The Burden of Breast Cancer Predisposition Variants Across The Age Spectrum Among 10 000 Patients

BACKGROUND/OBJECTIVES Women diagnosed with breast cancer (BC) at an older age are less likely to undergo genetic cancer risk assessment and genetic testing since the guidelines and referrals are biased toward earlier age at diagnosis. Thus, we determined the prevalence and type of pathogenic cancer...

Full description

Saved in:

Bibliographic Details
Published in:	Journal of the American Geriatrics Society (JAGS) Vol. 67; no. 5; pp. 884 - 888
Main Authors:	Chavarri‐Guerra, Yanin, Hendricks, Carolyn B., Brown, Sandra, Marcum, Catherine, Hander, Mary, Segota, Zdenka E., Hake, Chris, Sand, Sharon, Slavin, Thomas P., Hurria, Arti, Soto‐Perez‐de‐Celis, Enrique, Nehoray, Bita, Blankstein, Kenneth B., Blazer, Kathleen R., Weitzel, Jeffrey N.
Format:	Journal Article
Language:	English
Published:	Hoboken, USA John Wiley & Sons, Inc 01-05-2019 Wiley Subscription Services, Inc
Subjects:	Age Age Distribution Age Factors Aged Biomarkers, Tumor - genetics Biomarkers, Tumor - metabolism BRCA1 protein BRCA2 protein Breast cancer Breast Neoplasms - diagnosis Breast Neoplasms - epidemiology Breast Neoplasms - genetics Diagnosis Female Follow-Up Studies Genes Genetic Markers - genetics Genetic Predisposition to Disease Genetic screening Genetic Testing genetics Genomics Geriatric Assessment - methods Humans Latin America - epidemiology Morbidity - trends Older people older women Prospective Studies Registries Risk assessment Risk Assessment - methods United States - epidemiology United States Latin America breast cancer genetics older women
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	BACKGROUND/OBJECTIVES Women diagnosed with breast cancer (BC) at an older age are less likely to undergo genetic cancer risk assessment and genetic testing since the guidelines and referrals are biased toward earlier age at diagnosis. Thus, we determined the prevalence and type of pathogenic cancer predisposition variants among women with a history of BC diagnosed at the age of 65 years or older vs younger than 65 years. DESIGN Prospective registration cohort. SETTING The Clinical Cancer Genomics Community Research Network, including 40 community‐based clinics in the United States and 5 in Latin America. PARTICIPANTS Women with BC and genetic testing results. MEASUREMENTS Sociodemographic characteristics, clinical variables, and genetic profiles were compared between women aged 65 years and older and those younger than 65 years at BC diagnosis. RESULTS Among 588 women diagnosed with BC and aged 65 years and older and 9412 diagnosed at younger than 65 years, BC‐associated pathogenic variants (PVs) were detected in 5.6% of those aged 65 years and older (n = 33) and 14.2% of those younger than 65 years (n = 1340) (P < .01). PVs in high‐risk genes (eg, BRCA1 and BRCA2) represented 81.1% of carriers among women aged 65 years and older (n = 27) and 93.1% of those younger than 65 years (n = 1248) (P = .01). BRCA2 PVs represented 42.4% of high‐risk gene findings for those aged 65 years and older, whereas BRCA1 PVs were most common among carriers younger than 65 years (49.7%). PVs (n = 7) in moderate‐risk genes represented 21.2% for carriers aged 65 years and older and 7.3% of those younger than 65 years (n = 98; P < .01). CHEK2 PVs were the most common moderate‐risk gene finding in both groups. CONCLUSION Clinically actionable BC susceptibility PVs, particularly in BRCA2 and CHEK2, were relatively prevalent among older women undergoing genetic testing. The significant burden of PVs for older women with BC provides a critical reminder to recognize the full spectrum of eligibility and provide genetic testing for older women, rather than exclusion based on chronological age alone. J Am Geriatr Soc 67:884–888, 2019.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Mary Hander: Patient accrual; Data interpretation; Writing- review & editing. Sandra Brown: Patient accrual; Data interpretation; Writing- review & editing. Kisa E. Weeman: Patient accrual; Data interpretation; Writing- review & editing. Sharon Sand: Data curation and interpretation; Writing-review & editing. Bita Nehoray: Patient accrual; Data interpretation; Writing- review & editing. Kathleen Blazer: Patient accrual; Data interpretation; Writing- review & editing. Sponsor’s Role: none Kenneth B Blankstein: Patient accrual; Data interpretation; Writing- review & editing. Zdenka E Segota: Patient accrual; Data interpretation; Writing- review & editing. Chris Hake: Patient accrual; Data interpretation; Writing- review & editing. Thomas P Slavin: Patient accrual; Data interpretation; Writing-review & editing. Carolyn B Hendricks: Patient accrual; Data interpretation; Writing- review & editing. Enrique Soto-Perez-de-Celis: Data interpretation; Writing- review & editing. Arti Hurria: Data interpretation; Writing- review & editing. Jeffrey N Weitzel: Design and conceptualization; Funding acquisition; Patient accrual; Data interpretation; Writing-review & editing. Y Chavarri-Guerra: Design and Conceptualization; Data analysis and interpretation; Writing-original draft; Writing- review & editing. Author Contributions
ISSN:	0002-8614 1532-5415
DOI:	10.1111/jgs.15937