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Classification of comorbidity in obsessive–compulsive disorder: A latent class analysis
OBJECTIVE: Patients with OCD differ markedly from one another in both number and kind of comorbid disorders. In this study, we set out to identify and characterize homogeneous subgroups of OCD patients based on their comorbidity profile. METHODS: In a cohort of 419 adult subjects with OCD, the lifet...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375063/ https://www.ncbi.nlm.nih.gov/pubmed/32403206 http://dx.doi.org/10.1002/brb3.1641 |
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author | van Oudheusden, Lucas J. B. van de Schoot, Rens Hoogendoorn, Adriaan van Oppen, Patricia Kaarsemaker, Maarten Meynen, Gerben van Balkom, Anton J. L. M. |
author_facet | van Oudheusden, Lucas J. B. van de Schoot, Rens Hoogendoorn, Adriaan van Oppen, Patricia Kaarsemaker, Maarten Meynen, Gerben van Balkom, Anton J. L. M. |
author_sort | van Oudheusden, Lucas J. B. |
collection | PubMed |
description | OBJECTIVE: Patients with OCD differ markedly from one another in both number and kind of comorbid disorders. In this study, we set out to identify and characterize homogeneous subgroups of OCD patients based on their comorbidity profile. METHODS: In a cohort of 419 adult subjects with OCD, the lifetime presence of fifteen comorbid disorders was assessed. Latent class analysis was used to identify comorbidity‐based subgroups. Groups were compared with regard to core clinical characteristics: familiality, childhood trauma, age at onset, illness severity, OCD symptom dimensions, personality characteristics, and course of illness. RESULTS: The study sample could be divided in a large group (n = 311) with a low amount of comorbidity that could be further subdivided into two subgroups: OCD simplex (n = 147) and OCD with lifetime major depressive disorder (n = 186), and a group (n = 108) with a high amount of comorbidity that could be further subdivided into a general anxiety‐related subgroup (n = 49), an autism/social phobia‐related subgroup (n = 27), and a psychosis/bipolar‐related subgroup (n = 10). Membership of the high‐comorbid subgroup was associated with higher scores on childhood trauma, illness severity, and the aggression/checking symptom dimension and lower scores on several personality characteristics. CONCLUSION: Grouping OCD patients based on their comorbidity profile might provide more homogeneous, and therefore, more suitable categories for future studies aimed at unraveling the etiological mechanisms underlying this debilitating disorder. |
format | Online Article Text |
id | pubmed-7375063 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73750632020-07-22 Classification of comorbidity in obsessive–compulsive disorder: A latent class analysis van Oudheusden, Lucas J. B. van de Schoot, Rens Hoogendoorn, Adriaan van Oppen, Patricia Kaarsemaker, Maarten Meynen, Gerben van Balkom, Anton J. L. M. Brain Behav Original Research OBJECTIVE: Patients with OCD differ markedly from one another in both number and kind of comorbid disorders. In this study, we set out to identify and characterize homogeneous subgroups of OCD patients based on their comorbidity profile. METHODS: In a cohort of 419 adult subjects with OCD, the lifetime presence of fifteen comorbid disorders was assessed. Latent class analysis was used to identify comorbidity‐based subgroups. Groups were compared with regard to core clinical characteristics: familiality, childhood trauma, age at onset, illness severity, OCD symptom dimensions, personality characteristics, and course of illness. RESULTS: The study sample could be divided in a large group (n = 311) with a low amount of comorbidity that could be further subdivided into two subgroups: OCD simplex (n = 147) and OCD with lifetime major depressive disorder (n = 186), and a group (n = 108) with a high amount of comorbidity that could be further subdivided into a general anxiety‐related subgroup (n = 49), an autism/social phobia‐related subgroup (n = 27), and a psychosis/bipolar‐related subgroup (n = 10). Membership of the high‐comorbid subgroup was associated with higher scores on childhood trauma, illness severity, and the aggression/checking symptom dimension and lower scores on several personality characteristics. CONCLUSION: Grouping OCD patients based on their comorbidity profile might provide more homogeneous, and therefore, more suitable categories for future studies aimed at unraveling the etiological mechanisms underlying this debilitating disorder. John Wiley and Sons Inc. 2020-05-13 /pmc/articles/PMC7375063/ /pubmed/32403206 http://dx.doi.org/10.1002/brb3.1641 Text en © 2020 The Authors. Brain and Behavior published by Wiley Periodicals LLC. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research van Oudheusden, Lucas J. B. van de Schoot, Rens Hoogendoorn, Adriaan van Oppen, Patricia Kaarsemaker, Maarten Meynen, Gerben van Balkom, Anton J. L. M. Classification of comorbidity in obsessive–compulsive disorder: A latent class analysis |
title | Classification of comorbidity in obsessive–compulsive disorder: A latent class analysis |
title_full | Classification of comorbidity in obsessive–compulsive disorder: A latent class analysis |
title_fullStr | Classification of comorbidity in obsessive–compulsive disorder: A latent class analysis |
title_full_unstemmed | Classification of comorbidity in obsessive–compulsive disorder: A latent class analysis |
title_short | Classification of comorbidity in obsessive–compulsive disorder: A latent class analysis |
title_sort | classification of comorbidity in obsessive–compulsive disorder: a latent class analysis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375063/ https://www.ncbi.nlm.nih.gov/pubmed/32403206 http://dx.doi.org/10.1002/brb3.1641 |
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