Freer Phoebe E, Slanetz Priscilla J, Haas Jennifer S, Tung Nadine M, Hughes Kevin S, Armstrong Katrina, Semine A Alan, Troyan Susan L, Birdwell Robyn L
Division of Breast Imaging, MGH Imaging, Massachusetts General Hospital, Boston, USA,
Breast Cancer Res Treat. 2015 Sep;153(2):455-64. doi: 10.1007/s10549-015-3534-9. Epub 2015 Aug 20.
Stemming from breast density notification legislation in Massachusetts effective 2015, we sought to develop a collaborative evidence-based approach to density notification that could be used by practitioners across the state. Our goal was to develop an evidence-based consensus management algorithm to help patients and health care providers follow best practices to implement a coordinated, evidence-based, cost-effective, sustainable practice and to standardize care in recommendations for supplemental screening. We formed the Massachusetts Breast Risk Education and Assessment Task Force (MA-BREAST) a multi-institutional, multi-disciplinary panel of expert radiologists, surgeons, primary care physicians, and oncologists to develop a collaborative approach to density notification legislation. Using evidence-based data from the Institute for Clinical and Economic Review, the Cochrane review, National Comprehensive Cancer Network guidelines, American Cancer Society recommendations, and American College of Radiology appropriateness criteria, the group collaboratively developed an evidence-based best-practices algorithm. The expert consensus algorithm uses breast density as one element in the risk stratification to determine the need for supplemental screening. Women with dense breasts and otherwise low risk (<15% lifetime risk), do not routinely require supplemental screening per the expert consensus. Women of high risk (>20% lifetime) should consider supplemental screening MRI in addition to routine mammography regardless of breast density. We report the development of the multi-disciplinary collaborative approach to density notification. We propose a risk stratification algorithm to assess personal level of risk to determine the need for supplemental screening for an individual woman.
源自2015年生效的马萨诸塞州乳房密度通知立法,我们试图开发一种基于证据的协作式乳房密度通知方法,供全州的从业者使用。我们的目标是制定一种基于证据的共识管理算法,以帮助患者和医疗服务提供者遵循最佳实践,实施协调一致、基于证据、具有成本效益且可持续的做法,并规范补充筛查建议中的护理。我们成立了马萨诸塞州乳房风险教育与评估特别工作组(MA - BREAST),这是一个由放射科专家、外科医生、初级保健医生和肿瘤学家组成的多机构、多学科小组,旨在制定一种针对乳房密度通知立法的协作方法。该小组利用来自临床与经济审查研究所、考科蓝综述、国家综合癌症网络指南、美国癌症协会建议以及美国放射学会适宜性标准的循证数据,共同制定了一种基于证据的最佳实践算法。专家共识算法将乳房密度作为风险分层的一个要素,以确定是否需要进行补充筛查。根据专家共识,乳房致密但其他方面风险较低(终生风险<15%)的女性通常不需要进行补充筛查。高风险(终生风险>20%)的女性,无论乳房密度如何,除了常规乳腺钼靶检查外,都应考虑进行补充筛查磁共振成像(MRI)。我们报告了针对乳房密度通知的多学科协作方法的开发情况。我们提出一种风险分层算法,以评估个人风险水平,确定个体女性是否需要进行补充筛查。