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...

Descripción completa

Detalles Bibliográficos
Autores principales: Dyball, Sarah, Reynolds, John A, Herrick, Ariane L, Haque, Sahena, Chinoy, Hector, Bruce, Ellen, Naz, Sophia, Parker, Ben, Bruce, Ian N
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