Differential impact of CD34+ cell dose for different age groups in allogeneic hematopoietic cell transplantation for
Yiyang Qu1, Hamed Shourabizadeh1, Aravind Subramanian1
1Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada.
Allogeneic hematopoietic cell transplantation (allo-HCT) presents a potentially curative treatment for hematologic malignancies yet carries associated risks and complications. Continuous research focuses on predicting outcomes and identifying risk factors. Notably, the influence of CD34+ cell dose on overall survival (OS) has been the subject of numerous studies yielding contradictory results. We developed machine learning (ML) models to predict allo-HCT outcomes and, through the application of SHapley Additive exPlanations (SHAP), an explainable artificial intelligence (XAI) technique enabled the identification of new and clinically relevant feature-outcome relationships. In particular, we identified a clear interaction between CD34+ cell dose of peripheral blood stem cell (PBSC) grafts and patient age at allo-HCT for patients with acute leukemia. Results of multivariable analysis validated the interaction effect: in young patients with acute leukemia (aged ≤45 years), low dose of CD34+ cells (<4.3 × 106 CD34+/kg) was associated with better OS against high dose (≥7 ×106 CD34+/kg) (hazard ratio [HR], 0.38; p = 0.019), while for older patients with acute leukemia (>45 years), low CD34+ cell dose (<3.8 ×106 CD34+/kg) was associated with worse OS against high dose (≥6.1 ×106 CD34+/kg) (HR, 1.58; p = 0.033). In conclusion, our findings suggest that tailoring CD34+ cell dose by patient age may benefit patients with acute leukemia undergoing allo-HCT, while XAI showcases excellent proficiency in revealing such interactions.
Allogeneic hematopoietic cell transplantation (allo-HCT) presents a potentially curative treatment for hematologic malignancies yet carries associated risks and complications. Continuous research focuses on predicting outcomes and identifying risk factors. Notably, the influence of CD34+ cell dose on overall survival (OS) has been the subject of numerous studies yielding contradictory results. We developed machine learning (ML) models to predict allo-HCT outcomes and, through the application of SHapley Additive exPlanations (SHAP), an explainable artificial intelligence (XAI) technique enabled the identification of new and clinically relevant feature-outcome relationships. In particular, we identified a clear interaction between CD34+ cell dose of peripheral blood stem cell (PBSC) grafts and patient age at allo-HCT for patients with acute leukemia. Results of multivariable analysis validated the interaction effect: in young patients with acute leukemia (aged ≤45 years), low dose of CD34+ cells (<4.3 × 106 CD34+/kg) was associated with better OS against high dose (≥7 ×106 CD34+/kg) (hazard ratio [HR], 0.38; p = 0.019), while for older patients with acute leukemia (>45 years), low CD34+ cell dose (<3.8 ×106 CD34+/kg) was associated with worse OS against high dose (≥6.1 ×106 CD34+/kg) (HR, 1.58; p = 0.033). In conclusion, our findings suggest that tailoring CD34+ cell dose by patient age may benefit patients with acute leukemia undergoing allo-HCT, while XAI showcases excellent proficiency in revealing such interactions.
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