Breast Cancer Mode of Detection in a Population-Based Cohort.

Mayo Clin Proc

Division of General Internal Medicine, Mayo Clinic, Rochester, MN; Department of Internal Medicine, Yale New Haven Health, New Haven, CT. Electronic address:

Published: February 2023

Objective: To evaluate how breast cancers come to clinical attention (mode of detection [MOD]) in a population-based cohort, determine the relative frequency of different MODs, and characterize patient and tumor characteristics associated with MOD.

Patients And Methods: We used the Rochester Epidemiology Project to identify women ages 40 to 75 years with a first-time diagnosis of breast cancer from May 9, 2017, to May 9, 2019 (n=500) in a 9-county region in Minnesota. We conducted a retrospective medical record review to ascertain the relative frequency of MODs, evaluating differences between screening mammography vs all other MODs by breast density and cancer characteristics. Multiple logistic regression was conducted to examine the likelihood of MOD for breast density and stage of disease.

Results: In our population-based cohort, 162 of 500 breast cancers (32.4%) were detected by MODs other than screening mammography, including 124 (24.8%) self-detected cancers. Compared with women with mammography-detected cancers, those with MODs other than screening mammography were more frequently younger than 50 years of age (P=.004) and had higher-grade tumors (P=.007), higher number of positive lymph nodes (P<.001), and larger tumor size (P<.001). Relative to women with mammography-detected cancers, those with MODs other than screening mammography were more likely to have dense breasts (odds ratio, 1.87; 95% CI, 1.20 to 2.92; P=.006) and advanced cancer at diagnosis (odds ratio, 3.58; 95% CI, 2.29 to 5.58; P<.001).

Conclusion: One-third of all breast cancers in this population were detected by MODs other than screening mammography. Increased likelihood of nonmammographic MODs was observed among women with dense breasts and advanced cancer.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9907001PMC
http://dx.doi.org/10.1016/j.mayocp.2022.10.010DOI Listing

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