Predicting invasive breast cancer versus DCIS in different age groups

BMC Cancer

Elizabeth S Burnside⁶  Karla Kerlikowske³  Houssam Nassif⁴  Edward A Sickles²  Alejandro Munoz del Rio⁶  Jagpreet Chhatwal⁵  Oguzhan Alagoz⁷  Mehmet US Ayvaci¹ 

[1]Information Systems and Operations Management, University of Texas at Dallas, 800 W Campbell Rd, SM 33, Richardson, TX 75080-3021, USA

[2]Department of Radiology, University of California, San Francisco, CA 94143, USA

[3]Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, CA 94143, USA

[4]Department of Computer Science, University of Wisconsin, Madison, WI 53706, USA

[5]Department of Health Services Research, MD Anderson Cancer Center at University of Texas, 1400 Pressler Street, Unit 1444, Houston, TX 77098, USA

[6]Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave., Madison, WI 53792-3252, USA

[7]Industrial & Systems Engineering, University of Wisconsin, 1513 University Avenue, Madison, WI 53706, USA

关键词: Aging;    Biopsy;    Overdiagnosis;    Breast neoplasms;    Logistic models;    Mammography;   

Others  :  1125212
DOI  :  10.1186/1471-2407-14-584

 received in 2013-05-13, accepted in 2014-08-06,  发布年份 2014

【 摘 要 】

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.

【 授权许可】

   
2014 Ayvaci et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

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