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Predicting treatment response to IL6R blockers in rheumatoid arthritis
Patients with severe, active RA who have not responded to conventional therapy may receive biological disease modifying anti-rheumatic drugs (bDMARDs). However, 40% of cases do not achieve complete disease control, resulting in a negative impact on patient quality of life and representing a waste of...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733712/ https://www.ncbi.nlm.nih.gov/pubmed/32864695 http://dx.doi.org/10.1093/rheumatology/keaa529 |
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author | Nouri, Bako Nair, Nisha Barton, Anne |
author_facet | Nouri, Bako Nair, Nisha Barton, Anne |
author_sort | Nouri, Bako |
collection | PubMed |
description | Patients with severe, active RA who have not responded to conventional therapy may receive biological disease modifying anti-rheumatic drugs (bDMARDs). However, 40% of cases do not achieve complete disease control, resulting in a negative impact on patient quality of life and representing a waste of healthcare resources. Ongoing research seeks to establish biomarkers, which can be used to predict treatment response to biologics in RA to enable more targeted approaches to treatment. However, much of the work has focused on one class of biologic drug, the TNF inhibitors (TNFi). Here, we will review the current state of research to identify biomarkers predictive of response to the class of bDMARDs targeting the IL6R. While success has been limited thus far, serum drug and low ICAM1 levels have shown promise, with associations reported in independent studies. The challenges faced by researchers and lessons learned from studies of TNFi will be discussed. |
format | Online Article Text |
id | pubmed-7733712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77337122020-12-17 Predicting treatment response to IL6R blockers in rheumatoid arthritis Nouri, Bako Nair, Nisha Barton, Anne Rheumatology (Oxford) Review Articles Patients with severe, active RA who have not responded to conventional therapy may receive biological disease modifying anti-rheumatic drugs (bDMARDs). However, 40% of cases do not achieve complete disease control, resulting in a negative impact on patient quality of life and representing a waste of healthcare resources. Ongoing research seeks to establish biomarkers, which can be used to predict treatment response to biologics in RA to enable more targeted approaches to treatment. However, much of the work has focused on one class of biologic drug, the TNF inhibitors (TNFi). Here, we will review the current state of research to identify biomarkers predictive of response to the class of bDMARDs targeting the IL6R. While success has been limited thus far, serum drug and low ICAM1 levels have shown promise, with associations reported in independent studies. The challenges faced by researchers and lessons learned from studies of TNFi will be discussed. Oxford University Press 2020-08-31 /pmc/articles/PMC7733712/ /pubmed/32864695 http://dx.doi.org/10.1093/rheumatology/keaa529 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Articles Nouri, Bako Nair, Nisha Barton, Anne Predicting treatment response to IL6R blockers in rheumatoid arthritis |
title | Predicting treatment response to IL6R blockers in rheumatoid arthritis |
title_full | Predicting treatment response to IL6R blockers in rheumatoid arthritis |
title_fullStr | Predicting treatment response to IL6R blockers in rheumatoid arthritis |
title_full_unstemmed | Predicting treatment response to IL6R blockers in rheumatoid arthritis |
title_short | Predicting treatment response to IL6R blockers in rheumatoid arthritis |
title_sort | predicting treatment response to il6r blockers in rheumatoid arthritis |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733712/ https://www.ncbi.nlm.nih.gov/pubmed/32864695 http://dx.doi.org/10.1093/rheumatology/keaa529 |
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