TRANSPL CELL THER

Background: Early cardiac events (ECE) are a recognized cause of morbidity and mortality after allogeneic hematopoietic cell transplantation (allo-HCT), especially with the widespread use of post-transplant cyclophosphamide (PTCy) for graft-versus-host disease (GVHD) prophylaxis. Identifying patients at risk for ECE is crucial to optimize preventive strategies and improve outcomes.

Objectives: To validate the predictive performance of the CARE-BMT score for identifying patients at risk of ECE after allo-HCT and to determine whether incorporating PTCy exposure enhances its prognostic value.

Study design: A retrospective cohort study including 593 adult patients who underwent allo-HCT between 2011 and 2023 at a single institution. ECE was defined as any new cardiac event within 100 days post-HCT. The CARE-BMT score-based on age, race, cardiac comorbidities, serum creatinine, triglyceride levels, and prior anthracycline exposure-was applied to stratify patients into intermediate- and high-risk groups. A modified-CARE-BMT score was developed by adding two points for standard-dose PTCy exposure. Survival analyses, cumulative incidence functions, and multivariate regression models were used to assess associations.

Results: ECE occurred in 47 patients (7.9%), with a median onset at 21 days post-HCT, and was associated with inferior one-year overall survival (48.6% vs. 75.0%, p<0.001). The CARE-BMT score stratified patients into intermediate- and high-risk groups with Day +100 ECE incidences of 5.8% and 11.2%, respectively (p=0.033). Standard-dose PTCy (50 mg/kg/day) was independently associated with increased ECE risk (p=0.014). The modified-CARE-BMT score stratified patients into low-, intermediate-, and high-risk groups with respective ECE incidences of 4.5%, 9.5%, and 12.7% (p=0.037). EASIX trajectories further supported the stratification capability of the modified model.

Conclusions: The CARE-BMT score effectively predicts early cardiac events in allo-HCT recipients. Incorporating PTCy exposure into a modified risk model enhances its discriminatory power, allowing improved identification of high-risk patients who may benefit from tailored cardioprotective interventions and monitoring strategies.