Frontiers in Oncology (Sep 2022)
Lymphoma tumor burden before chimeric antigen receptor T-Cell treatment: RECIL vs. Lugano vs. metabolic tumor assessment
Abstract
PurposeHigh 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 methodsIn 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 (TBRECIL), sum of product of perpendicular diameters (TBLugano), and metabolic tumor volume (TBMTV). Correlation statistics were used for comparison. Proportional Cox regression analysis studied the association of TB metrics with PFS and OS.Results34 consecutive patients were included (median age: 67 years, 41% female) with total median baseline TBRECIL of 12.5 cm, TBLugano of 4,030 mm2 and TBMTV of 330 mL. The correlation of TBRECIL and TBLugano with TBMTV was strong (ρ=0.744, p<0.001 and ρ=0.741, p<0.001), with lowest correlation for extranodal TBRECIL with TBMTV (ρ=0.660, p<0.001). Stratification of PFS was strongest by total TBMTV>50% (HR=2.915, p=0.042), whereas total TBRECIL>50% and total TBLugano>50% were not significant (both p>0.05). None of the total TB metrics were associated with OS (all p>0.05).ConclusionPre-CART TB metrics vary significantly based on the assessment method, impacting their association with survival outcomes. The correlation between TBRECIL, TBLugano and TBMTV 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.
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