BACKGROUND: Advanced breast cancer is an outcome used to evaluate screening effectiveness. The advanced cancer definition resulting in the best discrimination of breast cancer death has not been studied in a breast imaging population. METHODS: A total of 52 496 women aged 40-79 years participating in the Breast Cancer Surveillance Consortium diagnosed with invasive cancer were staged using the 8th edition of American Joint Committee on Cancer (AJCC) anatomic and prognostic pathologic systems and Tomosynthesis Mammographic Imaging Screening Trial (TMIST) tumor categories. We calculated the area under the receiver operating characteristic curve for predicting 5-year breast cancer death and the sensitivity and specificity for predicting 5-year breast cancer death for 3 advanced cancer classifications: anatomic stage IIB or higher, prognostic pathologic stage IIA or higher, and TMIST advanced cancer. RESULTS: The area under the receiver operating characteristic curves for predicting 5-year breast cancer death for AJCC anatomic stage, AJCC prognostic pathologic stage, and TMIST tumor categories were 0.826 (95% confidence interval [CI] = 0.817 to 0.835), 0.856 (95% CI = 0.846 to 0.866), and 0.789 (95% CI = 0.780 to 0.797), respectively. AJCC prognostic pathologic stage had statistically significantly better discrimination than AJCC anatomic stage (difference = 0.030, bootstrap 95% CI = 0.024 to 0.037) and TMIST tumor categories (difference = 0.067, bootstrap 95% CI = 0.059 to 0.075). The sensitivity and specificity for predicting 5-year breast cancer death for AJCC anatomic stage IIB or higher, AJCC prognostic pathologic stage IIA or higher, and TMIST advanced cancer were 72.6%, 76.7%, and 96.1%; and 78.9%, 81.6%, and 41.1%, respectively. CONCLUSIONS: Defining advanced cancer as AJCC prognostic pathologic stage IIA or higher most accurately predicts breast cancer death. Use of this definition by investigators will facilitate comparing breast cancer screening effectiveness studies.
ASJC Scopus subject areas
- Cancer Research