Pharmacoepidemiology and drug safety · 2026
Early Identification of Differentiation Syndrome During ATRA and Arsenic Therapy in Pediatric NHR-APL: Insights From a 14-Year Multicenter Cohort.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Fan Zhong, Yang Liang-Chun, Chen Yi-Qiao, Wan Wu-Qing, Mai Hui-Rong, Yang Li-Hua, Lan He-Kui, Zhou Dun-Hua, Li Wan-Li, Guo Bi-Yun, He Fei, Liao Liu-Hua, Chen Hui-Qin, Zhen Zi-Jun, He Xiang-Ling, Feng Xiao-Qin, Chen Guo-Hua, Ji Xun-Qi, Chen Mo, Li Qiao-Ru, Long Xing-Jiang, Tian Chuan, Fu Ying, Huang Xiu-Ya, Luo Jie-Si, Huang Dan-Ping, Wang Li-Na, Li Yu, Li Bin, Luo Xue-Qun, Huang Li-Bin, Tang Yan-Lai, Zhang Xiao-Li
Аннотация
BACKGROUND: The combination of all-trans retinoic acid (ATRA) with arsenic trioxide (ATO) has dramatically improved the cure rate of acute promyelocytic leukemia (APL). However, differentiation syndrome (DS) remains a significant cause of early mortality in APL patients. This severe complication typically occurs during induction therapy with ATRA and/or ATO. Early prediction and timely intervention are crucial to reducing DS-related mortality. This study aimed to identify risk factors for DS and develop a predictive model tailored to children with non-high-risk (NHR) APL.
METHODS: We conducted a multicenter retrospective analysis of 166 pediatric NHR-APL patients treated between 2011 and 2024. Clinical characteristics were compared between DS and non-DS groups. Logistic regression was used to identify independent predictors, and a nomogram was developed based on these variables. The model was evaluated using the area under the curve (AUC) and decision curve analysis (DCA).
RESULTS: Seventeen patients (10.2%) developed DS during induction. Multivariate analysis identified five independent risk factors: female sex, non-chemotherapy group, BCR subtype 3, elevated peripheral promyelocyte proportion (≥ 44%), and platelet count (≥ 20 × 109/L). The predictive nomogram achieved an AUC of 0.89 in the training set and 0.75 in the validation set. DCA demonstrated favorable clinical utility of the model.
CONCLUSIONS: We developed and validated the first nomogram for predicting DS in pediatric NHR-APL. This tool enables early risk stratification and may guide clinical decision-making to reduce early mortality.
METHODS: We conducted a multicenter retrospective analysis of 166 pediatric NHR-APL patients treated between 2011 and 2024. Clinical characteristics were compared between DS and non-DS groups. Logistic regression was used to identify independent predictors, and a nomogram was developed based on these variables. The model was evaluated using the area under the curve (AUC) and decision curve analysis (DCA).
RESULTS: Seventeen patients (10.2%) developed DS during induction. Multivariate analysis identified five independent risk factors: female sex, non-chemotherapy group, BCR subtype 3, elevated peripheral promyelocyte proportion (≥ 44%), and platelet count (≥ 20 × 109/L). The predictive nomogram achieved an AUC of 0.89 in the training set and 0.75 in the validation set. DCA demonstrated favorable clinical utility of the model.
CONCLUSIONS: We developed and validated the first nomogram for predicting DS in pediatric NHR-APL. This tool enables early risk stratification and may guide clinical decision-making to reduce early mortality.