Integrating genetic polymorphisms and clinical data to develop predictive models for skin toxicity in breast cancer radiation therapy

Background: We aim to develop and validate predictive models for acute and late skin toxicity in breast cancer (BC) patients undergoing radiation therapy (RT). Models incorporate a genetic profile—comprising candidate single nucleotide polymorphisms (SNPs) in non-coding RNAs and previously reported...

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Principais autores:	Ester Aguado-Flor, Victoria M. Reyes, Víctor Navarro, Meritxell Mollà, Miguel E. Aguado-Barrera, Manuel Altabas, David Azria, Adinda Baten, Celine Bourgier, Renée Bultijnck, Jenny Chang-Claude, Maria Carmen De Santis, Alison M. Dunning, Laura Duran-Lozano, Rebecca M. Elliott, Marie-Pierre Farcy Jacquet, Carlotta Giandini, Alexandra Giraldo, Sheryl Green, Maarten Lambrecht, Carlos Lopez-Pleguezuelos, Chris Monten, Tiziana Rancati, Tim Rattay, Barry S. Rosenstein, Dirk De Ruysscher, Orland Diez, Petra Seibold, Elena Sperk, R Paul Symonds, Hilary Stobart, Ana Vega, Liv Veldeman, Guillermo Villacampa, Adam J. Webb, Caroline Weltens, Paolo Zunino, Christopher J. Talbot, Catharine M. West, Jordi Giralt, Sara Gutiérrez-Enríquez
格式:	Artigo
語言:	Inglês
出版:	Elsevier 2025-08-01
叢編:	Breast
主題:	Breast cancer Radiation therapy-induced side-effects Non-coding RNA polymorphisms Literature candidate polymorphisms' validation Predictive models
在線閱讀:	http://www.sciencedirect.com/science/article/pii/S0960977625005235
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