Validation of a breast cancer risk prediction model based on the key risk factors: family history, mammographic density and polygenic risk.

Allman, Richard; Mu, Yi; Dite, Gillian S; Spaeth, Erika; Hopper, John L; Rosner, Bernard A

Allman, Richard; Mu, Yi; Dite, Gillian S; Spaeth, Erika; Hopper, John L; Rosner, Bernard A.

Afiliación

Allman R; Genetic Technologies Limited, 60-66 Hanover St, Fitzroy, VIC, 3065, Australia. Richard.allman@gtglabs.com.
Mu Y; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Dite GS; Genetic Technologies Limited, 60-66 Hanover St, Fitzroy, VIC, 3065, Australia.
Spaeth E; Phenogen Sciences Inc, Charlotte, NC, USA.
Hopper JL; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.
Rosner BA; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Breast Cancer Res Treat ; 198(2): 335-347, 2023 Apr.

Article en En | MEDLINE | ID: mdl-36749458

Asunto(s)

Densidad de la Mama; Neoplasias de la Mama; Humanos; Femenino; Medición de Riesgo; Neoplasias de la Mama/diagnóstico por imagen; Neoplasias de la Mama/epidemiología; Neoplasias de la Mama/genética; Factores de Riesgo; Curva ROC; Modelos Estadísticos

Palabras clave

Mammographic density; Polygenic risk; Risk prediction model

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Densidad de la Mama Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Breast Cancer Res Treat Año: 2023 Tipo del documento: Article País de afiliación: Australia

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