Brix Ninna, Glerup Mia, Foell Dirk, Kessel Christoph, Wittkowski Helmut, Berntson Lillemor, Fasth Anders, Nielsen Susan, Nordal Ellen, Rygg Marite, Hasle Henrik, Herlin Troels
Department of Pediatrics and Adolescent Medicine, Aalborg University Hospital, Aalborg, Denmark.
Department of Pediatrics and Adolescent Medicine, Aarhus University Hospital, Aarhus, Denmark.
J Pediatr. 2023 Jul;258:113406. doi: 10.1016/j.jpeds.2023.113406. Epub 2023 Apr 4.
To evaluate the predictive value of biomarkers of inflammation like phagocyte-related S100 proteins and a panel of inflammatory cytokines in order to differentiate the child with acute lymphoblastic leukemia (ALL) from juvenile idiopathic arthritis (JIA).
In this cross-sectional study, we measured S100A9, S100A12, and 14 cytokines in serum from children with ALL (n = 150, including 27 with arthropathy) and JIA (n = 236). We constructed predictive models computing areas under the curve (AUC) as well as predicted probabilities in order to differentiate ALL from JIA. Logistic regression was used for predictions of ALL risk, considering the markers as the respective exposures. We performed internal validation using repeated 10-fold cross-validation and recalibration, adjusted for age.
In ALL, the levels of S100A9, S100A12, interleukin (IL)-1 beta, IL-4, IL-13, IL-17, matrix metalloproteinase-3, and myeloperoxidase were low compared with JIA (P < .001). IL-13 had an AUC of 100% (95% CI 100%-100%) due to no overlap between the serum levels in the 2 groups. Further, IL-4 and S100A9 had high predictive performance with AUCs of 99% (95% CI 97%-100%) and 98% (95% CI 94%-99%), respectively, exceeding both hemoglobin, platelets, C-reactive protein, and erythrocyte sedimentation rate.
The biomarkers S100A9, IL-4, and IL-13 might be valuable markers to differentiate ALL from JIA.
评估炎症生物标志物（如吞噬细胞相关的S100蛋白和一组炎性细胞因子）在区分急性淋巴细胞白血病（ALL）患儿与幼年特发性关节炎（JIA）方面的预测价值。
在这项横断面研究中，我们检测了ALL患儿（n = 150，包括27例有关节病的患儿）和JIA患儿（n = 236）血清中的S100A9、S100A12以及14种细胞因子。我们构建了预测模型，计算曲线下面积（AUC）以及预测概率，以区分ALL和JIA。使用逻辑回归预测ALL风险，将这些标志物视为各自的暴露因素。我们采用重复10倍交叉验证和重新校准进行内部验证，并对年龄进行了调整。
与JIA相比，ALL患儿的S100A9、S100A12、白细胞介素（IL）-1β、IL-4、IL-13、IL-17、基质金属蛋白酶-3和髓过氧化物酶水平较低（P < 0.001）。由于两组血清水平无重叠，IL-13的AUC为100%（95%CI 100%-100%）。此外，IL-4和S100A9具有较高的预测性能，AUC分别为99%（95%CI 97%-100%）和98%（95%CI 94%-99%），均超过血红蛋白、血小板、C反应蛋白和红细胞沉降率。
生物标志物S100A9、IL-4和IL-13可能是区分ALL和JIA的有价值标志物。
