Full Text | PDF

J Cancer 2011; 2:210-227. doi:10.7150/jca.2.210 This volume Cite

Review

Consensus Recommendations for Advancing Breast Cancer: Risk Identification and Screening in Ethnically Diverse Younger Women

Alexander Stojadinovic^{1, 2 ✉}, Thomas A Summers³, John Eberhardt⁴, Albert Cerussi⁵, Warren Grundfest⁶, Charles M. Peterson⁷, Michael Brazaitis⁷, Elizabeth Krupinski⁸, Harold Freeman⁹

1. Uniformed Services University of the Health Sciences, Bethesda, MD, USA
2. United States Military Cancer Institute, Washington, D.C. , USA
3. Department of Pathology and Laboratory Services, Walter Reed Army Medical Center, Washington, DC 20307, USA
4. DecisionQ Corporation, Washington, D.C. , USA
5. University of California, Irvine, USA
6. University of California, Los Angeles, USA
7. Telemedicine and Advanced Technology Research Center, Fort Detrick, MD, USA
8. Department of Radiology, University of Arizona, Tucson, AZ, USA
9. The Ralph Lauren Center for Cancer Care and Prevention, New York, NY, USA

✉ Corresponding author: Alexander Stojadinovic, MD FACS, Walter Reed Army Medical Center, Department of Surgery, General Surgery Service, 6900 Georgia Avenue, N.W., Washington, D.C. 20307. TEL: (202) 782-9691; FAX: (202) 782-0759; stojadinovicmdcom More

Abstract

A need exists for a breast cancer risk identification paradigm that utilizes relevant demographic, clinical, and other readily obtainable patient-specific data in order to provide individualized cancer risk assessment, direct screening efforts, and detect breast cancer at an early disease stage in historically underserved populations, such as younger women (under age 40) and minority populations, who represent a disproportionate number of military beneficiaries. Recognizing this unique need for military beneficiaries, a consensus panel was convened by the USA TATRC to review available evidence for individualized breast cancer risk assessment and screening in young (< 40), ethnically diverse women with an overall goal of improving care for military beneficiaries. In the process of review and discussion, it was determined to publish our findings as the panel believes that our recommendations have the potential to reduce health disparities in risk assessment, health promotion, disease prevention, and early cancer detection within and in other underserved populations outside of the military. This paper aims to provide clinicians with an overview of the clinical factors, evidence and recommendations that are being used to advance risk assessment and screening for breast cancer in the military.

Keywords: breast cancer, screening, personalized medicine, mammography, Bayesian Belief Networks, machine learning, Gail model, risk assessment

Citation styles

©2024 Ivyspring International Publisher. Terms of use