A tumor volume and performance status model to predict outcome prior to treatment in diffuse large B-cell lymphoma.
Membres identifiés du Cancéropôle Est :
Dr CASASNOVAS Olivier
Tous les auteurs :
Thieblemont C, Chartier L, Duhrsen U, Vitolo U, Barrington S, Zaucha JM, Vercellino L, Gomes da Silva M, Patrocinio-Carvalho I, Decazes P, Viailly PJ, Tilly H, Berriolo-Riedinger A, Casasnovas O, Hüttmann A, Ilyas H, Mikhaeel NG, Dunn JT, Cottereau AS, Schmitz C, Kostakoglu L, Paulson JN, Nielsen TG, Meignan M
Aggressive large B-cell lymphoma (LBCL) has variable outcomes. Current prognostic tools employ factors for risk stratification that inadequately identify patients at high risk of refractory disease or relapse, prior to initial treatment. A model associating two risk-factors, total metabolic tumor volume (TMTV)>220 cm3 by F18-FDG-PET/CT and performance status (PS)>=2, identified as prognostic in 301 elderly patients in the REMARC trial (NCT01122472), was validated in 2174 patients of all ages treated in two clinical trials PETAL (n=510) and GOYA (n=1315), and in real-world clinics (n=349) across Europe and United States. Three risk categories, low (no factors), intermediate (one risk-factor), and high (two risk-factors), significantly discriminated outcome in most of the series. Patients with two risk factors had a worse outcome than patients with no risk factors in the PETAL, GOYA and real-world series: progression-free survival (PFS) hazard ratio (HR)=3.32 (95% confidence interval [CI]: 2.0-5.5), HR=2.85 (95% CI: 2.11-3.84), HR=3.85 (2.5-5.9) respectively; overall survival (OS) HR=3.85 (95% CI: 2.2-6.8), HR=3.35 (95% CI: 2.34-4.77), HR= 4.61 (2.9-7.3). Patients with intermediate risk also had a significantly worse outcome than patients with no risk factors. The TMTV/ECOG-PS combination outperformed the International Prognostic Index with a positive C-Index for PFS and OS in most of series. The combination of high TMTV >220 cm3 and ECOG-PS>=2 is a simple clinical model to identify pretreatment aggressive LBCL-risk categories. This combination addresses the unmet need to better predict before treatment initiation for aggressive LBCL, those patients likely to benefit the most or not at all from therapy.
Blood Adv. 2022 08 31;: