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Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models
BACKGROUND: Systemic lupus erythematosus (SLE) is a heterogeneous systemic autoimmune condition for which there are limited licensed therapies. Clinical trial design is challenging in SLE due at least in part to imperfect outcome measures. Improved understanding of how disease activity changes over...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320218/ https://www.ncbi.nlm.nih.gov/pubmed/34321096 http://dx.doi.org/10.1186/s13075-021-02584-x |
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author | Reynolds, John A. Prattley, Jennifer Geifman, Nophar Lunt, Mark Gordon, Caroline Bruce, Ian N. |
author_facet | Reynolds, John A. Prattley, Jennifer Geifman, Nophar Lunt, Mark Gordon, Caroline Bruce, Ian N. |
author_sort | Reynolds, John A. |
collection | PubMed |
description | BACKGROUND: Systemic lupus erythematosus (SLE) is a heterogeneous systemic autoimmune condition for which there are limited licensed therapies. Clinical trial design is challenging in SLE due at least in part to imperfect outcome measures. Improved understanding of how disease activity changes over time could inform future trial design. The aim of this study was to determine whether distinct trajectories of disease activity over time occur in patients with active SLE within a clinical trial setting and to identify factors associated with these trajectories. METHODS: Latent class trajectory models were fitted to a clinical trial dataset of a monoclonal antibody targeting CD22 (Epratuzumab) in patients with active SLE using the numerical BILAG-2004 score (nBILAG). The baseline characteristics of patients in each class and changes in prednisolone over time were identified. Exploratory PK-PD modelling was used to examine cumulative drug exposure in relation to latent class membership. RESULTS: Five trajectories of disease activity were identified, with 3 principal classes: non-responders (NR), slow responders (SR) and rapid-responders (RR). In both the SR and RR groups, significant changes in disease activity were evident within the first 90 days of the trial. The SR and RR patients had significantly higher baseline disease activity, exposure to epratuzumab and activity in specific BILAG domains, whilst NR had lower steroid use at baseline and less change in steroid dose early in the trial. CONCLUSIONS: Longitudinal nBILAG scores reveal different trajectories of disease activity and may offer advantages over fixed endpoints. Corticosteroid use however remains an important confounder in lupus trials and can influence early response. Changes in disease activity and steroid dose early in the trial were associated with the overall disease activity trajectory, supporting the feasibility of performing adaptive trial designs in SLE. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13075-021-02584-x. |
format | Online Article Text |
id | pubmed-8320218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83202182021-07-30 Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models Reynolds, John A. Prattley, Jennifer Geifman, Nophar Lunt, Mark Gordon, Caroline Bruce, Ian N. Arthritis Res Ther Research Article BACKGROUND: Systemic lupus erythematosus (SLE) is a heterogeneous systemic autoimmune condition for which there are limited licensed therapies. Clinical trial design is challenging in SLE due at least in part to imperfect outcome measures. Improved understanding of how disease activity changes over time could inform future trial design. The aim of this study was to determine whether distinct trajectories of disease activity over time occur in patients with active SLE within a clinical trial setting and to identify factors associated with these trajectories. METHODS: Latent class trajectory models were fitted to a clinical trial dataset of a monoclonal antibody targeting CD22 (Epratuzumab) in patients with active SLE using the numerical BILAG-2004 score (nBILAG). The baseline characteristics of patients in each class and changes in prednisolone over time were identified. Exploratory PK-PD modelling was used to examine cumulative drug exposure in relation to latent class membership. RESULTS: Five trajectories of disease activity were identified, with 3 principal classes: non-responders (NR), slow responders (SR) and rapid-responders (RR). In both the SR and RR groups, significant changes in disease activity were evident within the first 90 days of the trial. The SR and RR patients had significantly higher baseline disease activity, exposure to epratuzumab and activity in specific BILAG domains, whilst NR had lower steroid use at baseline and less change in steroid dose early in the trial. CONCLUSIONS: Longitudinal nBILAG scores reveal different trajectories of disease activity and may offer advantages over fixed endpoints. Corticosteroid use however remains an important confounder in lupus trials and can influence early response. Changes in disease activity and steroid dose early in the trial were associated with the overall disease activity trajectory, supporting the feasibility of performing adaptive trial designs in SLE. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13075-021-02584-x. BioMed Central 2021-07-29 2021 /pmc/articles/PMC8320218/ /pubmed/34321096 http://dx.doi.org/10.1186/s13075-021-02584-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Article Reynolds, John A. Prattley, Jennifer Geifman, Nophar Lunt, Mark Gordon, Caroline Bruce, Ian N. Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models |
title | Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models |
title_full | Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models |
title_fullStr | Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models |
title_full_unstemmed | Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models |
title_short | Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models |
title_sort | distinct patterns of disease activity over time in patients with active sle revealed using latent class trajectory models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320218/ https://www.ncbi.nlm.nih.gov/pubmed/34321096 http://dx.doi.org/10.1186/s13075-021-02584-x |
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