World Workshop on Oral Medicine VII: Biomarkers predicting lymphoma in the salivary glands of patients with Sjögren's syndrome—A systematic review.

Autor: Delli, Konstantina, Villa, Alessandro, Farah, Camile S., Celentano, Antonio, Ojeda, David, Peterson, Douglas, Jensen, Siri B., Glurich, Ingrid, Vissink, Arjan
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Zdroj: Oral Diseases; Jun2019 Supplement S1, Vol. 25, p49-63, 15p, 1 Diagram, 3 Charts, 1 Graph
Abstrakt: Objective: To conduct a systematic review of studies exploring potential biomarkers for development, course, and efficacy of treatment of lymphomas in salivary glands of patients with Sjögren's syndrome. Material and Methods: Eligible studies were identified through a comprehensive search of two databases, that is, PubMed and EMBASE. Quality of included articles was assessed with the "Quality In Prognosis Studies" (QUIPS) tool. The "CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies" (CHARMS) was used to facilitate data extraction. Results: Fifty‐eight studies met the inclusion criteria. Only one study assessed the progression of lymphoma. Moderate risk of bias was detected in "outcome measurement," "study participation," and "study confounding" domains. Parotid gland enlargement, mixed monoclonal cryoglobulins, and low C4 levels represented strongest predictors of lymphoma development. The role of histological biomarkers, and specifically germinal centers, remains controversial. Clinical and methodological heterogeneity across studies precluded conduct of a meta‐analysis. Conclusions: Specific biomarkers in combination with clinical manifestations represent potential candidates for advancing precision medicine approaches to lymphoma prediction in patients with Sjögren's syndrome. Current focus has increasingly been on genetic and epigenetic markers as candidate predictors. Predictive accuracy of key biomarker candidates remains to be tested in well‐designed prospectively followed Sjögren's syndrome cohorts. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index