Testing a clinical staging model for bipolar disorder using longitudinal life chart data
Objective Bipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical staging model for bipolar disorder and to gain insight into the nature of the variables influencing progression through consecutive s...
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Published in | Bipolar disorders Vol. 21; no. 3; pp. 228 - 234 |
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Main Authors | , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Denmark
Wiley Subscription Services, Inc
01.05.2019
John Wiley and Sons Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1398-5647 1399-5618 1399-5618 |
DOI | 10.1111/bdi.12727 |
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Abstract | Objective
Bipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical staging model for bipolar disorder and to gain insight into the nature of the variables influencing progression through consecutive stages.
Methods
Using retrospectively reported longitudinal life chart data of 99 subjects from the Stanley Foundation Bipolar Network Naturalistic Follow‐up Study, the occurrence, duration and timely sequence of stages 2‐4 were determined per month. A multi‐state model was used to calculate progression rates and identify determinants of illness progression. Stages 0, 1 and several other variables were added to the multi‐state model to determine their influence on the progression rates.
Results
Five years after onset of BD (stage 2), 72% reached stage 3 (recurrent episodes) and 21% had reached stage 4 (continuous episodes), of whom 8% recovered back to stage 3. The progression from stage 2 to 3 was increased by a biphasic onset for both the depression‐mania and the mania‐depression course and by male sex.
Conclusions
Staging is a useful model to determine illness progression in longitudinal life chart data. Variables influencing transition rates were successfully identified. |
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AbstractList | Objective
Bipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical staging model for bipolar disorder and to gain insight into the nature of the variables influencing progression through consecutive stages.
Methods
Using retrospectively reported longitudinal life chart data of 99 subjects from the Stanley Foundation Bipolar Network Naturalistic Follow‐up Study, the occurrence, duration and timely sequence of stages 2‐4 were determined per month. A multi‐state model was used to calculate progression rates and identify determinants of illness progression. Stages 0, 1 and several other variables were added to the multi‐state model to determine their influence on the progression rates.
Results
Five years after onset of BD (stage 2), 72% reached stage 3 (recurrent episodes) and 21% had reached stage 4 (continuous episodes), of whom 8% recovered back to stage 3. The progression from stage 2 to 3 was increased by a biphasic onset for both the depression‐mania and the mania‐depression course and by male sex.
Conclusions
Staging is a useful model to determine illness progression in longitudinal life chart data. Variables influencing transition rates were successfully identified. Bipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical staging model for bipolar disorder and to gain insight into the nature of the variables influencing progression through consecutive stages.OBJECTIVEBipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical staging model for bipolar disorder and to gain insight into the nature of the variables influencing progression through consecutive stages.Using retrospectively reported longitudinal life chart data of 99 subjects from the Stanley Foundation Bipolar Network Naturalistic Follow-up Study, the occurrence, duration and timely sequence of stages 2-4 were determined per month. A multi-state model was used to calculate progression rates and identify determinants of illness progression. Stages 0, 1 and several other variables were added to the multi-state model to determine their influence on the progression rates.METHODSUsing retrospectively reported longitudinal life chart data of 99 subjects from the Stanley Foundation Bipolar Network Naturalistic Follow-up Study, the occurrence, duration and timely sequence of stages 2-4 were determined per month. A multi-state model was used to calculate progression rates and identify determinants of illness progression. Stages 0, 1 and several other variables were added to the multi-state model to determine their influence on the progression rates.Five years after onset of BD (stage 2), 72% reached stage 3 (recurrent episodes) and 21% had reached stage 4 (continuous episodes), of whom 8% recovered back to stage 3. The progression from stage 2 to 3 was increased by a biphasic onset for both the depression-mania and the mania-depression course and by male sex.RESULTSFive years after onset of BD (stage 2), 72% reached stage 3 (recurrent episodes) and 21% had reached stage 4 (continuous episodes), of whom 8% recovered back to stage 3. The progression from stage 2 to 3 was increased by a biphasic onset for both the depression-mania and the mania-depression course and by male sex.Staging is a useful model to determine illness progression in longitudinal life chart data. Variables influencing transition rates were successfully identified.CONCLUSIONSStaging is a useful model to determine illness progression in longitudinal life chart data. Variables influencing transition rates were successfully identified. ObjectiveBipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical staging model for bipolar disorder and to gain insight into the nature of the variables influencing progression through consecutive stages.MethodsUsing retrospectively reported longitudinal life chart data of 99 subjects from the Stanley Foundation Bipolar Network Naturalistic Follow‐up Study, the occurrence, duration and timely sequence of stages 2‐4 were determined per month. A multi‐state model was used to calculate progression rates and identify determinants of illness progression. Stages 0, 1 and several other variables were added to the multi‐state model to determine their influence on the progression rates.ResultsFive years after onset of BD (stage 2), 72% reached stage 3 (recurrent episodes) and 21% had reached stage 4 (continuous episodes), of whom 8% recovered back to stage 3. The progression from stage 2 to 3 was increased by a biphasic onset for both the depression‐mania and the mania‐depression course and by male sex.ConclusionsStaging is a useful model to determine illness progression in longitudinal life chart data. Variables influencing transition rates were successfully identified. Bipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical staging model for bipolar disorder and to gain insight into the nature of the variables influencing progression through consecutive stages. Using retrospectively reported longitudinal life chart data of 99 subjects from the Stanley Foundation Bipolar Network Naturalistic Follow-up Study, the occurrence, duration and timely sequence of stages 2-4 were determined per month. A multi-state model was used to calculate progression rates and identify determinants of illness progression. Stages 0, 1 and several other variables were added to the multi-state model to determine their influence on the progression rates. Five years after onset of BD (stage 2), 72% reached stage 3 (recurrent episodes) and 21% had reached stage 4 (continuous episodes), of whom 8% recovered back to stage 3. The progression from stage 2 to 3 was increased by a biphasic onset for both the depression-mania and the mania-depression course and by male sex. Staging is a useful model to determine illness progression in longitudinal life chart data. Variables influencing transition rates were successfully identified. |
Author | Klumpers, Ursula MH Draisma, Stasja Dols, Annemiek Post, Robert M McElroy, Susan L Kupka, Ralph W Keck, Paul E Markt, Afra Beekman, Aartjan TF Altshuler, Lori L Nolen, Willem A Frye, Mark A Suppes, Trisha Grunze, Heinz |
AuthorAffiliation | 3 Department of Psychiatry University Medical Center University of Groningen Groningen The Netherlands 5 Department of Psychiatry and Behavioral Sciences George Washington University Washington District of Columbia 11 Lindner Center of HOPE Mason Ohio 4 Bipolar Collaborative Network Bethesda Maryland 9 Klinikum am Weissenhof Weinsberg Germany & Paracelsus Medical University Nuremberg Germany 6 Department of Psychiatry and Biobehavioral Sciences David Geffen School of Medicine University of California Los Angeles California 14 V.A. Palo Alto Health Care System Palo Alto California 2 Department of Psychiatry Amsterdam Neuroscience Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam The Netherlands 13 Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Palo Alto California 12 Biological Psychiatry Program University of Cincinnati Medical College Cincinnati Ohio 7 Department of Psychiatry VA Greater Los Angeles Healthcare System West Los Angeles Healthcare Center |
AuthorAffiliation_xml | – name: 1 Department of Psychiatry Amsterdam Public Health Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam The Netherlands – name: 13 Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Palo Alto California – name: 6 Department of Psychiatry and Biobehavioral Sciences David Geffen School of Medicine University of California Los Angeles California – name: 11 Lindner Center of HOPE Mason Ohio – name: 14 V.A. Palo Alto Health Care System Palo Alto California – name: 8 Department of Psychiatry Mayo Clinic Rochester Minnesota – name: 12 Biological Psychiatry Program University of Cincinnati Medical College Cincinnati Ohio – name: 5 Department of Psychiatry and Behavioral Sciences George Washington University Washington District of Columbia – name: 9 Klinikum am Weissenhof Weinsberg Germany & Paracelsus Medical University Nuremberg Germany – name: 2 Department of Psychiatry Amsterdam Neuroscience Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam The Netherlands – name: 4 Bipolar Collaborative Network Bethesda Maryland – name: 3 Department of Psychiatry University Medical Center University of Groningen Groningen The Netherlands – name: 10 University of Cincinnati College of Medicine Cincinnati Ohio – name: 7 Department of Psychiatry VA Greater Los Angeles Healthcare System West Los Angeles Healthcare Center Los Angeles California |
Author_xml | – sequence: 1 givenname: Afra orcidid: 0000-0002-4022-9438 surname: Markt fullname: Markt, Afra email: a.vandermarkt@ggzingeest.nl organization: Vrije Universiteit Amsterdam – sequence: 2 givenname: Ursula MH surname: Klumpers fullname: Klumpers, Ursula MH organization: Vrije Universiteit Amsterdam – sequence: 3 givenname: Stasja surname: Draisma fullname: Draisma, Stasja organization: Vrije Universiteit Amsterdam – sequence: 4 givenname: Annemiek orcidid: 0000-0003-1964-0318 surname: Dols fullname: Dols, Annemiek organization: Vrije Universiteit Amsterdam – sequence: 5 givenname: Willem A surname: Nolen fullname: Nolen, Willem A organization: University of Groningen – sequence: 6 givenname: Robert M orcidid: 0000-0002-4246-524X surname: Post fullname: Post, Robert M organization: George Washington University – sequence: 7 givenname: Lori L surname: Altshuler fullname: Altshuler, Lori L organization: West Los Angeles Healthcare Center – sequence: 8 givenname: Mark A surname: Frye fullname: Frye, Mark A organization: Mayo Clinic – sequence: 9 givenname: Heinz orcidid: 0000-0003-4712-8979 surname: Grunze fullname: Grunze, Heinz organization: Weinsberg Germany & Paracelsus Medical University – sequence: 10 givenname: Paul E surname: Keck fullname: Keck, Paul E organization: Lindner Center of HOPE – sequence: 11 givenname: Susan L surname: McElroy fullname: McElroy, Susan L organization: University of Cincinnati Medical College – sequence: 12 givenname: Trisha surname: Suppes fullname: Suppes, Trisha organization: V.A. Palo Alto Health Care System – sequence: 13 givenname: Aartjan TF surname: Beekman fullname: Beekman, Aartjan TF organization: Vrije Universiteit Amsterdam – sequence: 14 givenname: Ralph W surname: Kupka fullname: Kupka, Ralph W organization: Vrije Universiteit Amsterdam |
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Bipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a... Bipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a clinical... ObjectiveBipolar disorder has a wide range of clinical manifestations which may progress over time. The aim of this study was to test the applicability of a... |
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SubjectTerms | Adult Affective disorders biphasic onset Bipolar disorder Bipolar Disorder - epidemiology Disease Progression Female Follow-Up Studies Humans Male male sex mood disorders multi‐state model Original Retrospective Studies staging staging models Young Adult |
Title | Testing a clinical staging model for bipolar disorder using longitudinal life chart data |
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