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Meta-Analysis
. 2015 Jan;35(1):17-26.
doi: 10.1007/s00296-014-3051-x. Epub 2014 Jun 5.

Identification of lymphoma predictors in patients with primary Sjögren's syndrome: a systematic literature review and meta-analysis

Affiliations
Meta-Analysis

Identification of lymphoma predictors in patients with primary Sjögren's syndrome: a systematic literature review and meta-analysis

Maria B Nishishinya et al. Rheumatol Int. 2015 Jan.

Abstract

To identify risk and predictors of lymphoma or lymphoproliferative disease in patients with primary Sjögren syndrome. Articles were identified through a comprehensive search strategy in Medline, Embase and Cochrane CENTRAL. Studies had to investigate primary Sjögren syndrome patients, 18 years of age or older, with the goal of examining potential clinical, immunological and hematological risk factors for lymphoma or lymphoproliferative disease. The quality of the studies was graded using the Oxford Levels of Evidence Scale. Whenever possible, the authors created evidence tables and performed meta-analysis. Of 900 studies identified, 18 were selected for inclusion. These studies provided data from over 15,000 patients (90 % female) for analysis. Lymphadenopathy, parotid enlargement, palpable purpura, low C4 serum levels and cryoglobulins were the most consistent non-Hodgkin´s lymphoma/lymphoproliferative disease predictors. Additionally, some of the studies identified splenomegaly, low C3 serum levels, lymphopenia and neutropenia as significant prognostic factors. The detection of germinal center-like lesions in primary Sjögren Syndrome diagnostic salivary biopsies was also proposed as highly predictive of non-Hodgkin´s lymphoma. In contrast, anemia, anti-Ro, anti-La, antinuclear antibodies, rheumatoid factor, male gender and hypergammaglobulinemia were not associated with lymphoma or lymphoproliferative disease. Patients with primary Sjögren syndrome have an increased risk of lymphoma or lymphoproliferative disease compared to the general population. Ascertaining relevant and reliable predictors in this patient population would greatly facilitate the identification of patients at elevated risk for closer monitoring in the context of limited resources.

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