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Personalized baseline and residual TMTV influence treatment response and outcomes in relapsed/refractory lymphomas:
Solène Malmon1, Olivier Casasnovas2, Marguerite Fournier3
1Pixilib SAS, Toulouse, France.
Purpose:
Total metabolic tumor volume (TMTV) at baseline becomes a key biomarker in several lymphoma subtypes. Variability in segmentation methods such as 41%SUVmax and SUVmax > 4 has limited its clinical application. Additionally, immune-checkpoint-inhibitors introduced challenges in response assessment due to pseudoprogression, complicating the use of traditional metrics. This study investigates the prognostic impact of baseline- and residual-TMTV and introduces a novel personalized-liver-based-threshold (pTMTVliver) to enhance precision in patient stratification.
Methods:
We analyzed 91 patients with relapsed/refractory diffuse-large-B-cell lymphoma and follicular lymphoma from the GATA trial, comparing patient's outcome according to three segmentation methods: TMTV41%, TMTV4, and pTMTVliver. pTMTVliver used a threshold of 200%SUVmeanliver aligning with 125%SUVmaxliver to enhance standardization and reduce variability.
Results:
Baseline-TMTV significantly influenced prognosis with higher TMTV correlating with shorter PFS and OS (p < 0.0001 for all methods). Residual-TMTV, particularly with pTMTVliver and TMTV4, stratified no-CMR patients with the lowest predictive errors and better predictive accuracy compared to TMTV41% Multivariate analyses confirmed residual-pTMTVliver as superior for prognostic performance for PFS (HR:5.10; C-index:0.724) and OS (HR:4.00; C-index:0.853) compared to TMTV4 and Deauville Score (DS). The DS alone did not fully capture the heterogeneity of outcomes of DS4-5 patients.
Conclusion:
Baseline- and residual-TMTV strongly influence prognosis and response in lymphoma patients. The novel personalized pTMTVliver method offers improved accuracy of patient stratification, particularly for those with DS4-5, providing more reliable risk assessment. Larger cohorts are needed to validate these findings and optimize residual-TMTV-based clinical applications.
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