Lymphoma tumor burden before chimeric antigen receptor T-Cell treatment: RECIL vs. Lugano vs. metabolic tumor assessment

PURPOSE: High tumor burden has emerged as a negative predictor of efficacy in chimeric antigen receptor T-cell therapy (CART) in patients with refractory or relapsed large B-cell lymphoma. This study analyzed the deviation among imaging-based tumor burden (TB) metrics and their association with progression-free (PFS) and overall survival (OS). MATERIALS AND METHODS: In this single-center observational study, we included all consecutively treated patients receiving CD19 CART with available baseline PET-CT imaging. Imaging-based TB was determined based on response evaluation criteria in lymphoma (RECIL), the Lugano criteria, and metabolic tumor volume. Total, nodal and extranodal TB were represented, according to the respective criteria, by sum of longest diameters (TB(RECIL)), sum of product of perpendicular diameters (TB(Lugano)), and metabolic tumor volume (TB(MTV)). Correlation statistics were used for comparison. Proportional Cox regression analysis studied the association of TB metrics with PFS and OS. RESULTS: 34 consecutive patients were included (median age: 67 years, 41% female) with total median baseline TB(RECIL) of 12.5 cm, TB(Lugano) of 4,030 mm(2) and TB(MTV) of 330 mL. The correlation of TB(RECIL) and TB(Lugano) with TB(MTV) was strong (ρ=0.744, p<0.001 and ρ=0.741, p<0.001), with lowest correlation for extranodal TB(RECIL) with TB(MTV) (ρ=0.660, p<0.001). Stratification of PFS was strongest by total TB(MTV>50%) (HR=2.915, p=0.042), whereas total TB(RECIL>50%) and total TB(Lugano>50%) were not significant (both p>0.05). None of the total TB metrics were associated with OS (all p>0.05). CONCLUSION: Pre-CART TB metrics vary significantly based on the assessment method, impacting their association with survival outcomes. The correlation between TB(RECIL), TB(Lugano) and TB(MTV) was influenced by disease phenotype and prior bridging therapy. TB method of assessment must be considered when interpreting the impact of TB on outcomes in clinical trials. Considering the heterogeneity, our results argue for standardization and harmonization across centers.