Modified EASIX scores predict severe CRS/ICANS in patients with acute myeloid leukemia following CLL1 CAR-T cell therapy.

Chimeric antigen receptor T (CAR-T) cell therapy targeting CLL1 has been considered a potent weapon for patients with acute myeloid leukemia (AML). This study aims to evaluate the efficacy and toxicity of CLL1 CAR-T cell therapy in a larger cohort, with particular attention to cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Among the 32 patients assessed for efficacy, complete remission occurred in 71.88% (23/32) of cases and undetectable minimal residual disease in 14 patients. The CRS developed in all patients, with 8 individuals experiencing ICANS. Severe CRS and ICANS were observed in 11 and 2 patients, respectively. Furthermore, the Endothelial Activation and Stress Index (EASIX) and its derivatives measured before and after CLL1 CAR-T cell infusion were employed for predicting the severe complications. Significant differences were observed in EASIX scores on the day before lymphodepletion (Day BL, P = 0.023), −1 (P < 0.001), +1 (P < 0.001), and +3(P = 0.014); sEASIX scores on Day BL (P = 0.007), −1 (P < 0.001), +1 (P < 0.001), and +3 (P < 0.001); and mEASIX score on Day −1 (P = 0.004) between patients with mild and severe CRS/ICANS. Additionally, there was a significant difference in mEASIX scores between responders and non-responders on Day BL (P = 0.004) and Day −1 (P = 0.044). Our findings indicate that pre- and post-infusion assessments of EASIX/mEASIX/sEASIX scores serve as reliable prognostic indicators for severe CRS/ICANS and treatment response following CLL1 CAR-T cell therapy, which can assist physicians in implementing preemptive treatment strategies for potential severe complications and screening patients who are suitable candidates for CLL1 CAR-T cell therapy. EASIX/mEASIX/sEASIX scores serve as reliable prognostic indicators for severe CRS/ICANS following CLL1 CAR-T cell therapy. The preinfusion mEASIX scores of CLL1 CAR-T cells can effectively predict treatment response. [ABSTRACT FROM AUTHOR]