Predicting invasive breast cancer versus DCIS in different age groups

Citation:

M. U. Ayvaci, O. Alagoz, J. Chhatwal, A. Munoz del Rio, E. A. Sickles, H. Nassif, K. Kerlikowske, and E.S. Burnside. 2014. “Predicting invasive breast cancer versus DCIS in different age groups.” BMC Cancer, 14, Pp. 584.

Abstract:

BACKGROUND: Increasing focus on potentially unnecessary diagnosis and treatment of certain breast cancers prompted our investigation of whether clinical and mammographic features predictive of invasive breast cancer versus ductal carcinoma in situ (DCIS) differ by age. METHODS: We analyzed 1,475 malignant breast biopsies, 1,063 invasive and 412 DCIS, from 35,871 prospectively collected consecutive diagnostic mammograms interpreted at University of California, San Francisco between 1/6/1997 and 6/29/2007. We constructed three logistic regression models to predict the probability of invasive cancer versus DCIS for the following groups: women >/= 65 (older group), women 50-64 (middle age group), and women < 50 (younger group). We identified significant predictors and measured the performance in all models using area under the receiver operating characteristic curve (AUC). RESULTS: The models for older and the middle age groups performed significantly better than the model for younger group (AUC = 0.848 vs, 0.778; p = 0.049 and AUC = 0.851 vs, 0.778; p = 0.022, respectively). Palpability and principal mammographic finding were significant predictors in distinguishing invasive from DCIS in all age groups. Family history of breast cancer, mass shape and mass margins were significant positive predictors of invasive cancer in the older group whereas calcification distribution was a negative predictor of invasive cancer (i.e. predicted DCIS). In the middle age group–mass margins, and in the younger group–mass size were positive predictors of invasive cancer. CONCLUSIONS: Clinical and mammographic finding features predict invasive breast cancer versus DCIS better in older women than younger women. Specific predictive variables differ based on age.

Notes:

Ayvaci, Mehmet U S Alagoz, Oguzhan Chhatwal, Jagpreet Munoz del Rio, Alejandro Sickles, Edward A Nassif, Houssam Kerlikowske, Karla Burnside, Elizabeth S K07CA114181/CA/NCI NIH HHS/United States P30CA014520/CA/NCI NIH HHS/United States R01 CA165229/CA/NCI NIH HHS/United States R01CA127379/CA/NCI NIH HHS/United States R01CA165229/CA/NCI NIH HHS/United States R01LM010921/LM/NLM NIH HHS/United States R21CA129393/CA/NCI NIH HHS/United States U01CA63740/CA/NCI NIH HHS/United States UL1 TR000427/TR/NCATS NIH HHS/United States UL1TR000427/TR/NCATS NIH HHS/United States Research Support, N.I.H., Extramural England BMC Cancer. 2014 Aug 11;14:584. doi: 10.1186/1471-2407-14-584.