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- Title
A Novel Automated Mammographic Density Measure and Breast Cancer Risk.
- Authors
Heine, John J.; Scott, Christopher G.; Sellers, Thomas A.; Brandt, Kathleen R.; Serie, Daniel J.; Wu, Fang-Fang; Morton, Marilyn J.; Schueler, Beth A.; Couch, Fergus J.; Olson, Janet E.; Pankratz, V. Shane; Vachon, Celine M.
- Abstract
Background Mammographic breast density is a strong breast cancer risk factor but is not used in the clinical setting, partly because of a lack of standardization and automation. We developed an automated and objective measurement of the grayscale value variation within a mammogram, evaluated its association with breast cancer, and compared its performance with that of percent density (PD).Methods Three clinic-based studies were included: a case–cohort study of 217 breast cancer case subjects and 2094 non-case subjects and two case–control studies comprising 928 case subjects and 1039 control subjects and 246 case subjects and 516 control subjects, respectively. Percent density was estimated from digitized mammograms using the computer-assisted Cumulus thresholding program, and variation was estimated from an automated algorithm. We estimated hazards ratios (HRs), odds ratios (ORs), the area under the receiver operating characteristic curve (AUC), and 95% confidence intervals (CIs) using Cox proportional hazards models for the cohort and logistic regression for case–control studies, with adjustment for age and body mass index. We performed a meta-analysis using random study effects to obtain pooled estimates of the associations between the two mammographic measures and breast cancer. All statistical tests were two-sided.Results The variation measure was statistically significantly associated with the risk of breast cancer in all three studies (highest vs lowest quartile: HR = 7.0 [95% CI = 4.6 to 10.4]; OR = 10.7 [95% CI = 7.5 to 15.3]; OR = 2.6 [95% CI = 1.6 to 4.2]; all Ptrend < .001). In two studies, the risk estimates and AUCs for the variation measure were greater than those for percent density (AUCs for variation = 0.71 and 0.76; AUCs for percent density = 0.65 and 0.65), whereas in the third study, these estimates were similar (AUC for variation = 0.60 and AUC for percent density = 0.61). A meta-analysis of the three studies demonstrated a stronger association between variation and breast cancer (highest vs lowest quartile: RR = 3.6, 95% CI = 1.9 to 7.0) than between percent density and breast cancer (highest vs lowest quartile: RR = 2.3, 95% CI = 1.9 to 2.9).Conclusion The association between the automated variation measure and the risk of breast cancer is at least as strong as that for percent density. Efforts to further evaluate and translate the variation measure to the clinical setting are warranted.
- Subjects
BREAST cancer risk factors; MAMMOGRAMS; MEDICAL digital radiography; ALGORITHMS; CONFIDENCE intervals; PROPORTIONAL hazards models; REGRESSION analysis; META-analysis
- Publication
JNCI: Journal of the National Cancer Institute, 2012, Vol 104, Issue 13, p1028
- ISSN
0027-8874
- Publication type
Article
- DOI
10.1093/jnci/djs254