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Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results.
MacInnis, Robert J; Liao, Yuyan; Knight, Julia A; Milne, Roger L; Whittemore, Alice S; Chung, Wendy K; Leoce, Nicole; Buchsbaum, Richard; Zeinomar, Nur; Dite, Gillian S; Southey, Melissa C; Goldgar, David; Giles, Graham G; McLachlan, Sue-Anne; Weideman, Prue C; Nesci, Stephanie; Friedlander, Michael L; Glendon, Gord; Andrulis, Irene L; John, Esther M; Daly, Mary B; Buys, Saundra S; Phillips, Kelly Anne; Hopper, John L; Terry, Mary Beth.
Afiliación
  • MacInnis RJ; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
  • Liao Y; Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
  • Knight JA; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York.
  • Milne RL; Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
  • Whittemore AS; Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
  • Chung WK; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
  • Leoce N; Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
  • Buchsbaum R; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
  • Zeinomar N; Departments of Health Research and Policy and Biomedical Data Science, Stanford University School of Medicine, Stanford.
  • Dite GS; Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York.
  • Southey MC; Departments of Pediatrics and Medicine, Columbia University, New York.
  • Goldgar D; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York.
  • Giles GG; Department of Biostatistics, Mailman School of Public Health, Columbia University, New York.
  • McLachlan SA; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York.
  • Weideman PC; Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
  • Nesci S; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
  • Friedlander ML; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
  • Glendon G; Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia.
  • Andrulis IL; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
  • John EM; Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
  • Daly MB; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Buys SS; Department of Medicine, St Vincent's Hospital, The University of Melbourne, Parkville, Victoria, Australia.
  • Phillips KA; Department of Medical Oncology, St Vincent's Hospital, Fitzroy, Victoria, Australia.
  • Hopper JL; Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
  • Terry MB; Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
J Natl Cancer Inst ; 112(4): 418-422, 2020 04 01.
Article en En | MEDLINE | ID: mdl-31584660
The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Modelos Estadísticos Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Middle aged País/Región como asunto: America do norte / Oceania Idioma: En Revista: J Natl Cancer Inst Año: 2020 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Modelos Estadísticos Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Middle aged País/Región como asunto: America do norte / Oceania Idioma: En Revista: J Natl Cancer Inst Año: 2020 Tipo del documento: Article País de afiliación: Australia