1. 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
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Diana Mateus, Cristina Nanni, Ludivine Morvan, Thomas Carlier, Caroline Bodet-Milin, Clément Bailly, Stephane Chauvie, Elena Zamagni, Bastien Jamet, Françoise Kraeber-Bodéré, Cyrille Touzeau, Anne-Victoire Michaud, Philippe Moreau, Département de Médecine Nucléaire [CHU Nantes], Centre hospitalier universitaire de Nantes (CHU Nantes), Nuclear Oncology (CRCINA-ÉQUIPE 13), Centre de Recherche en Cancérologie et Immunologie Nantes-Angers (CRCINA), Université d'Angers (UA)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre hospitalier universitaire de Nantes (CHU Nantes)-Université d'Angers (UA)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre hospitalier universitaire de Nantes (CHU Nantes), Laboratoire des Sciences du Numérique de Nantes (LS2N), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Policlinico S. Orsola-malpighi, Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO)-Servizio sanitario regionale Emilia-Romagna, Santa Croce e Carle Hospital [Cuneo, Italy], Service d'Hématologie [Nantes], University of Bologna/Università di Bologna, Service de médecine nucléaire [Saint-Herblain], Centre René Gauducheau-Institut Régional du Cancer Nantes-Atlantique (IRCNA)-Institut de Cancérologie de l'Ouest [Angers/Nantes] (UNICANCER/ICO), UNICANCER-UNICANCER, Bernardo, Elizabeth, Jamet B., Morvan L., Nanni C., Michaud A.-V., Bailly C., Chauvie S., Moreau P., Touzeau C., Zamagni E., Bodet-Milin C., Kraeber-Bodere F., Mateus D., Carlier T., Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes)-Centre National de la Recherche Scientifique (CNRS)-Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes)-Centre National de la Recherche Scientifique (CNRS)-Université d'Angers (UA), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), University of Bologna, Centre René Gauducheau-Institut de Cancérologie de l'Ouest [Angers/Nantes] (UNICANCER/ICO), and UNICANCER-UNICANCER-Institut Régional du Cancer Nantes-Atlantique (IRCNA)
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medicine.medical_specialty ,Poor prognosis ,[SDV.CAN]Life Sciences [q-bio]/Cancer ,Newly diagnosed ,Tumor heterogeneity ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,Risk groups ,Radiomics ,[SDV.CAN] Life Sciences [q-bio]/Cancer ,Fluorodeoxyglucose F18 ,Multiple myeloma ,Positron Emission Tomography Computed Tomography ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Prospective Studies ,business.industry ,Hazard ratio ,Random survival forest ,General Medicine ,Prognosis ,medicine.disease ,FDG-PET/CT ,3. Good health ,030220 oncology & carcinogenesis ,Radiology ,Radiopharmaceuticals ,Radiomic ,business ,Prognostic value ,Treatment Arm - Abstract
International audience; 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.
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- 2021