Random survival forest to predict transplant-eligible newly diagnosed multiple myeloma outcome including FDG-PET radiomics: a combined analysis of two independent prospective European trials.

Autor: Jamet, Bastien, Morvan, Ludivine, Nanni, Cristina, Michaud, Anne-Victoire, Bailly, Clément, Chauvie, Stéphane, Moreau, Philippe, Touzeau, Cyrille, Zamagni, Elena, Bodet-Milin, Caroline, Kraeber-Bodéré, Françoise, Mateus, Diana, Carlier, Thomas
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Zdroj: European Journal of Nuclear Medicine & Molecular Imaging; Apr2021, Vol. 48 Issue 4, p1005-1015, 11p, 1 Diagram, 2 Charts, 4 Graphs
Abstrakt: Purpose: Fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) is included in the International Myeloma Working Group (IMWG) imaging guidelines for the work-up at diagnosis and the follow-up of multiple myeloma (MM) notably because it is a reliable tool as a predictor of prognosis. Nevertheless, none of the published studies focusing on the prognostic value of PET-derived features at baseline consider tumor heterogeneity, which could be of high importance in MM. The aim of this study was to evaluate the prognostic value of baseline PET-derived features in transplant-eligible newly diagnosed (TEND) MM patients enrolled in two prospective independent European randomized phase III trials using an innovative statistical random survival forest (RSF) approach. Methods: Imaging ancillary studies of IFM/DFCI2009 and EMN02/HO95 trials formed part of the present analysis (IMAJEM and EMN02/HO95, respectively). Among all patients initially enrolled in these studies, those with a positive baseline FDG-PET/CT imaging and focal bone lesions (FLs) and/or extramedullary disease (EMD) were included in the present analysis. A total of 17 image features (visual and quantitative, reflecting whole imaging characteristics) and 5 clinical/histopathological parameters were collected. The statistical analysis was conducted using two RSF approaches (train/validation + test and additional nested cross-validation) to predict progression-free survival (PFS). Results: One hundred thirty-nine patients were considered for this study. The final model based on the first RSF (train/validation + test) approach selected 3 features (treatment arm, hemoglobin, and SUVmaxBone Marrow (BM)) among the 22 involved initially, and two risk groups of patients (good and poor prognosis) could be defined with a mean hazard ratio of 4.3 ± 1.5 and a mean log-rank p value of 0.01 ± 0.01. The additional RSF (nested cross-validation) analysis highlighted the robustness of the proposed model across different splits of the dataset. Indeed, the first features selected using the train/validation + test approach remained the first ones over the folds with the nested approach. Conclusion: We proposed a new prognosis model for TEND MM patients at diagnosis based on two RSF approaches. Trial registration: IMAJEM: NCT01309334 and EMN02/HO95: NCT01134484 [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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