Mathieu Nessim Toledano1,2, P Desbordes3, A Banjar4,3, I Gardin4,3, P Vera4,3, P Ruminy5, F Jardin5,6, H Tilly5,6, S Becker4,3. 1. Nuclear Medicine Department, Henri Becquerel Cancer Centre and Rouen University Hospital, Rouen, France. mathieu.toledano@gmail.com. 2. QuantIF-LITIS (EA 4108-FR CNRS 3638), Faculty of Medicine, University of Rouen, Rouen, France. mathieu.toledano@gmail.com. 3. QuantIF-LITIS (EA 4108-FR CNRS 3638), Faculty of Medicine, University of Rouen, Rouen, France. 4. Nuclear Medicine Department, Henri Becquerel Cancer Centre and Rouen University Hospital, Rouen, France. 5. INSERM U918, Centre Henri Becquerel, Rouen, France. 6. Hematology Department, Centre Henri Becquerel, Rouen, France.
Abstract
PURPOSE: This study evaluated the predictive significance of total metabolic tumour volume (TMTV) measured on baseline FDG PET/CT and its value in addition to gene expression profiling using a new method of gene analysis (rapid reverse transcriptase multiplex ligation-dependent probe amplification assay, RT-MLPA) in patients with diffuse large B-cell lymphoma treated with R-CHOP or R-CHOP-like chemotherapies. METHODS: The analysis included 114 patients. TMTV was measured using a 41% SUVmax threshold and tumours were classified into GCB or ABC subtypes according to the RT-MLPA assay. RESULTS: The median follow-up was 40 months. the 5-year progression-free survival (PFS) was 54% and the 5-year overall survival (OS) was 62%. The optimal TMTV cut-off value was 261 cm3. In 59 patients with a high TMTV the 5-year PFS and OS were 37% and 39%, respectively, in comparison with 72% and 83%, respectively, in 55 patients with a low TMTV (p = 0.0002 for PFS, p < 0.0001 for OS). ABC status was significantly associated with a worse prognosis. TMTV combined with molecular data identified three groups with very different outcomes: (1) patients with a low TMTV whatever their phenotype (n = 55), (2) patients with a high TMTV and GCB phenotype (n = 33), and (3) patients with a high TMTV and ABC phenotype (n = 26). In the three groups, 5-year PFS rates were 72%, 51% and 17% (p < 0.0001), and 5-year OS rates were 83%, 55% and 17% (p < 0.0001), respectively. In multivariate analysis, TMTV, ABC/GCB phenotype and International Prognostic Index were independent predictive factors for both PFS and OS (p < 0.05 for both). CONCLUSIONS: This integrated risk model could lead to more accurate selection of patients that would allow better individualization of therapy.
PURPOSE: This study evaluated the predictive significance of total metabolic tumour volume (TMTV) measured on baseline FDG PET/CT and its value in addition to gene expression profiling using a new method of gene analysis (rapid reverse transcriptase multiplex ligation-dependent probe amplification assay, RT-MLPA) in patients with diffuse large B-cell lymphoma treated with R-CHOP or R-CHOP-like chemotherapies. METHODS: The analysis included 114 patients. TMTV was measured using a 41% SUVmax threshold and tumours were classified into GCB or ABC subtypes according to the RT-MLPA assay. RESULTS: The median follow-up was 40 months. the 5-year progression-free survival (PFS) was 54% and the 5-year overall survival (OS) was 62%. The optimal TMTV cut-off value was 261 cm3. In 59 patients with a high TMTV the 5-year PFS and OS were 37% and 39%, respectively, in comparison with 72% and 83%, respectively, in 55 patients with a low TMTV (p = 0.0002 for PFS, p < 0.0001 for OS). ABC status was significantly associated with a worse prognosis. TMTV combined with molecular data identified three groups with very different outcomes: (1) patients with a low TMTV whatever their phenotype (n = 55), (2) patients with a high TMTV and GCB phenotype (n = 33), and (3) patients with a high TMTV and ABC phenotype (n = 26). In the three groups, 5-year PFS rates were 72%, 51% and 17% (p < 0.0001), and 5-year OS rates were 83%, 55% and 17% (p < 0.0001), respectively. In multivariate analysis, TMTV, ABC/GCB phenotype and International Prognostic Index were independent predictive factors for both PFS and OS (p < 0.05 for both). CONCLUSIONS: This integrated risk model could lead to more accurate selection of patients that would allow better individualization of therapy.
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