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Cited by 744

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Breast cancer early detection: A phased approach to implementation

Open access
Ginsburg, Ophira, Yip, Cheng‐Har, Brooks, Ari, Cabanes, Anna, Caleffi, Maira, Dunstan Yataco, Jorge Antonio, Gyawali, Bishal, McCormack, Valerie, McLaughlin de Anderson, Myrna, Mehrotra, Ravi, Mohar, Alejandro, Murillo, Raul, Pace, Lydia E., Paskett, Electra D., Romanoff, Anya, Rositch, Anne F., Scheel, John R., Schneidman, Miriam, Unger‐Saldaña, Karla, Vanderpuye, Verna, Wu, Tsu‐Yin, Yuma, Safina, Dvaladze, Allison, Duggan, Catherine, Anderson, Benjamin O.·2020·Cancer

Abstract

When breast cancer is detected and treated early, the chances of survival are very high. However, women in many settings face complex barriers to early detection, including social, economic, geographic, and other interrelated factors, which can limit their access to timely, affordable, and effective breast health care services. Previously, the Breast Health Global Initiative (BHGI) developed resource‐stratified guidelines for the early detection and diagnosis of breast cancer. In this consensus article from the sixth BHGI Global Summit held in October 2018, the authors describe phases of early detection program development, beginning with management strategies required for the diagnosis of clinically detectable disease based on awareness education and technical training, history and physical examination, and accurate tissue diagnosis. The core issues address include finance and governance, which pertain to successful planning, implementation, and the iterative process of program improvement and are needed for a breast cancer early detection program to succeed in any resource setting. Examples are presented of implementation, process, and clinical outcome metrics that assist in program implementation monitoring. Country case examples are presented to highlight the challenges and opportunities of implementing successful breast cancer early detection programs, and the complex interplay of barriers and facilitators to achieving early detection for breast cancer in real‐world settings are considered.

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Metadata

Authors
Ginsburg, O., Yip, C., Brooks, A., Cabanes, A., Caleffi, M., Dunstan Yataco, J. A., Gyawali, B., McCormack, V., McLaughlin de Anderson, M., Mehrotra, R., Mohar, A., Murillo, R., Pace, L. E., Paskett, E. D., Romanoff, A., Rositch, A. F., Scheel, J. R., Schneidman, M., Unger‐Saldaña, K., Vanderpuye, V., Wu, T., Yuma, S., Dvaladze, A., Duggan, C., & Anderson, B. O.
Venue
Cancer
Publisher
Wiley
Published
2020-04-29
Volume
126
Issue
S10
Pages
2379-2393
ISSN
  • 0008-543X (ISSN-L)
  • 1097-0142
OpenAlex
W3020578014
Cited by
744
References
1
FWCI
24.78
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Breast cancer early detection: A phased approach to implementation. https://app.cochat.ai/papers/10.1002/cncr.32887
The paper
Ginsburg, O., Yip, C., Brooks, A., Cabanes, A., Caleffi, M., Dunstan Yataco, J. A., Gyawali, B., McCormack, V., McLaughlin de Anderson, M., Mehrotra, R., Mohar, A., Murillo, R., Pace, L. E., Paskett, E. D., Romanoff, A., Rositch, A. F., Scheel, J. R., Schneidman, M., Unger‐Saldaña, K., . . . Anderson, B. O. (2020). Breast cancer early detection: A phased approach to implementation. Cancer. https://doi.org/10.1002/cncr.32887

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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