Posted: Thursday, March 2, 2023
Breast cancer risk models are often used to estimate a woman’s risk of developing invasive breast cancer and to inform chemopreventive decisions. Historically, these models were developed and validated at the population level. Now that oncology is moving toward highly individualized patient care, more attention should be paid to the utility and uniformity of these predictive models for the assessment of individual patients. Published in the Journal of General Internal Medicine, a study by Joann G. Elmore, MD, MPH, of the University of California, Los Angeles (UCLA), and colleagues compared the accuracy and disagreement of three leading risk prevention models: Breast Cancer Risk Assessment Tool, Breast Cancer Surveillance Consortium, and the International Breast Intervention Study, at the individual patient level.
“This study highlights the risk of a blanket approach to using risk prediction models to inform individual-level medical screening and treatment decisions. All three of the models we looked at had similar accuracy at the population level, but in our analyses, there was marked disagreement between who was identified as ‘high risk’ by all three models,” Dr. Elmore stated in a UCLA press release.
A total of 31,115 women, aged 40 to 74, were assessed by questionnaire at screening mammography and again either after 5 years or at diagnosis of breast cancer. Two thresholds (> 1.67% and > 3.0%) were used to define high risk.
When all three models were considered, 46.6% of the study women were classified as being at high risk for breast cancer using the first threshold (> 1.67%), whereas 11.1% were classified as being at high risk using the second (> 3.0%). The study results indicated that breast cancer risk estimates for individual women varied considerably depending on which risk assessment tool was used.
Disclosure: For full disclosures of the study authors, visit link.springer.com.
Journal of General Internal Medicine