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

机译：使用梯度增强树组合预测原发性干燥综合征患者的淋巴瘤结局和危险因素

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Primary Sjogren’s Syndrome (pSS) is a chronic autoimmune disease followed by exocrine gland dysfunction, where it has been long stated that 5% of pSS patients are prone to lymphoma development. In this work, we use clinical data from 449 pSS patients to develop a first, rule-based, supervised learning model that can be used to predict lymphoma outcomes, as well as, identify prominent features for lymphoma prediction in pSS patients. Towards this direction, the gradient boosting method combined with regression tree ensembles is used to derive a rule-based, decision model for lymphoma prediction. Our results reveal an average accuracy 87.1% and area under the curve score 88%, highlighting the importance of the C4 value, the rheumatoid factor and the lymphadenopathy factor as prominent lymphoma predictors, among others.

机译：原发性干燥综合征（pSS）是继发于外分泌腺功能障碍的慢性自身免疫性疾病，长期以来，已有5％的pSS患者易患淋巴瘤。在这项工作中，我们使用来自449名pSS患者的临床数据来开发第一个基于规则的监督学习模型，该模型可用于预测淋巴瘤的预后以及确定pSS患者的淋巴瘤预测的突出特征。朝着这个方向，将梯度增强方法与回归树组合相结合，可以得出用于淋巴瘤预测的基于规则的决策模型。我们的结果显示平均准确度为87.1％，曲线下面积为88％，突出了C4值，类风湿因子和淋巴结病因子作为重要的淋巴瘤预测指标的重要性。

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《Annual International Conference of the IEEE Engineering in Medicine and Biology Society》|2019年|2165-2168|共4页
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Vasileios C. Pezoulas; Themis P. Exarchos; Athanasios G. Tzioufas; Salvatore De Vita; Dimitrios I. Fotiadis;
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Boosting; Predictive models; Data models; Salivary glands; Diseases; Mathematical model;

机译：促进;预测模型;数据模型;唾液腺;疾病;数学模型;

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专利

1. Association between B Cell Growth Factors and Primary Sj?gren’s Syndrome-Related Autoantibodies in Patients with Non-Hodgkin’s Lymphoma [J] . Zhenhua Xian, Dehua Fu, Shuang Liu, Journal of immunology research. . 2019,第1期

机译：B细胞生长因子和原发性SJ之间的关联与非霍奇金淋巴瘤患者的综合征相关的自身抗体
2. Predicting adverse outcomes in primary Sj?gren's syndrome: identification of prognostic factors [J] . P. Brito-Zerón M. Ramos-Casals A. Bove J. Sentis, and J. Font Rheumatology . 2007,第8期

机译：预测原发性干燥综合征的不良预后：确定预后因素
3. Is primary Sj?gren’s syndrome a risk factor for malignancies different from lymphomas? What does the literature highlight about it? [J] . Ciro Manzo, Melek Kechida Reumatologia . 2017,第3期

机译：原发性干燥综合征是否不同于淋巴瘤是恶性肿瘤的危险因素？文献对此有何强调？
4. Predicting lymphoma outcomes and risk factors in patients with primary Sj?gren’s Syndrome using gradient boosting tree ensembles [C] . Vasileios C. Pezoulas, Themis P. Exarchos, Athanasios G. Tzioufas, Annual International Conference of the IEEE Engineering in Medicine and Biology Society . 2019

机译：使用渐变升压树合奏预测原发性SJ患者淋巴瘤结果和危险因素
5. Immunopathogenic Mechanisms in Primary Sj?gren’s Syndrome [D] . Bj?rk, Albin. 2021

机译：原发性SJ的免疫致病机制？GREN的综合征
6. Association between B Cell Growth Factors and Primary Sjögrens Syndrome-Related Autoantibodies in Patients with Non-Hodgkins Lymphoma [O] . Zhenhua Xian, Dehua Fu, Shuang Liu, 2019

机译：非霍奇金淋巴瘤患者中B细胞生长因子与原发性Sjögren综合征相关自身抗体之间的关联
7. Predicting Lymphoma Development by Exploiting Genetic Variants and Clinical Findings in a Machine Learning-Based Methodology With Ensemble Classifiers in a Cohort of Sjögren's Syndrome Patients [O] . Konstantina D. Kourou, Vasileios C. Pezoulas, Eleni I. Georga, 2020

机译：通过在Sjögren综合征患者队列的基于机器学习方法中利用基于机器学习的方法的遗传变异和临床发现来预测淋巴瘤发展

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

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