Erschienen in:
17.01.2018 | Original Article
Combination of baseline FDG PET/CT total metabolic tumour volume and gene expression profile have a robust predictive value in patients with diffuse large B-cell lymphoma
verfasst von:
Mathieu Nessim Toledano, P. Desbordes, A. Banjar, I. Gardin, P. Vera, P. Ruminy, F. Jardin, H. Tilly, S. Becker
Erschienen in:
European Journal of Nuclear Medicine and Molecular Imaging
|
Ausgabe 5/2018
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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.