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Predicting the risk for lymphoma development in Sjogren syndrome: An easy tool for clinical use
The heightened risk of non-Hodgkin lymphoma (NHL) development in primary Sjogren syndrome (SS) is well established. Several adverse clinical and laboratory predictors have been described. In the current work, we aimed to formulate a predictive score for NHL development, based on clinical, serologica...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4998301/ https://www.ncbi.nlm.nih.gov/pubmed/27336863 http://dx.doi.org/10.1097/MD.0000000000003766 |
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author | Fragkioudaki, Sofia Mavragani, Clio P. Moutsopoulos, Haralampos M. |
author_facet | Fragkioudaki, Sofia Mavragani, Clio P. Moutsopoulos, Haralampos M. |
author_sort | Fragkioudaki, Sofia |
collection | PubMed |
description | The heightened risk of non-Hodgkin lymphoma (NHL) development in primary Sjogren syndrome (SS) is well established. Several adverse clinical and laboratory predictors have been described. In the current work, we aimed to formulate a predictive score for NHL development, based on clinical, serological, and histopathological findings at the time of SS diagnosis. In the present case–control study of 381 primary SS patients and 92 primary SS patients with concomitant NHL, clinical, serological, and histopathological variables at the time of SS diagnosis were retrospectively recorded. For the identification of predictors for NHL development univariate and multivariate models were constructed. Salivary gland enlargement (SGE), lymphadenopathy, Raynaud phenomenon, anti-Ro/SSA or/and anti-La/SSB autoantibodies, rheumatoid factor (RF) positivity, monoclonal gammopathy, and C4 hypocomplementemia were shown to be independent predictors for NHL development. On the basis of the number of independent risk factors identified, a predictive risk score for NHL development was formulated. Thus, patients presenting with ≤2 risk factors had a 3.8% probability of NHL development, those with 3 to 6 risk factors 39.9% (OR (95%CI): 16.6 [6.5–42.5], P < 0.05), while in the presence of all 7 risk factors the corresponding probability reached 100% (OR [95%CI]: 210.0 [10.0–4412.9], P < 0.0001). In conclusion, an easy to use diagnostic scoring tool for NHL development in the context of SS is presented. This model is highly significant for the design of early therapeutic interventions in high risk SS patients for NHL development. |
format | Online Article Text |
id | pubmed-4998301 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-49983012016-09-02 Predicting the risk for lymphoma development in Sjogren syndrome: An easy tool for clinical use Fragkioudaki, Sofia Mavragani, Clio P. Moutsopoulos, Haralampos M. Medicine (Baltimore) 6900 The heightened risk of non-Hodgkin lymphoma (NHL) development in primary Sjogren syndrome (SS) is well established. Several adverse clinical and laboratory predictors have been described. In the current work, we aimed to formulate a predictive score for NHL development, based on clinical, serological, and histopathological findings at the time of SS diagnosis. In the present case–control study of 381 primary SS patients and 92 primary SS patients with concomitant NHL, clinical, serological, and histopathological variables at the time of SS diagnosis were retrospectively recorded. For the identification of predictors for NHL development univariate and multivariate models were constructed. Salivary gland enlargement (SGE), lymphadenopathy, Raynaud phenomenon, anti-Ro/SSA or/and anti-La/SSB autoantibodies, rheumatoid factor (RF) positivity, monoclonal gammopathy, and C4 hypocomplementemia were shown to be independent predictors for NHL development. On the basis of the number of independent risk factors identified, a predictive risk score for NHL development was formulated. Thus, patients presenting with ≤2 risk factors had a 3.8% probability of NHL development, those with 3 to 6 risk factors 39.9% (OR (95%CI): 16.6 [6.5–42.5], P < 0.05), while in the presence of all 7 risk factors the corresponding probability reached 100% (OR [95%CI]: 210.0 [10.0–4412.9], P < 0.0001). In conclusion, an easy to use diagnostic scoring tool for NHL development in the context of SS is presented. This model is highly significant for the design of early therapeutic interventions in high risk SS patients for NHL development. Wolters Kluwer Health 2016-06-24 /pmc/articles/PMC4998301/ /pubmed/27336863 http://dx.doi.org/10.1097/MD.0000000000003766 Text en Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 |
spellingShingle | 6900 Fragkioudaki, Sofia Mavragani, Clio P. Moutsopoulos, Haralampos M. Predicting the risk for lymphoma development in Sjogren syndrome: An easy tool for clinical use |
title | Predicting the risk for lymphoma development in Sjogren syndrome: An easy tool for clinical use |
title_full | Predicting the risk for lymphoma development in Sjogren syndrome: An easy tool for clinical use |
title_fullStr | Predicting the risk for lymphoma development in Sjogren syndrome: An easy tool for clinical use |
title_full_unstemmed | Predicting the risk for lymphoma development in Sjogren syndrome: An easy tool for clinical use |
title_short | Predicting the risk for lymphoma development in Sjogren syndrome: An easy tool for clinical use |
title_sort | predicting the risk for lymphoma development in sjogren syndrome: an easy tool for clinical use |
topic | 6900 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4998301/ https://www.ncbi.nlm.nih.gov/pubmed/27336863 http://dx.doi.org/10.1097/MD.0000000000003766 |
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