Background

Tumor burden is a known negative prognostic factor in diffuse large B-cell lymphoma (DLBCL) and may influence treatment response to immunotherapy. Eosinophils and other white blood cell (WBC) types have also been associated with response outcomes in hematologic malignancies. Peripheral eosinophil counts predict efficacy of anti-CD19 CAR-T cell therapy against B-lineage non-Hodgkin lymphoma (Jia Q, et al 2021). However, it remains unclear how the tumor burden status and pre lymphodepletion eosinophils value correlate with response outcomes. This study explores the interaction between baseline WBC subtypes, particularly eosinophils, and tumor burden in predicting best overall response (BOR) and progression-free survival (PFS) in DLBCL patients undergoing lymphodepleting chemotherapy (LD) prior to anti-CD19 CAR-T cell therapy.

Methods

We retrospectively analyzed data from 542 DLBCL patients enrolled in clinical trials. Patients were included if they had recorded tumor burden (sum of longest diameters at screening), WBC measurements within 5 days prior to LD, and defined BOR and PFS outcomes. Patients were stratified into high vs. low tumor burden groups using thresholds of greater or lesser than 7 cm for the sum of tumor longest diameters, respectively. Pre-LD WBC values (monocytes, basophils, eosinophils, neutrophils, and lymphocytes) were categorized as high or low based on percentile thresholds (e.g., eosinophils: 30th percentile, neutrophils: 50th percentile). For BOR, contingency analyses were performed using Fisher's exact test, grouping by WBC category (e.g. high vs low Eosinophils) and complete response vs. other responses, or response (complete response and partial response) vs no response (progressive disease, stable disease). PFS was evaluated using univariate Kaplan-Meier (K-M) analyses with the log-rank test for statistical significance and multivariate Cox Proportional Hazard (CPH) models with the Wald test. For the CPH models we used the pre-LD eosinophils, neutrophils, basophils, the sum of longest tumor diameters, and the number of lines of prior treatment for the entire cohort, and then used only pre-LD WBC values grouped high vs low tumor burden.

Results

For the multivariate models on the entire cohort, the tumor burden value was the strongest predictor of PFS (p<0.005). Grouping by high vs low tumor burden, multivariate models including eosinophils, basophils, neutrophils and monocytes showed eosinophils to be correlated with improved PFS in the high tumor burden group (p<0.05). In univariate analyses done separately on the high vs low tumor burden groups, high pre-LD eosinophil levels were significantly associated with improved PFS among patients with high tumor burden (eosinophils: p<0.01). Within the high tumor burden group, high eosinophils levels were associated with superior BOR, defined as either complete response vs. all other responses (p<0.05), or response (complete or partial responses) vs. no response (stable disease or progressive disease) (p<0.05). In both cases, the odds ratio was less than 1 (0.59 and 0.56, respectively), indicating that patients with high pre-LD eosinophil counts have higher odds of responding compared to those with low eosinophil counts. No significant associations were consistently observed for any other WBC lineages across the analyses conducted.

Conclusions

Among DLBCL patients with high tumor burden, elevated eosinophil levels prior to LD for CAR-T cell therapy are associated with improved response rates and PFS, suggesting eosinophils may serve as a predictive biomarker in this high-risk population. These findings underscore the added value of pre-LD eosinophil levels as a complementary biomarker to tumor burden, offering a more nuanced approach to predicting treatment outcomes and informing CAR-T stratification. Further studies are needed to explore whether a functional relationship between eosinophils and CAR-T cell therapeutics exists.

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2025
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