Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes

Bersanelli, Matteo; Travaglino, Erica; Meggendorfer, Manja; Matteuzzi, Tommaso; Sala, Claudia; Mosca, Ettore; Chiereghin, Chiara; Di Nanni, Noemi; Gnocchi, Matteo; Zampini, Matteo; Rossi, Marianna; Maggioni, Giulia; Termanini, Alberto; Angelucci, Emanuele; Bernardi, Massimo; Borin, Lorenza; Bruno, Benedetto; Bonifazi, Francesca; Santini, Valeria; Bacigalupo, Andrea; Teresa Voso, Maria; Natalie Olíva, Esther; Riva, Marta; Ubezio, Marta; Morabito, Lucio; Campagna, Alessia; Saitta, Claudia; Savevski, Victor; Giampieri, Enrico; Remondini, Daniel; Passamonti, Francesco; Ciceri, Fabio; Bolli, Niccolò; Rambaldi, Alessandro; Kern, Wolfgang; Kordasti, Shahram; Solé, Françesc; Palomo, Laura; Sanz, Guillermo; Santoro, Armando; Platzbecker, Uwe; Fenaux, Pierre; Milanesi, Luciano; Haferlach, Torsten; Castellani, Gastone; Giovanni Della Porta, Matteo

doi:10.1200/jco.20.01659

Public

Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes

Published in Journal of Clinical Oncology • Feb 4, 2021

Authors:

Matteo Bersanelli

Erica Travaglino

Manja Meggendorfer

Abstract

PURPOSE Recurrently mutated genes and chromosomal abnormalities have been identified in myelodysplastic syndromes (MDS). We aim to integrate these genomic features into disease classification and prognostication. METHODS We retrospectively enrolled 2,043 patients. Using Bayesian networks and Dirichl...

Subject

Myelodysplastic syndromes

Proportional hazards model

Medicine

Research Assistant

AI chat, annotations, notes & similar papers

Finding related papers...

Discussions

(0)

No comments yet

Be the first to share your thoughts!