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Breast Cancer Risk Prediction Models: Challenges in Clinical Application
Melissa Paquin1, Tracy Fasolino1, Mary Beth Steck1
1Clemson University.
Clinical Journal of Oncology Nursing
|May 18, 2019
Summary
Oncology nurses can improve patient care by understanding breast cancer risk prediction models (BCRPMs). This knowledge ensures patients receive accurate information about their personal cancer risks and hereditary predispositions.
Area of Science:
- Oncology
- Genetics
- Nursing
Background:
- Breast cancer risk prediction models (BCRPMs) are crucial tools for assessing individual cancer development risk.
- These models also evaluate the likelihood of hereditary mutations linked to cancer.
- Accurate risk assessment is vital for personalized cancer prevention and management strategies.
Purpose of the Study:
- To provide oncology nurses with up-to-date information on available BCRPMs.
- To highlight the specific implications of BCRPMs for nursing practice.
- To emphasize the importance of nurses' understanding of BCRPMs for effective patient counseling.
Main Methods:
- Review of current literature on breast cancer risk prediction models.
- Analysis of the utility and application of various BCRPMs in clinical settings.
- Identification of key nursing considerations and interventions related to BCRPM use.
Main Results:
- Several BCRPMs are available, varying in their predictive capabilities and target populations.
- Understanding these models allows nurses to interpret risk assessments effectively.
- Nursing implications include patient education, risk stratification, and referral guidance.
Conclusions:
- Oncology nurses play a pivotal role in utilizing and communicating BCRPM results.
- Enhanced understanding of BCRPMs empowers nurses to provide accurate risk information to patients.
- This facilitates informed decision-making regarding cancer screening, prevention, and genetic testing.
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