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Prognostic Role of Detection Method and Its Relationship with Tumor Biomarkers in Breast Cancer: The University of Texas M. D. Anderson Cancer Center Experience

Departments of ¹ Biostatistics, ² Clinical Cancer Prevention, and ³ Breast Medical Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas

Requests for reprints: Yu Shen, Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 447, Houston, TX 77030. Phone: 713-794-4159; Fax: 713-563-4242. E-mail: yshen{at}mdanderson.org

Purpose: To assess the effect of tumor detection method (screening versus symptom-based diagnosis) in predicting breast cancer survival and investigate how biological features of breast cancer are related to the tumor detection method.

Patients and Methods: The study population consisted of 5,481 women diagnosed with primary invasive breast cancer between 1997 and 2005 and received their treatment at The University of Texas M. D. Anderson Cancer Center.

Results: Patients with symptom-detected tumors had an increased risk of recurrence or death [relative risk (RR), 1.34; P = 0.006] and breast cancer–specific death (RR, 1.31; P = 0.117) than patients with screen-detected tumors after adjusting for tumor characteristics and treatments received. This relationship was especially evident among estrogen receptor (ER)–negative tumors (RR, 1.60 for breast cancer recurrence for ER-negative tumors; RR, 1.18 for ER-positive tumors). ER status and Ki-67 expression were statistically significantly associated with symptom detection rate after adjusting for patients' age, tumor stage, tumor size, and nuclear grade [odds ratio (OR) of ER negative versus ER positive, 1.35; P < 0.001; OR of Ki-67 10-30% versus <10%, 1.40; P = 0.005; OR of Ki-67 >30% versus <10%, 2.11; P < 0.001].

Conclusion: The method of detection was a statistically significant independent predictor of breast cancer recurrence. Information on the method of tumor detection should be collected to improve the prediction of prognosis of breast cancer patients. (Cancer Epidemiol Biomarkers Prev 2008;17(5):1096–103)

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