Wan Liyan, Gao Yuting, Yang Chendie, Gu Jieyu, Liu Tingting, Hu Qiongyi, Tang Zihan, Teng Jialin, Liu Honglei, Cheng Xiaobing, Ye Junna, Su Yutong, Shi Yi, Huang Xinyun, Yang Chengde, Li Biao, Shi Hui, Zhang Min
Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Department of Rheumatology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Quant Imaging Med Surg. 2023 Jan 1;13(1):37-48. doi: 10.21037/qims-22-246. Epub 2022 Nov 2.
Adult-onset still's disease (AOSD) and lymphoma are the common causes of fever of unknown origin (FUO) and show some similar clinical symptoms. This study aimed to establish a reliable and easy-to-used scoring model based on clinical information, laboratory characteristics and F-fluorodeoxyglucose positron emission tomography/computer tomography (F-FDG PET/CT) images for the differential diagnosis of these two diseases.
A development cohort including 70 AOSD and 37 lymphoma patients was used to establish a scoring model based on the features of PET/CT images. The scoring model was then validated in a validation cohort of 15 AOSD and 12 lymphoma patients. The features of involved bone marrow, spleen, lymph nodes, and other organs or tissues displayed on PET/CT images were compared. Multiple logistics regression and decision tree analysis were used to establish the scoring model.
Four features that could significantly differentiate these two diseases were selected to establish a scoring model discriminating AOSD from lymphoma, including (I) white blood cell (WBC) count ≤10×10/L (1 point); (II) ferritin ≤ upper limit of normal (ULN) (1 point); (III) no abnormal bone marrow metabolism (1 point); (IV) total lesion glycolysis (TLG) >9.0 (1 point). After decision tree analysis, it showed that a score ≤1 indicates AOSD. A score ≥3 strongly suggested lymphoma, with a sensitivity of 81.1% and specificity of 90.0% in the development cohort, and a sensitivity of 58.3% and specificity of 100% in the validation cohort.
Our scoring model showed good diagnosis performance in distinguishing AOSD from lymphoma.
成人斯蒂尔病（AOSD）和淋巴瘤是不明原因发热（FUO）的常见病因，且表现出一些相似的临床症状。本研究旨在基于临床信息、实验室特征和氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描（F-FDG PET/CT）图像建立一种可靠且易于使用的评分模型，用于这两种疾病的鉴别诊断。
一个包含70例AOSD患者和37例淋巴瘤患者的开发队列用于基于PET/CT图像特征建立评分模型。然后在一个由15例AOSD患者和12例淋巴瘤患者组成的验证队列中对该评分模型进行验证。比较PET/CT图像上显示的累及骨髓、脾脏、淋巴结及其他器官或组织的特征。采用多元逻辑回归和决策树分析建立评分模型。
选择四个可显著区分这两种疾病的特征建立一个区分AOSD和淋巴瘤的评分模型，包括：（I）白细胞（WBC）计数≤10×10⁹/L（1分）；（II）铁蛋白≤正常上限（ULN）（1分）；（III）无异常骨髓代谢（1分）；（IV）总病变糖酵解（TLG）>9.0（1分）。经过决策树分析，结果显示评分≤1表明为AOSD。评分≥3强烈提示为淋巴瘤，在开发队列中的敏感性为81.1%，特异性为90.0%，在验证队列中的敏感性为58.3%，特异性为100%。
我们的评分模型在区分AOSD和淋巴瘤方面显示出良好的诊断性能。
