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Updated: Jan 11, 2026
![Dynamic Imaging of Chimeric Antigen Receptor T Cells with [18F]Tetrafluoroborate Positron Emission Tomography/Computed Tomography](/_next/image?url=https%3A%2F%2Fcloudfront.jove.com%2FCDNSource%2Fteasers%2F62334.jpg&w=3840&q=50)
Dynamic Imaging of Chimeric Antigen Receptor T Cells with [18F]Tetrafluoroborate Positron Emission Tomography/Computed Tomography
Published on: February 17, 2022
Bone marrow blasts- and modified EASIX-guided risk stratification for coagulopathy and outcomes after CAR-T therapy
Yingying Li1, Jiachen Liu1, Lili Luo1
1Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China; Hubei Clinical and Research Center of Thrombosis and Haemostasis, Wuhan, 430022, China.
Background:
Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of relapsed/refractory (r/r) B-cell acute lymphoblastic leukemia (B-ALL). While CAR-T-associated coagulopathy (CARAC) remains a critical complication, significantly increasing the risk of hemorrhage and disseminated intravascular coagulation (DIC).
Aims:
To develop an effective CARAC risk stratification and outcome prediction model.
Methods:
This multicenter retrospective study enrolled r/r B-ALL patients who received CD19 CAR-T therapy between January 2016 and July 2025. Machine learning, logistic regression and cutoff values were utilized to select key variables and develop predictive models. Model performance and clinical applicability were evaluated by receiver operating characteristic, calibration, and clinical decision curves. Survival analyses evaluated the impact of CARAC severity on overall survival (OS) and progression-free survival (PFS) and to validate the prognostic value of the prediction model.
Results:
Bone marrow (BM) blasts and the modified endothelial activation and stress index (mEASIX) were independent predictors for CARAC. Patients with mEASIX<4.0 were identified as low-risk CARAC. For patients with mEASIX≥4.0, CARAC was stratified by BM blast percentage (blast%). Blast% between 10 % and 44 % indicated high-risk CARAC-nonDIC, and a blast% ≥ 44 % indicated high-risk CARAC-DIC. Moreover, compared to non-CARAC patients, CARAC patients had inferior OS (hazard ratio [HR]: 2.62, p = 0.002) and PFS (HR: 2.11, p = 0.002). The stratified prediction model revealed progressively worse OS and PFS from low-risk CARAC patients to high-risk CARAC-nonDIC, with high-risk CARAC-DIC patients demonstrating the most unfavorable outcomes.
Conclusions:
An effective CARAC risk prediction and stratification model was established. High-risk CARAC patients, particularly CARAC-DIC, were associated with significantly worse outcomes.
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