability to predict CCu in these vulnerable patient groups. In the current study, we investigated how structur...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907166/ https://www.ncbi.nlm.nih.gov/pubmed/35264631 http://dx.doi.org/10.1038/s41537-022-00218-y |
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author | Penzel, Nora Sanfelici, Rachele Antonucci, Linda A. Betz, Linda T. Dwyer, Dominic Ruef, Anne Cho, Kang Ik K. Cumming, Paul Pogarell, Oliver Howes, Oliver Falkai, Peter Upthegrove, Rachel Borgwardt, Stefan Brambilla, Paolo Lencer, Rebekka Meisenzahl, Eva Schultze-Lutter, Frauke Rosen, Marlene Lichtenstein, Theresa Kambeitz-Ilankovic, Lana Ruhrmann, Stephan Salokangas, Raimo K. R. Pantelis, Christos Wood, Stephen J. Quednow, Boris B. Pergola, Giulio Bertolino, Alessandro Koutsouleris, Nikolaos Kambeitz, Joseph |
author_facet | Penzel, Nora Sanfelici, Rachele Antonucci, Linda A. Betz, Linda T. Dwyer, Dominic Ruef, Anne Cho, Kang Ik K. Cumming, Paul Pogarell, Oliver Howes, Oliver Falkai, Peter Upthegrove, Rachel Borgwardt, Stefan Brambilla, Paolo Lencer, Rebekka Meisenzahl, Eva Schultze-Lutter, Frauke Rosen, Marlene Lichtenstein, Theresa Kambeitz-Ilankovic, Lana Ruhrmann, Stephan Salokangas, Raimo K. R. Pantelis, Christos Wood, Stephen J. Quednow, Boris B. Pergola, Giulio Bertolino, Alessandro Koutsouleris, Nikolaos Kambeitz, Joseph |
author_sort | Penzel, Nora |
collection | PubMed |
description | Continued cannabis use (CCu) is an important predictor for poor long-term outcomes in psychosis and clinically high-risk patients, but no generalizable model has hitherto been tested for its ability to predict CCu in these vulnerable patient groups. In the current study, we investigated how structured clinical and cognitive assessments and structural magnetic resonance imaging (sMRI) contributed to the prediction of CCu in a group of 109 patients with recent-onset psychosis (ROP). We tested the generalizability of our predictors in 73 patients at clinical high-risk for psychosis (CHR). Here, CCu was defined as any cannabis consumption between baseline and 9-month follow-up, as assessed in structured interviews. All patients reported lifetime cannabis use at baseline. Data from clinical assessment alone correctly classified 73% (p < 0.001) of ROP and 59 % of CHR patients. The classifications of CCu based on sMRI and cognition were non-significant (ps > 0.093), and their addition to the interview-based predictor via stacking did not improve prediction significantly, either in the ROP or CHR groups (ps > 0.065). Lower functioning, specific substance use patterns, urbanicity and a lack of other coping strategies contributed reliably to the prediction of CCu and might thus represent important factors for guiding preventative efforts. Our results suggest that it may be possible to identify by clinical measures those psychosis-spectrum patients at high risk for CCu, potentially allowing to improve clinical care through targeted interventions. However, our model needs further testing in larger samples including more diverse clinical populations before being transferred into clinical practice. |
format | Online Article Text |
id | pubmed-8907166 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89071662022-03-23 Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis Penzel, Nora Sanfelici, Rachele Antonucci, Linda A. Betz, Linda T. Dwyer, Dominic Ruef, Anne Cho, Kang Ik K. Cumming, Paul Pogarell, Oliver Howes, Oliver Falkai, Peter Upthegrove, Rachel Borgwardt, Stefan Brambilla, Paolo Lencer, Rebekka Meisenzahl, Eva Schultze-Lutter, Frauke Rosen, Marlene Lichtenstein, Theresa Kambeitz-Ilankovic, Lana Ruhrmann, Stephan Salokangas, Raimo K. R. Pantelis, Christos Wood, Stephen J. Quednow, Boris B. Pergola, Giulio Bertolino, Alessandro Koutsouleris, Nikolaos Kambeitz, Joseph Schizophrenia (Heidelb) Article Continued cannabis use (CCu) is an important predictor for poor long-term outcomes in psychosis and clinically high-risk patients, but no generalizable model has hitherto been tested for its ability to predict CCu in these vulnerable patient groups. In the current study, we investigated how structured clinical and cognitive assessments and structural magnetic resonance imaging (sMRI) contributed to the prediction of CCu in a group of 109 patients with recent-onset psychosis (ROP). We tested the generalizability of our predictors in 73 patients at clinical high-risk for psychosis (CHR). Here, CCu was defined as any cannabis consumption between baseline and 9-month follow-up, as assessed in structured interviews. All patients reported lifetime cannabis use at baseline. Data from clinical assessment alone correctly classified 73% (p < 0.001) of ROP and 59 % of CHR patients. The classifications of CCu based on sMRI and cognition were non-significant (ps > 0.093), and their addition to the interview-based predictor via stacking did not improve prediction significantly, either in the ROP or CHR groups (ps > 0.065). Lower functioning, specific substance use patterns, urbanicity and a lack of other coping strategies contributed reliably to the prediction of CCu and might thus represent important factors for guiding preventative efforts. Our results suggest that it may be possible to identify by clinical measures those psychosis-spectrum patients at high risk for CCu, potentially allowing to improve clinical care through targeted interventions. However, our model needs further testing in larger samples including more diverse clinical populations before being transferred into clinical practice. Nature Publishing Group UK 2022-03-09 /pmc/articles/PMC8907166/ /pubmed/35264631 http://dx.doi.org/10.1038/s41537-022-00218-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Penzel, Nora Sanfelici, Rachele Antonucci, Linda A. Betz, Linda T. Dwyer, Dominic Ruef, Anne Cho, Kang Ik K. Cumming, Paul Pogarell, Oliver Howes, Oliver Falkai, Peter Upthegrove, Rachel Borgwardt, Stefan Brambilla, Paolo Lencer, Rebekka Meisenzahl, Eva Schultze-Lutter, Frauke Rosen, Marlene Lichtenstein, Theresa Kambeitz-Ilankovic, Lana Ruhrmann, Stephan Salokangas, Raimo K. R. Pantelis, Christos Wood, Stephen J. Quednow, Boris B. Pergola, Giulio Bertolino, Alessandro Koutsouleris, Nikolaos Kambeitz, Joseph Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis |
title | Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis |
title_full | Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis |
title_fullStr | Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis |
title_full_unstemmed | Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis |
title_short | Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis |
title_sort | pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907166/ https://www.ncbi.nlm.nih.gov/pubmed/35264631 http://dx.doi.org/10.1038/s41537-022-00218-y |
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