Diagnostic predictive model for distinguishing intravascular large B-cell lymphoma among patients with fever of unknown origin

作者：Chao Chen, Yiao Di, Zhe Zhuang, Zepeng Li, Congwei Jia, Ximin Shi, Danqing Zhao, Wei Wang, Wei Zhang, Daobin Zhou, Yan Zhang · 发表于：Research Square · 年份：2024 · DOI：10.21203/rs.3.rs-4441204/v1 · 被引用次数：1 · 研究领域：CNS Lymphoma Diagnosis and Treatment、Lymphoma Diagnosis and Treatment、Autoimmune and Inflammatory Disorders Research

Abstract Intravascular large B-cell lymphoma (IVLBCL) is relatively rare. Due to the lack of distinctive symptoms, the diagnosis is difficult. Fever of unknown origin (FUO) is the most common symptom. This study retrospectively analyzed IVLBCL patients and FUO patients between February 2015 and October 2023. Diagnostic predictive models were constructed using multivariable logistic regression in the training cohort including 42 IVLBCL patients and 45 FUO patients. Model 1 consisted of peripheral edema, hypoxemia, neurological symptoms, hemophagocytic lymphohistiocytosis, and interstitial lung abnormalities on CT, exhibited good diagnostic efficiency (AUC = 0.928). Model 2 consisted of peripheral edema, hypoxemia, neurological symptoms and Interleukin-10/Interleukin-6 concentration ratio, showed a higher diagnostic ability than Model 1 (AUC = 0.982, p = 0.023). The diagnostic abilities of models were validated internally in leave-one-out validation and externally in the validation cohort. As some medical institutions may lack the capability to test for interleukin concentration, Model 1 can be used to help the diagnosis of IVLBCL in these institutions. Based on Model 1 and Model 2, we established and validated two integer-based scoring systems for clinical practice. Most patients (58%) were histologically diagnosed by random skin biopsy, and the positive rate of random skin biopsy was 79.5%.