Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra‐high risk for psychosis.
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| Title: | Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra‐high risk for psychosis. |
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| Authors: | Kristensen, Tina D. (AUTHOR), Glenthøj, Louise B. (AUTHOR), Ambrosen, Karen (AUTHOR), Syeda, Warda (AUTHOR), Ragahava, Jayachandra M. (AUTHOR), Krakauer, Kristine (AUTHOR), Wenneberg, Christina (AUTHOR), Fagerlund, Birgitte (AUTHOR), Pantelis, Christos (AUTHOR), Glenthøj, Birte Y. (AUTHOR), Nordentoft, Merete (AUTHOR), Ebdrup, Bjørn H. (AUTHOR) |
| Source: | Acta Psychiatrica Scandinavica. Nov2021, Vol. 144 Issue 5, p448-463. 16p. 3 Charts, 2 Graphs. |
| Subjects: | Prognosis, Sensitivity & specificity (Statistics), Psychoses, Diffusion magnetic resonance imaging, Socioeconomic status |
| Abstract: | Objective: Psychosis spectrum disorders are associated with cerebral changes, but the prognostic value and clinical utility of these findings are unclear. Here, we applied a multivariate statistical model to examine the predictive accuracy of global white matter fractional anisotropy (FA) for transition to psychosis in individuals at ultra‐high risk for psychosis (UHR). Methods: 110 UHR individuals underwent 3 Tesla diffusion‐weighted imaging and clinical assessments at baseline, and after 6 and 12 months. Using logistic regression, we examined the reliability of global FA at baseline as a predictor for psychosis transition after 12 months. We tested the predictive accuracy, sensitivity and specificity of global FA in a multivariate prediction model accounting for potential confounders to FA (head motion in scanner, age, gender, antipsychotic medication, parental socioeconomic status and activity level). In secondary analyses, we tested FA as a predictor of clinical symptoms and functional level using multivariate linear regression. Results: Ten UHR individuals had transitioned to psychosis after 12 months (9%). The model reliably predicted transition at 12 months (χ2 = 17.595, p = 0.040), accounted for 15–33% of the variance in transition outcome with a sensitivity of 0.70, a specificity of 0.88 and AUC of 0.87. Global FA predicted level of UHR symptoms (R2 = 0.055, F = 6.084, p = 0.016) and functional level (R2 = 0.040, F = 4.57, p = 0.036) at 6 months, but not at 12 months. Conclusion: Global FA provided prognostic information on clinical outcome and symptom course of UHR individuals. Our findings suggest that the application of prediction models including neuroimaging data can inform clinical management on risk for psychosis transition. [ABSTRACT FROM AUTHOR] |
| Copyright of Acta Psychiatrica Scandinavica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 153092542 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra‐high risk for psychosis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kristensen%2C+Tina+D%2E%22">Kristensen, Tina D.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Glenthøj%2C+Louise+B%2E%22">Glenthøj, Louise B.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ambrosen%2C+Karen%22">Ambrosen, Karen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Syeda%2C+Warda%22">Syeda, Warda</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ragahava%2C+Jayachandra+M%2E%22">Ragahava, Jayachandra M.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Krakauer%2C+Kristine%22">Krakauer, Kristine</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wenneberg%2C+Christina%22">Wenneberg, Christina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fagerlund%2C+Birgitte%22">Fagerlund, Birgitte</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pantelis%2C+Christos%22">Pantelis, Christos</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Glenthøj%2C+Birte+Y%2E%22">Glenthøj, Birte Y.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nordentoft%2C+Merete%22">Nordentoft, Merete</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ebdrup%2C+Bjørn+H%2E%22">Ebdrup, Bjørn H.</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Acta+Psychiatrica+Scandinavica%22">Acta Psychiatrica Scandinavica</searchLink>. Nov2021, Vol. 144 Issue 5, p448-463. 16p. 3 Charts, 2 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Prognosis%22">Prognosis</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+%26+specificity+%28Statistics%29%22">Sensitivity & specificity (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Psychoses%22">Psychoses</searchLink><br /><searchLink fieldCode="DE" term="%22Diffusion+magnetic+resonance+imaging%22">Diffusion magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+status%22">Socioeconomic status</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Objective: Psychosis spectrum disorders are associated with cerebral changes, but the prognostic value and clinical utility of these findings are unclear. Here, we applied a multivariate statistical model to examine the predictive accuracy of global white matter fractional anisotropy (FA) for transition to psychosis in individuals at ultra‐high risk for psychosis (UHR). Methods: 110 UHR individuals underwent 3 Tesla diffusion‐weighted imaging and clinical assessments at baseline, and after 6 and 12 months. Using logistic regression, we examined the reliability of global FA at baseline as a predictor for psychosis transition after 12 months. We tested the predictive accuracy, sensitivity and specificity of global FA in a multivariate prediction model accounting for potential confounders to FA (head motion in scanner, age, gender, antipsychotic medication, parental socioeconomic status and activity level). In secondary analyses, we tested FA as a predictor of clinical symptoms and functional level using multivariate linear regression. Results: Ten UHR individuals had transitioned to psychosis after 12 months (9%). The model reliably predicted transition at 12 months (χ2 = 17.595, p = 0.040), accounted for 15–33% of the variance in transition outcome with a sensitivity of 0.70, a specificity of 0.88 and AUC of 0.87. Global FA predicted level of UHR symptoms (R2 = 0.055, F = 6.084, p = 0.016) and functional level (R2 = 0.040, F = 4.57, p = 0.036) at 6 months, but not at 12 months. Conclusion: Global FA provided prognostic information on clinical outcome and symptom course of UHR individuals. Our findings suggest that the application of prediction models including neuroimaging data can inform clinical management on risk for psychosis transition. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Acta Psychiatrica Scandinavica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/acps.13355 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 448 Subjects: – SubjectFull: Prognosis Type: general – SubjectFull: Sensitivity & specificity (Statistics) Type: general – SubjectFull: Psychoses Type: general – SubjectFull: Diffusion magnetic resonance imaging Type: general – SubjectFull: Socioeconomic status Type: general Titles: – TitleFull: Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra‐high risk for psychosis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kristensen, Tina D. – PersonEntity: Name: NameFull: Glenthøj, Louise B. – PersonEntity: Name: NameFull: Ambrosen, Karen – PersonEntity: Name: NameFull: Syeda, Warda – PersonEntity: Name: NameFull: Ragahava, Jayachandra M. – PersonEntity: Name: NameFull: Krakauer, Kristine – PersonEntity: Name: NameFull: Wenneberg, Christina – PersonEntity: Name: NameFull: Fagerlund, Birgitte – PersonEntity: Name: NameFull: Pantelis, Christos – PersonEntity: Name: NameFull: Glenthøj, Birte Y. – PersonEntity: Name: NameFull: Nordentoft, Merete – PersonEntity: Name: NameFull: Ebdrup, Bjørn H. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 0001690X Numbering: – Type: volume Value: 144 – Type: issue Value: 5 Titles: – TitleFull: Acta Psychiatrica Scandinavica Type: main |
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