Cargando…
Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort
OBJECTIVES: Poor health-related quality of life (HRQoL) is well recognized in patients with CTD. We hypothesized that subgroups of patients across the spectrum of CTD experience different HRQoL patterns and aimed to determine patient-level characteristics associated with these different subgroups. M...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393437/ https://www.ncbi.nlm.nih.gov/pubmed/36534822 http://dx.doi.org/10.1093/rheumatology/keac680 |
_version_ | 1785083157313224704 |
---|---|
author | Dyball, Sarah Reynolds, John A Herrick, Ariane L Haque, Sahena Chinoy, Hector Bruce, Ellen Naz, Sophia Parker, Ben Bruce, Ian N |
author_facet | Dyball, Sarah Reynolds, John A Herrick, Ariane L Haque, Sahena Chinoy, Hector Bruce, Ellen Naz, Sophia Parker, Ben Bruce, Ian N |
author_sort | Dyball, Sarah |
collection | PubMed |
description | OBJECTIVES: Poor health-related quality of life (HRQoL) is well recognized in patients with CTD. We hypothesized that subgroups of patients across the spectrum of CTD experience different HRQoL patterns and aimed to determine patient-level characteristics associated with these different subgroups. METHODS: Using the eight continuous domains of the Medical Outcomes Study 36-item Short Form (SF-36) questionnaire we performed data-driven clustering to derive latent profiles (LPs) of patients with distinct HRQoL patterns. Multivariable ordinal logistic regression was used to determine patient-level characteristics associated with each HRQoL subgroup identified. RESULTS: A total of 309 CTD patients completed the SF-36 questionnaire. The most impaired SF-36 domains in each disease group were vitality, general health and bodily pain. The physical component of the SF-36 was consistently more impaired compared with the mental component, with similar scores across disease groups. Three LPs were identified with poor [n = 89 (29%)], average [n = 190 (61.4%)] and excellent [n = 30 (9.7%)] HRQoL. LPs were not associated with diagnostic grouping or autoantibody profiles. Black background [odds ratio (OR) 0.22 (95% CI 0.08, 0.63)], Indo-Asian background [OR 0.39 (95% CI 0.19, 0.78)], concomitant fibromyalgia [OR 0.40 (95% CI 0.20, 0.78)], sicca symptoms [OR 0.56 (95% CI 0.32, 0.98)] and multimorbidity [Charlson Comorbidity Index; OR 0.81 (95% CI 0.67, 0.97)] were associated with the ‘poor’ HRQoL LP. CONCLUSION: Distinct HRQoL subgroups exist that are not primarily driven by a specific diagnosis or autoantibody profiles. We identified a number of key demographic and clinical factors associated with poor HRQoL. These factors need to be addressed across the whole CTD spectrum as part of a holistic management approach aimed at improving overall patient outcomes. |
format | Online Article Text |
id | pubmed-10393437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103934372023-08-02 Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort Dyball, Sarah Reynolds, John A Herrick, Ariane L Haque, Sahena Chinoy, Hector Bruce, Ellen Naz, Sophia Parker, Ben Bruce, Ian N Rheumatology (Oxford) Clinical Science OBJECTIVES: Poor health-related quality of life (HRQoL) is well recognized in patients with CTD. We hypothesized that subgroups of patients across the spectrum of CTD experience different HRQoL patterns and aimed to determine patient-level characteristics associated with these different subgroups. METHODS: Using the eight continuous domains of the Medical Outcomes Study 36-item Short Form (SF-36) questionnaire we performed data-driven clustering to derive latent profiles (LPs) of patients with distinct HRQoL patterns. Multivariable ordinal logistic regression was used to determine patient-level characteristics associated with each HRQoL subgroup identified. RESULTS: A total of 309 CTD patients completed the SF-36 questionnaire. The most impaired SF-36 domains in each disease group were vitality, general health and bodily pain. The physical component of the SF-36 was consistently more impaired compared with the mental component, with similar scores across disease groups. Three LPs were identified with poor [n = 89 (29%)], average [n = 190 (61.4%)] and excellent [n = 30 (9.7%)] HRQoL. LPs were not associated with diagnostic grouping or autoantibody profiles. Black background [odds ratio (OR) 0.22 (95% CI 0.08, 0.63)], Indo-Asian background [OR 0.39 (95% CI 0.19, 0.78)], concomitant fibromyalgia [OR 0.40 (95% CI 0.20, 0.78)], sicca symptoms [OR 0.56 (95% CI 0.32, 0.98)] and multimorbidity [Charlson Comorbidity Index; OR 0.81 (95% CI 0.67, 0.97)] were associated with the ‘poor’ HRQoL LP. CONCLUSION: Distinct HRQoL subgroups exist that are not primarily driven by a specific diagnosis or autoantibody profiles. We identified a number of key demographic and clinical factors associated with poor HRQoL. These factors need to be addressed across the whole CTD spectrum as part of a holistic management approach aimed at improving overall patient outcomes. Oxford University Press 2022-12-19 /pmc/articles/PMC10393437/ /pubmed/36534822 http://dx.doi.org/10.1093/rheumatology/keac680 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Science Dyball, Sarah Reynolds, John A Herrick, Ariane L Haque, Sahena Chinoy, Hector Bruce, Ellen Naz, Sophia Parker, Ben Bruce, Ian N Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort |
title | Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort |
title_full | Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort |
title_fullStr | Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort |
title_full_unstemmed | Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort |
title_short | Determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the LEAP cohort |
title_sort | determinants of health-related quality of life across the spectrum of connective tissue diseases using latent profile analysis: results from the leap cohort |
topic | Clinical Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393437/ https://www.ncbi.nlm.nih.gov/pubmed/36534822 http://dx.doi.org/10.1093/rheumatology/keac680 |
work_keys_str_mv | AT dyballsarah determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort AT reynoldsjohna determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort AT herrickarianel determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort AT haquesahena determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort AT chinoyhector determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort AT bruceellen determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort AT nazsophia determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort AT parkerben determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort AT bruceiann determinantsofhealthrelatedqualityoflifeacrossthespectrumofconnectivetissuediseasesusinglatentprofileanalysisresultsfromtheleapcohort |