What Predicts an Advanced-Stage Diagnosis of Breast Cancer? Sorting Out the Influence of Method of Detection, Access to Care, and Biologic Factors.

Journal Article

Multiple studies have yielded important findings regarding the determinants of an advanced-stage diagnosis of breast cancer. We seek to advance this line of inquiry through a broadened conceptual framework and accompanying statistical modeling strategy that recognize the dual importance of access-to-care and biologic factors on stage.The Centers for Disease Control and Prevention-sponsored Breast and Prostate Cancer Data Quality and Patterns of Care Study yielded a seven-state, cancer registry-derived population-based sample of 9,142 women diagnosed with a first primary in situ or invasive breast cancer in 2004. The likelihood of advanced-stage cancer (American Joint Committee on Cancer IIIB, IIIC, or IV) was investigated through multivariable regression modeling, with base-case analyses using the method of instrumental variables (IV) to detect and correct for possible selection bias. The robustness of base-case findings was examined through extensive sensitivity analyses.Advanced-stage disease was negatively associated with detection by mammography (P < 0.001) and with age < 50 (P < 0.001), and positively related to black race (P = 0.07), not being privately insured [Medicaid (P = 0.01), Medicare (P = 0.04), uninsured (P = 0.07)], being single (P = 0.06), body mass index > 40 (P = 0.001), a HER2 type tumor (P < 0.001), and tumor grade not well differentiated (P < 0.001). This IV model detected and adjusted for significant selection effects associated with method of detection (P = 0.02). Sensitivity analyses generally supported these base-case results.Through our comprehensive modeling strategy and sensitivity analyses, we provide new estimates of the magnitude and robustness of the determinants of advanced-stage breast cancer.Statistical approaches frequently used to address observational data biases in treatment-outcome studies can be applied similarly in analyses of the determinants of stage at diagnosis. Cancer Epidemiol Biomarkers Prev; 25(4); 613-23. ©2016 AACR.

Full Text

Duke Authors

Cited Authors

  • Lipscomb, J; Fleming, ST; Trentham-Dietz, A; Kimmick, G; Wu, X-C; Morris, CR; Zhang, K; Smith, RA; Anderson, RT; Sabatino, SA; Centers for Disease Control and Prevention National Program of Cancer Registries Patterns of Care Study Group,

Published Date

  • April 2016

Published In

Volume / Issue

  • 25 / 4

Start / End Page

  • 613 - 623

PubMed ID

  • 26819266

Electronic International Standard Serial Number (EISSN)

  • 1538-7755

International Standard Serial Number (ISSN)

  • 1055-9965

Digital Object Identifier (DOI)

  • 10.1158/1055-9965.epi-15-0225

Language

  • eng