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Title: Validating a breast cancer score in Spanish women. The MCC-Spain study.
Authors: Dierssen-Sotos, Trinidad
Gómez-Acebo, Inés
Palazuelos, Camilo
Fernández-Navarro, Pablo
Altzibar, Jone M
González-Donquiles, Carmen
Ardanaz, Eva
Bustamante, Mariona
Alonso-Molero, Jessica
Vidal, Carmen
Bayo-Calero, Juan
Tardón, Adonina
Salas, Dolores
Marcos-Gragera, Rafael
Moreno, Víctor
Rodriguez-Cundin, Paz
Castaño-Vinyals, Gemma
Ederra, María
Vilorio-Marqués, Laura
Amiano, Pilar
Pérez-Gómez, Beatriz
Aragonés, Nuria
Kogevinas, Manolis
Pollán, Marina
Llorca, Javier
metadata.dc.subject.mesh: Area Under Curve
Breast Neoplasms
Case-Control Studies
Genetic Predisposition to Disease
Genetic Testing
Logistic Models
Mass Screening
Models, Statistical
Polymorphism, Single Nucleotide
ROC Curve
Reproducibility of Results
Risk Assessment
Risk Factors
White People
Issue Date: 14-Feb-2018
Abstract: A breast-risk score, published in 2016, was developed in white-American women using 92 genetic variants (GRS92), modifiable and non-modifiable risk factors. With the aim of validating the score in the Spanish population, 1,732 breast cancer cases and 1,910 controls were studied. The GRS92, modifiable and non-modifiable risk factor scores were estimated via logistic regression. SNPs without available genotyping were simulated as in the aforementioned 2016 study. The full model score was obtained by combining GRS92, modifiable and non-modifiable risk factor scores. Score performances were tested via the area under the ROC curve (AUROC), net reclassification index (NRI) and integrated discrimination improvement (IDI). Compared with non-modifiable and modifiable factor scores, GRS92 had higher discrimination power (AUROC: 0.6195, 0.5885 and 0.5214, respectively). Adding the non-modifiable factor score to GRS92 improved patient classification by 23.6% (NRI = 0.236), while the modifiable factor score only improved it by 7.2%. The full model AUROC reached 0.6244. A simulation study showed the ability of the full model for identifying women at high risk for breast cancer. In conclusion, a model combining genetic and risk factors can be used for stratifying women by their breast cancer risk, which can be applied to individualizing genetic counseling and screening recommendations.
metadata.dc.identifier.doi: 10.1038/s41598-018-20832-0
Appears in Collections:Producción 2020

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