Wang Qing Ya, Han Yi Fan, Li Yu Han, Wang Qing Yun, Zhu Jin Ye, Dong Yu Jun, Liu Wei, Han Na, Ren Han Yun, Li Yuan
Department of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Department of Gastroenterology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
J Adv Res. 2025 Jul;73:671-679. doi: 10.1016/j.jare.2024.09.014. Epub 2024 Sep 18.
This study aims to develop a robust predictive model for survival in AML patients undergoing allo-HSCT.
It was performed a retrospective analysis of 336 AML patients who underwent allo-HSCT at Peking University First Hospital between September 2003 and March 2023. Univariable and multivariable Cox regression analyses were conducted to determine hazard ratios (HR) for overall survival. A predictive model was developed based on multivariable analysis results. Internal validation was carried out through bootstrap resampling, and the model's performance was assessed using the Concordance Index (C-index), Receiver Operating Characteristics (ROC) curve, calibration plots, and Decision Curve Analysis (DCA).
Our prognostic model, which includes age, disease stage, donor/recipient gender, mononuclear cell counts, and the Hematopoietic Cell Transplantation Comorbidity Index (HCT-CI), effectively stratified patients into low-risk and high-risk groups. The two groups showed significant differences in overall survival (P<0.0001), disease-free survival (P<0.0001), non-relapse mortality (NRM) (P<0.0001), and relapse rates (P=0.08). The model achieved a C-index of 0.71. Calibration plots and DCA confirmed strong alignment between predicted and observed outcomes. Subgroup analysis revealed that overall survival was significantly lower in the high-risk group compared to the low-risk group in both measurable residual disease (MRD) negative and MRD positive subgroups (P=0.015 for both).
The developed prognostic model, which integrates comprehensive disease and patient characteristics, enhances risk stratification for AML patients undergoing allo-HSCT. This model effectively stratifies risk in both MRD-negative and MRD-positive subgroups and may facilitate more informed MRD-based treatment decisions.
本研究旨在为接受异基因造血干细胞移植(allo-HSCT)的急性髓系白血病(AML)患者开发一种可靠的生存预测模型。
对2003年9月至2023年3月期间在北京大学第一医院接受allo-HSCT的336例AML患者进行回顾性分析。进行单变量和多变量Cox回归分析以确定总生存的风险比(HR)。基于多变量分析结果开发预测模型。通过自助重采样进行内部验证,并使用一致性指数(C指数)、受试者工作特征(ROC)曲线、校准图和决策曲线分析(DCA)评估模型性能。
我们的预后模型包括年龄、疾病分期、供体/受体性别、单核细胞计数和造血细胞移植合并症指数(HCT-CI),有效地将患者分为低风险和高风险组。两组在总生存(P<0.0001)、无病生存(P<0.0001)、非复发死亡率(NRM)(P<0.0001)和复发率(P=0.08)方面存在显著差异。该模型的C指数为0.71。校准图和DCA证实预测结果与观察结果高度一致。亚组分析显示,在可测量残留病(MRD)阴性和MRD阳性亚组中,高风险组的总生存均显著低于低风险组(两者P均=0.015)。
所开发的预后模型整合了全面的疾病和患者特征,增强了接受allo-HSCT的AML患者的风险分层。该模型在MRD阴性和MRD阳性亚组中均能有效分层风险,并可能有助于基于MRD做出更明智的治疗决策。