ASSOCIATION OF BRCA1 AND BRCA2 GENE MUTATIONS WITH BREAST CANCER RISK AMONG WOMEN WITH POSITIVE FAMILY HISTORY: A SYSTEMATIC REVIEW
DOI:
https://doi.org/10.71000/j0mn1e74Keywords:
BRCA1, BRCA2, , Hereditary Breast Cancer, Family History, Systematic Review, Risk Assessment.Abstract
Background: Pathogenic variants in the BRCA1 and BRCA2 genes significantly elevate breast cancer risk, particularly among women with a positive family history. However, precise risk quantification for this specific, genetically predisposed subpopulation requires consolidation from the growing body of recent literature.
Objective: This systematic review aims to investigate the association between BRCA1/2 mutations and breast cancer risk among women with a confirmed positive family history of the disease.
Methods: A systematic review was conducted following PRISMA guidelines. Electronic databases (PubMed, Scopus, Web of Science, Cochrane Library) were searched for observational studies published between 2019-2024. Included studies reported breast cancer risk estimates for BRCA carriers versus non-carriers within cohorts of women with a family history. Study quality was assessed using the Newcastle-Ottawa Scale.
Results: Eight studies (n=35,842 participants) were included. The synthesis consistently demonstrated a substantially elevated risk for BRCA carriers with a family history compared to non-carrier relatives, with adjusted hazard ratios ranging from 12.5 to 28.4. Cumulative risk estimates by age 70 were high, between 66% and 72%. The strength of the family history was identified as a key effect modifier, with stronger family aggregation associated with higher penetrance.
Conclusion: The evidence confirms that BRCA1/2 mutations confer a profoundly high risk of breast cancer in women with a positive family history. These findings are critical for refining risk assessment, guiding genetic counseling, and personalizing clinical management strategies for this high-risk population. Future research should focus on standardizing family history reporting and integrating genetic modifiers into risk prediction models.
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Copyright (c) 2025 Imad Hassan, Asmat Nawaz , Shehroz Nafees , Kifayat Ullah , Irfan Ishaque , Momtaz Akter Mitu, Rehana Shaheen , Javeria Naz (Author)
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