A novel prognostic scoring system for AML patients undergoing allogeneic hematopoietic stem cell transplantation with real world validation.
J Adv Res
; 2024 Sep 18.
Article
in En
| MEDLINE
| ID: mdl-39299605
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.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
J Adv Res
Year:
2024
Document type:
Article
Affiliation country:
Country of publication: