Clinical rheumatology · 2026
Interferon-γ as a predictive biomarker for macrophage activation syndrome in systemic JIA: a chinese multicenter study.
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Xu Xuefeng, Wu Jianqiang, Peng Yue, Qiu Lingzhi, Peng Yuanyuan, Liu Jinxiang, Li Yunyan, Xie Fang, Jin Xinghao, Li Xiaoqing, Geng Lingling, Yu Haiguo, Zhang Wei, Yang Sirui, Wu Ling, Liu Xiaohui, Lu Meiping
Аннотация
OBJECTIVES: To develop and validate interferon-γ-based early prediction models for MAS in pediatric SJIA patients.
METHODS: We conducted a retrospective multicentre study of hospitalized SJIA patients complicated with MAS across seven tertiary paediatric centres in China between January 2020 and December 2024. Demographic, clinical, laboratory, and cytokine data were extracted from electronic medical records. Univariate and multivariate logistic regression analyses identified independent risk factors. A nomogram and cytokine-based predictive models were constructed and externally validated.
RESULTS: In the training cohort, independent predictors of MAS included thrombocytopenia (≤ 181 × 10⁹/L; OR 31.5, P = 0.002), elevated AST (> 50 U/L; OR 24.5, P < 0.001), hypertriglyceridaemia (> 1.76 mmol/L; OR 12.0, P < 0.001), hyperferritinaemia (> 684 μg/L; OR 33.0, P < 0.001), hypofibrinogenaemia (≤ 3.6 g/L; OR 24.9, P < 0.001), elevated D-dimer (> 5.0 mg/L; OR 26.3, P < 0.001), increased IL-10 (> 15 pg/mL; OR 29.4, P < 0.001), and IFN-γ (≥ 20 pg/mL; OR 17.9, P < 0.001). A clinical nomogram incorporating AST, fibrinogen, and ferritin yielded an area under the curve (AUC) of 0.92 for MAS prediction. Furthermore, integrating IFN-γwith specific clinical marker (AST, and fibrinogen, or ferritin and fibrinogen) established enhanced models that maintained robust discriminative accuracy across training and external validation cohorts. with AUCs ranging from 0.91 to 0.98.
CONCLUSION: We developed and validated early prediction tools for MAS in paediatric SJIA by integrating serum IFN-γ with clinical parameters. These models may support timely diagnosis and treatment. Key points • Serum IFN-γ is a strong early biomarker for MAS in SJIA. • A cytokine-enhanced model improves MAS risk prediction in paediatric SJIA. • Ferritin, AST, and fibrinogen remain core predictors of MAS.
METHODS: We conducted a retrospective multicentre study of hospitalized SJIA patients complicated with MAS across seven tertiary paediatric centres in China between January 2020 and December 2024. Demographic, clinical, laboratory, and cytokine data were extracted from electronic medical records. Univariate and multivariate logistic regression analyses identified independent risk factors. A nomogram and cytokine-based predictive models were constructed and externally validated.
RESULTS: In the training cohort, independent predictors of MAS included thrombocytopenia (≤ 181 × 10⁹/L; OR 31.5, P = 0.002), elevated AST (> 50 U/L; OR 24.5, P < 0.001), hypertriglyceridaemia (> 1.76 mmol/L; OR 12.0, P < 0.001), hyperferritinaemia (> 684 μg/L; OR 33.0, P < 0.001), hypofibrinogenaemia (≤ 3.6 g/L; OR 24.9, P < 0.001), elevated D-dimer (> 5.0 mg/L; OR 26.3, P < 0.001), increased IL-10 (> 15 pg/mL; OR 29.4, P < 0.001), and IFN-γ (≥ 20 pg/mL; OR 17.9, P < 0.001). A clinical nomogram incorporating AST, fibrinogen, and ferritin yielded an area under the curve (AUC) of 0.92 for MAS prediction. Furthermore, integrating IFN-γwith specific clinical marker (AST, and fibrinogen, or ferritin and fibrinogen) established enhanced models that maintained robust discriminative accuracy across training and external validation cohorts. with AUCs ranging from 0.91 to 0.98.
CONCLUSION: We developed and validated early prediction tools for MAS in paediatric SJIA by integrating serum IFN-γ with clinical parameters. These models may support timely diagnosis and treatment. Key points • Serum IFN-γ is a strong early biomarker for MAS in SJIA. • A cytokine-enhanced model improves MAS risk prediction in paediatric SJIA. • Ferritin, AST, and fibrinogen remain core predictors of MAS.