A novel prognostic scoring system for AML patients undergoing allogeneic hematopoietic stem cell transplantation with real world validation

一种用于接受异基因造血干细胞移植的急性髓系白血病患者的新型预后评分系统及其真实世界验证

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Abstract

OBJECTIVES: This study aims to develop a robust predictive model for survival in AML patients undergoing allo-HSCT. METHODS: 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). RESULTS: 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). CONCLUSION: 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.

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