Predicting lymphoma outcomes and risk factors in patients with primary Sjögren's Syndrome using gradient boosting tree ensembles

A federated AI strategy for the classification of patients with Mucosa Associated Lymphoma Tissue (MALT) lymphoma across multiple harmonized cohorts

Mucosa Associated Lymphoma Tissue (MALT) type is an extremely rare type of lymphoma which occurs in less than 3% of patients with primary Sjögren's Syndrome (pSS). No reported studies so far have been able to investigate risk factors for MALT development across multiple cohort databases with sufficient statistical power. Here, we present a generalized, federated AI (artificial intelligence) strategy which enables the training of AI algorithms across multiple harmonized databases. A case study is conducted towards the development of MALT classification models across 17 databases on pSS. Advanced AI algorithms were developed, including federated Multinomial Naïve Bayes (FMNB), federated gradient boosting trees (FGBT), FGBT with dropouts (FDART), and the federated Multilayer Perceptron (FMLP). The FDART with dropout rate 0.3 achieved the best performance with sensitivity 0.812, and specificity 0.829, yielding 8 biomarkers as prominent for MALT development.

Ultrasound and Bioptic Investigation of Patients with Primary Sjögren's Syndrome

Primary Sjögren's syndrome (pSS) is a chronic and heterogeneous disorder characterized by a wide spectrum of glandular and extra-glandular features. The hallmark of pSS is considered to be the immune-mediated involvement of the exocrine glands and B-cell hyperactivation. This leads pSS patients to an increased risk of developing lymphoproliferative diseases, and persistent (>2 months) major salivary gland enlargement is a well-known clinical sign of possible involvement by B cell lymphoma. Better stratification of the patients may improve understanding of the mechanism underlying the risk of lymphoproliferative disorder. Here, we summarize the role of different imaging techniques and a bioptic approach in pSS patients, focusing mainly on the role of salivary gland ultrasonography (SGUS) and a US-guided core needle biopsy (Us-guided CNB) as diagnostic and prognostic tools in pSS patients with persistent parotid swelling.

Novel insights on lymphoma and lymphomagenesis in primary Sjögren's Syndrome

Primary Sjögren's Syndrome (pSS) is a systemic autoimmune disease characterized by a chronic inflammatory process mainly affecting the exocrine glands but also burdened by a wide range of extraglandular manifestations. Non-Hodgkin lymphoma (NHL) is the most severe pSS complication worsening disease prognosis. We summarized original articles published between April 2018 and May 2020 on this topic aiming to highlight novelties on lymphoma and lymphomagenesis. Results have been grouped by epidemiology, etiopathogenesis and predictors of lymphoma. NHL is the most severe complication of pSS and occurs in around 5-10% of patients. Over the last two years, several clinical, serological, and histopathological features have been proposed as predictive for lymphoma in pSS patients, allowing early diagnosis and consequently, better management and prognosis. Individual monitoring for disease activity and possible lymphoma development is a central clue in the evaluation of pSS patients.