Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis
Abstract 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...
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-03-01
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| Series: | npj Schizophrenia |
| Online Access: | https://doi.org/10.1038/s41537-022-00218-y |
| _version_ | 1797423624009809920 |
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| author | Nora Penzel Rachele Sanfelici Linda A. Antonucci Linda T. Betz Dominic Dwyer Anne Ruef Kang Ik K. Cho Paul Cumming Oliver Pogarell Oliver Howes Peter Falkai Rachel Upthegrove Stefan Borgwardt Paolo Brambilla Rebekka Lencer Eva Meisenzahl Frauke Schultze-Lutter Marlene Rosen Theresa Lichtenstein Lana Kambeitz-Ilankovic Stephan Ruhrmann Raimo K. R. Salokangas Christos Pantelis Stephen J. Wood Boris B. Quednow Giulio Pergola Alessandro Bertolino Nikolaos Koutsouleris Joseph Kambeitz the PRONIA Consortium |
| author_facet | Nora Penzel Rachele Sanfelici Linda A. Antonucci Linda T. Betz Dominic Dwyer Anne Ruef Kang Ik K. Cho Paul Cumming Oliver Pogarell Oliver Howes Peter Falkai Rachel Upthegrove Stefan Borgwardt Paolo Brambilla Rebekka Lencer Eva Meisenzahl Frauke Schultze-Lutter Marlene Rosen Theresa Lichtenstein Lana Kambeitz-Ilankovic Stephan Ruhrmann Raimo K. R. Salokangas Christos Pantelis Stephen J. Wood Boris B. Quednow Giulio Pergola Alessandro Bertolino Nikolaos Koutsouleris Joseph Kambeitz the PRONIA Consortium |
| author_sort | Nora Penzel |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-09T07:49:36Z |
| format | Article |
| id | doaj.art-5423228607174dbd91d07c33026cc7b3 |
| institution | Directory Open Access Journal |
| issn | 2334-265X |
| language | English |
| last_indexed | 2024-03-09T07:49:36Z |
| publishDate | 2022-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Schizophrenia |
| spelling | doaj.art-5423228607174dbd91d07c33026cc7b32023-12-03T02:03:17ZengNature Portfolionpj Schizophrenia2334-265X2022-03-018111110.1038/s41537-022-00218-yPattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosisNora Penzel0Rachele Sanfelici1Linda A. Antonucci2Linda T. Betz3Dominic Dwyer4Anne Ruef5Kang Ik K. Cho6Paul Cumming7Oliver Pogarell8Oliver Howes9Peter Falkai10Rachel Upthegrove11Stefan Borgwardt12Paolo Brambilla13Rebekka Lencer14Eva Meisenzahl15Frauke Schultze-Lutter16Marlene Rosen17Theresa Lichtenstein18Lana Kambeitz-Ilankovic19Stephan Ruhrmann20Raimo K. R. Salokangas21Christos Pantelis22Stephen J. Wood23Boris B. Quednow24Giulio Pergola25Alessandro Bertolino26Nikolaos Koutsouleris27Joseph Kambeitz28the PRONIA ConsortiumUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and PsychotherapyDepartment of Psychiatry and Psychotherapy, Ludwig-Maximilian-UniversityDepartment of Psychiatry and Psychotherapy, Ludwig-Maximilian-UniversityUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and PsychotherapyDepartment of Psychiatry and Psychotherapy, Ludwig-Maximilian-UniversityDepartment of Psychiatry and Psychotherapy, Ludwig-Maximilian-UniversityDepartment of Psychiatry, Brigham and Women’s Hospital, Harvard Medical SchoolDepartment of Nuclear Medicine, Bern University HospitalDepartment of Psychiatry and Psychotherapy, Ludwig-Maximilian-UniversityDepartment of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College LondonDepartment of Psychiatry and Psychotherapy, Ludwig-Maximilian-UniversityInstitute for Mental Health, University of BirminghamDepartment of Psychiatry (UPK), University of BaselDepartment of Neurosciences and Mental Health, Fondazione IRCCUS Ca’ Granda Ospedale Maggiore Policlinico, University of MilanDepartment of Psychiatry and Psychotherapy, University of LübeckDepartment of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine UniversityDepartment of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine UniversityUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and PsychotherapyUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and PsychotherapyUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and PsychotherapyUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and PsychotherapyDepartment of Psychiatry, University of TurkuMelbourne Neuropsychiatry Centre, University of Melbourne & Melbourne HealthInstitute for Mental Health, University of BirminghamExperimental and Clinical Pharmacopsychology, Department of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric Hospital of the University of ZurichGroup of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-UniversityUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and PsychotherapyAbstract 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.https://doi.org/10.1038/s41537-022-00218-y |
| spellingShingle | Nora Penzel Rachele Sanfelici Linda A. Antonucci Linda T. Betz Dominic Dwyer Anne Ruef Kang Ik K. Cho Paul Cumming Oliver Pogarell Oliver Howes Peter Falkai Rachel Upthegrove Stefan Borgwardt Paolo Brambilla Rebekka Lencer Eva Meisenzahl Frauke Schultze-Lutter Marlene Rosen Theresa Lichtenstein Lana Kambeitz-Ilankovic Stephan Ruhrmann Raimo K. R. Salokangas Christos Pantelis Stephen J. Wood Boris B. Quednow Giulio Pergola Alessandro Bertolino Nikolaos Koutsouleris Joseph Kambeitz the PRONIA Consortium Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis npj Schizophrenia |
| 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 |
| url | https://doi.org/10.1038/s41537-022-00218-y |
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