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Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data

BACKGROUND: Traditionally rheumatoid arthritis (RA) trials classify patients as responders and non-responders; they ignore the potential range of treatment responses. Group Based Trajectory Models (GBTMs) provide a more refined approach. They identify patient subgroups with similar outcome trajector...

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Autores principales: Ibrahim, Fowzia, Scott, Ian C, Scott, David L, Ayis, Salma Ahmed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518927/
https://www.ncbi.nlm.nih.gov/pubmed/37749588
http://dx.doi.org/10.1186/s41927-023-00348-5
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author Ibrahim, Fowzia
Scott, Ian C
Scott, David L
Ayis, Salma Ahmed
author_facet Ibrahim, Fowzia
Scott, Ian C
Scott, David L
Ayis, Salma Ahmed
author_sort Ibrahim, Fowzia
collection PubMed
description BACKGROUND: Traditionally rheumatoid arthritis (RA) trials classify patients as responders and non-responders; they ignore the potential range of treatment responses. Group Based Trajectory Models (GBTMs) provide a more refined approach. They identify patient subgroups with similar outcome trajectories. We used GBTMs to classify patients into subgroups of varying responses and explore factors associated with different responses to intensive treatment in a secondary analysis of intensive treatment in the TITRATE clinical trial. METHODS: The TITRATE trial enrolled 335 patients with RA: 168 patients were randomised to receive intensive management, which comprised monthly assessments including measures of the disease activity score for 28 joints (DAS28), treatment escalation when patients were not responding sufficiently and psychosocial support; 163 of these patients completed the trial. We applied GBTMs to monthly DAS28 scores over one year to these patients who had received intensive management. The control group had standard care and were assessed every 6 months; they had too few DAS28 scores for applying GBTMs. RESULTS: GBTMs identified three distinct trajectories in the patients receiving intensive management: good (n = 40), moderate (n = 76) and poor (n = 47) responders. Baseline body mass index (BMI), disability, fatigue and depression levels were significantly different between trajectory groups. Few (10%) good responders were obese, compared to 38% of moderate, and 43% of poor responders (P = 0.002). Few (8%) good responders had depression, compared to 14% moderate responders, and 38% poor responders (P < 0.001). The key difference in treatments was using high-cost biologics, used in only 5% of good responders but 30% of moderate and 51% of poor responders (P < 0.001). Most good responders had endpoint remissions and low disability, pain, and fatigue scores; few poor responders achieved any favourable outcomes. CONCLUSION: GBTMs identified three trajectories of disease activity progression in patients receiving intensive management for moderately active RA. Baseline variables like obesity and depression predicted different treatment responses. Few good responders needed biologic drugs; they responded to conventional DMARDs alone. GBTMs have the potential to facilitate precision medicine enabling patient-oriented treatment strategies based on key characteristics. REGISTRATION: TITRATE Trial ISRCTN 70160382.
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spelling pubmed-105189272023-09-26 Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data Ibrahim, Fowzia Scott, Ian C Scott, David L Ayis, Salma Ahmed BMC Rheumatol Research BACKGROUND: Traditionally rheumatoid arthritis (RA) trials classify patients as responders and non-responders; they ignore the potential range of treatment responses. Group Based Trajectory Models (GBTMs) provide a more refined approach. They identify patient subgroups with similar outcome trajectories. We used GBTMs to classify patients into subgroups of varying responses and explore factors associated with different responses to intensive treatment in a secondary analysis of intensive treatment in the TITRATE clinical trial. METHODS: The TITRATE trial enrolled 335 patients with RA: 168 patients were randomised to receive intensive management, which comprised monthly assessments including measures of the disease activity score for 28 joints (DAS28), treatment escalation when patients were not responding sufficiently and psychosocial support; 163 of these patients completed the trial. We applied GBTMs to monthly DAS28 scores over one year to these patients who had received intensive management. The control group had standard care and were assessed every 6 months; they had too few DAS28 scores for applying GBTMs. RESULTS: GBTMs identified three distinct trajectories in the patients receiving intensive management: good (n = 40), moderate (n = 76) and poor (n = 47) responders. Baseline body mass index (BMI), disability, fatigue and depression levels were significantly different between trajectory groups. Few (10%) good responders were obese, compared to 38% of moderate, and 43% of poor responders (P = 0.002). Few (8%) good responders had depression, compared to 14% moderate responders, and 38% poor responders (P < 0.001). The key difference in treatments was using high-cost biologics, used in only 5% of good responders but 30% of moderate and 51% of poor responders (P < 0.001). Most good responders had endpoint remissions and low disability, pain, and fatigue scores; few poor responders achieved any favourable outcomes. CONCLUSION: GBTMs identified three trajectories of disease activity progression in patients receiving intensive management for moderately active RA. Baseline variables like obesity and depression predicted different treatment responses. Few good responders needed biologic drugs; they responded to conventional DMARDs alone. GBTMs have the potential to facilitate precision medicine enabling patient-oriented treatment strategies based on key characteristics. REGISTRATION: TITRATE Trial ISRCTN 70160382. BioMed Central 2023-09-25 /pmc/articles/PMC10518927/ /pubmed/37749588 http://dx.doi.org/10.1186/s41927-023-00348-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ibrahim, Fowzia
Scott, Ian C
Scott, David L
Ayis, Salma Ahmed
Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data
title Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data
title_full Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data
title_fullStr Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data
title_full_unstemmed Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data
title_short Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data
title_sort heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518927/
https://www.ncbi.nlm.nih.gov/pubmed/37749588
http://dx.doi.org/10.1186/s41927-023-00348-5
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