Investigating the association between anxiety symptoms and mood disorder in high-risk offspring of bipolar parents: a comparison of Joint and Cox models
Abstract Background Anxiety is associated with mood disorders including bipolar disorder. Two statistical modelling frameworks were compared to investigate the longitudinal relationship between repeatedly measured anxiety symptoms and the onset of depression and bipolar disorder in youth at confirme...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2019-10-01
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| Series: | International Journal of Bipolar Disorders |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s40345-019-0157-9 |
| _version_ | 1818455110969196544 |
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| author | Ruoxi Dong George Stefan Julie Horrocks Sarah M. Goodday Anne Duffy |
| author_facet | Ruoxi Dong George Stefan Julie Horrocks Sarah M. Goodday Anne Duffy |
| author_sort | Ruoxi Dong |
| collection | DOAJ |
| description | Abstract Background Anxiety is associated with mood disorders including bipolar disorder. Two statistical modelling frameworks were compared to investigate the longitudinal relationship between repeatedly measured anxiety symptoms and the onset of depression and bipolar disorder in youth at confirmed familial risk. Methods Prospectively collected data on 156 offspring of a parent with confirmed bipolar disorder participating in the Canadian Flourish high-risk offspring longitudinal cohort study were used for this analysis. As part of the research protocol at approximately yearly visits, a research psychiatrist completed the HAM-A and a semi-structured diagnostic research interview following KSADS-PL format. Diagnoses using DSM-IV criteria were made on blind consensus review of all available clinical information. We investigated two statistical approaches, Cox model and Joint model, to evaluate the relationship between repeated HAM-A scores and the onset of major depressive or bipolar disorder. The Joint model estimates the trajectory of the longitudinal variable using a longitudinal sub-model and incorporates this estimated trajectory into a Cox sub-model. Results There was evidence of an increased hazard of major mood disorder for high-risk individuals with higher HAM-A scores under both modelling frameworks. After adjusting for other covariates, a one-unit increase in log-transformed HAM-A score was associated with a hazard ratio of 1.74 (95% CI (1.12, 2.72)) in the Cox model compared to 2.91(95% CI (1.29, 6.52)) in the Joint model. In an exploratory analysis there was no evidence that family clustering substantially affected the conclusions. Conclusions Estimated effects from the conventional Cox model, which is often the model of choice, were dramatically lower in this dataset, compared to the Joint model. While the Cox model is often considered the approach of choice for analysis, research has shown that the Joint model may be more efficient and less biased. Our analysis based on a Joint model suggests that the magnitude of association between anxiety and mood disorder in individuals at familial risk of developing bipolar disorder may be stronger than previously reported. |
| first_indexed | 2024-12-14T22:05:34Z |
| format | Article |
| id | doaj.art-81931f5c71c04ceeac9429034630acae |
| institution | Directory Open Access Journal |
| issn | 2194-7511 |
| language | English |
| last_indexed | 2024-12-14T22:05:34Z |
| publishDate | 2019-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | International Journal of Bipolar Disorders |
| spelling | doaj.art-81931f5c71c04ceeac9429034630acae2022-12-21T22:45:53ZengSpringerOpenInternational Journal of Bipolar Disorders2194-75112019-10-01711810.1186/s40345-019-0157-9Investigating the association between anxiety symptoms and mood disorder in high-risk offspring of bipolar parents: a comparison of Joint and Cox modelsRuoxi Dong0George Stefan1Julie Horrocks2Sarah M. Goodday3Anne Duffy4Department of Mathematics and Statistics, University of GuelphDepartment of Mathematics and Statistics, University of GuelphDepartment of Mathematics and Statistics, University of GuelphDepartment of Psychiatry, University of OxfordDepartment of Psychiatry, Queen’s UniversityAbstract Background Anxiety is associated with mood disorders including bipolar disorder. Two statistical modelling frameworks were compared to investigate the longitudinal relationship between repeatedly measured anxiety symptoms and the onset of depression and bipolar disorder in youth at confirmed familial risk. Methods Prospectively collected data on 156 offspring of a parent with confirmed bipolar disorder participating in the Canadian Flourish high-risk offspring longitudinal cohort study were used for this analysis. As part of the research protocol at approximately yearly visits, a research psychiatrist completed the HAM-A and a semi-structured diagnostic research interview following KSADS-PL format. Diagnoses using DSM-IV criteria were made on blind consensus review of all available clinical information. We investigated two statistical approaches, Cox model and Joint model, to evaluate the relationship between repeated HAM-A scores and the onset of major depressive or bipolar disorder. The Joint model estimates the trajectory of the longitudinal variable using a longitudinal sub-model and incorporates this estimated trajectory into a Cox sub-model. Results There was evidence of an increased hazard of major mood disorder for high-risk individuals with higher HAM-A scores under both modelling frameworks. After adjusting for other covariates, a one-unit increase in log-transformed HAM-A score was associated with a hazard ratio of 1.74 (95% CI (1.12, 2.72)) in the Cox model compared to 2.91(95% CI (1.29, 6.52)) in the Joint model. In an exploratory analysis there was no evidence that family clustering substantially affected the conclusions. Conclusions Estimated effects from the conventional Cox model, which is often the model of choice, were dramatically lower in this dataset, compared to the Joint model. While the Cox model is often considered the approach of choice for analysis, research has shown that the Joint model may be more efficient and less biased. Our analysis based on a Joint model suggests that the magnitude of association between anxiety and mood disorder in individuals at familial risk of developing bipolar disorder may be stronger than previously reported.http://link.springer.com/article/10.1186/s40345-019-0157-9High-riskOffspringLongitudinalBipolar disorderDepressive disorderAnxiety |
| spellingShingle | Ruoxi Dong George Stefan Julie Horrocks Sarah M. Goodday Anne Duffy Investigating the association between anxiety symptoms and mood disorder in high-risk offspring of bipolar parents: a comparison of Joint and Cox models International Journal of Bipolar Disorders High-risk Offspring Longitudinal Bipolar disorder Depressive disorder Anxiety |
| title | Investigating the association between anxiety symptoms and mood disorder in high-risk offspring of bipolar parents: a comparison of Joint and Cox models |
| title_full | Investigating the association between anxiety symptoms and mood disorder in high-risk offspring of bipolar parents: a comparison of Joint and Cox models |
| title_fullStr | Investigating the association between anxiety symptoms and mood disorder in high-risk offspring of bipolar parents: a comparison of Joint and Cox models |
| title_full_unstemmed | Investigating the association between anxiety symptoms and mood disorder in high-risk offspring of bipolar parents: a comparison of Joint and Cox models |
| title_short | Investigating the association between anxiety symptoms and mood disorder in high-risk offspring of bipolar parents: a comparison of Joint and Cox models |
| title_sort | investigating the association between anxiety symptoms and mood disorder in high risk offspring of bipolar parents a comparison of joint and cox models |
| topic | High-risk Offspring Longitudinal Bipolar disorder Depressive disorder Anxiety |
| url | http://link.springer.com/article/10.1186/s40345-019-0157-9 |
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