Clinical Scorecard: Assessment of Polygenic Risk Scores for Breast Cancer in High-Risk African American Women
At a Glance
Category
Detail
Condition
Key Mechanisms
Polygenic risk scores (PRSs) based on single-nucleotide variations (SNVs) associated with breast cancer, as identified in genomewide association studies (GWAS).
Target Population
Care Setting
Key Highlights
Breast cancer survival rates are lower in women of African ancestry compared to those of European ancestry, as reported in studies.
Triple-negative breast cancer (TNBC) disproportionately affects women of African ancestry, according to research.
Polygenic risk scores (PRSs) can stratify breast cancer risk and inform screening strategies, as indicated by recent findings.
Independent validation of PRS models is essential for clinical application in diverse populations, as emphasized in the literature.
The study evaluated PRS models in a cohort of African American women with negative results for pathogenic variants, as per the study design.
Guideline-Based Recommendations
Diagnosis
Breast cancer cases defined as invasive breast cancer or ductal carcinoma in situ (DCIS), as per established definitions.
Unaffected individuals defined as those with no history of breast cancer, according to standard criteria.
Management
Utilization of PRS models for risk stratification and screening in high-risk populations, as recommended in clinical guidelines.
Monitoring & Follow-up
Regular screening for breast cancer in women identified at higher risk through PRS, as suggested by current practices.
Risks
Higher risk of aggressive breast cancer subtypes and later-stage diagnosis in women of African ancestry, as documented in research.
Patient & Prescribing Data
Women of self-reported Black or African ancestry aged 18-89 years.
Focus on genetic testing and risk assessment for breast cancer susceptibility.
Clinical Best Practices
Incorporate PRS in comprehensive breast cancer risk assessment, as supported by recent studies.
Ensure independent validation of PRS models in diverse populations, as highlighted in the literature.
Utilize genetic data to inform clinical decision-making regarding breast cancer screening, as per current recommendations.
by Yijia Sun, Timothy Simmons, James L. Li, Armaan Jamal, Achille V. C. Manirakiza, Dmitry Pruss, Sarah Ratzel, Olufunmilayo I. Olopade, Alexander Gutin, Elisha Hughes, Dezheng Huo
