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本文引用的文献

1
Readiness of primary care clinicians to implement lung cancer screening programs.基层医疗临床医生实施肺癌筛查项目的准备情况。
Prev Med Rep. 2015 Aug 24;2:717-9. doi: 10.1016/j.pmedr.2015.08.014. eCollection 2015.
2
Baseline Screening Mammography: Performance of Full-Field Digital Mammography Versus Digital Breast Tomosynthesis.基线筛查乳腺钼靶检查：全视野数字化乳腺钼靶与数字乳腺断层合成技术的性能比较
AJR Am J Roentgenol. 2015 Nov;205(5):1143-8. doi: 10.2214/AJR.15.14406.
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Importance of determining indication for colonoscopy: implications for practice and policy original.确定结肠镜检查适应证的重要性：对实践和政策的影响 原创
Clin Gastroenterol Hepatol. 2014 Dec;12(12):1958-63.e1-3. doi: 10.1016/j.cgh.2014.09.028.
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Breast cancer screening with tomosynthesis and digital mammography-reply.乳腺断层合成与数字乳腺摄影用于乳腺癌筛查——回复
JAMA. 2014;312(16):1695-6. doi: 10.1001/jama.2014.11123.
5
Screening outcomes following implementation of digital breast tomosynthesis in a general-population screening program.在一项普通人群筛查项目中实施数字乳腺断层合成后的筛查结果。
J Natl Cancer Inst. 2014 Oct 13;106(11). doi: 10.1093/jnci/dju316. Print 2014 Nov.
6
Should CMS cover lung cancer screening for the fully informed patient?医疗保险和医疗补助服务中心（CMS）是否应为充分知情的患者提供肺癌筛查？
JAMA. 2014 Sep 24;312(12):1193-4. doi: 10.1001/jama.2014.12709.
7
Understanding patient options, utilization patterns, and burdens associated with breast cancer screening.了解与乳腺癌筛查相关的患者选择、利用模式和负担。
J Womens Health (Larchmt). 2014 Sep;23 Suppl 1:S3-9. doi: 10.1089/jwh.2014.1510.
8
Prevalence of mammographically dense breasts in the United States.美国乳腺钼靶检查显示乳房致密的患病率。
J Natl Cancer Inst. 2014 Sep 12;106(10). doi: 10.1093/jnci/dju255. Print 2014 Oct.
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Breast MRI BI-RADS assessments and abnormal interpretation rates by clinical indication in US community practices.美国社区医疗机构中乳腺MRI的BI-RADS评估及按临床指征划分的异常解读率
Acad Radiol. 2014 Nov;21(11):1370-6. doi: 10.1016/j.acra.2014.06.003. Epub 2014 Aug 7.
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How should screening breast US be audited? The BI-RADS perspective.乳腺超声筛查应如何进行审核？基于乳腺影像报告和数据系统（BI-RADS）的视角。
Radiology. 2014 Aug;272(2):316-20. doi: 10.1148/radiol.14140634.

在实践、研究和政策中，将乳腺影像学检查指征识别作为关键临床属性所面临的挑战。

Challenges With Identifying Indication for Examination in Breast Imaging as a Key Clinical Attribute in Practice, Research, and Policy.

作者信息

Weiss Julie E, Goodrich Martha, Harris Kimberly A, Chicoine Rachael E, Synnestvedt Marie B, Pyle Steve J, Chen Jane S, Herschorn Sally D, Beaber Elisabeth F, Haas Jennifer S, Tosteson Anna N A, Onega Tracy

机构信息

Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire; Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.

Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire; Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.

出版信息

J Am Coll Radiol. 2017 Feb;14(2):198-207.e2. doi: 10.1016/j.jacr.2016.08.017. Epub 2016 Oct 13.

DOI:10.1016/j.jacr.2016.08.017
PMID:
27744009
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5292278/
Abstract

PURPOSE

To assess indication for examination for four breast imaging modalities and describe the complexity and heterogeneity of data sources and ascertainment methods.

METHODS

Indication was evaluated among the Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) breast cancer research centers (PRCs). Indication data were reported overall and separately for four breast imaging modalities: digital mammography (DM), digital breast tomosynthesis (DBT), ultrasound (US), and magnetic resonance imaging (MRI).

RESULTS

The breast PRCs contributed 236,262 women with 607,735 breast imaging records from 31 radiology facilities. We found a high degree of heterogeneity for indication within and across six data sources. Structured codes within a data source were used most often to identify indication for mammography (59% DM, 85% DBT) and text analytics for US (45%) and MRI (44%). Indication could not be identified for 17% of US and 26% of MRI compared with 2% of mammography examinations (1% DM, 3% DBT).

CONCLUSIONS

Multiple and diverse data sources, heterogeneity of ascertainment methods, and nonstandardization of codes within and across data systems for determining indication were found. Consideration of data sources and standardized methodology for determining indication is needed to assure accurate measurement of cancer screening rates and performance in clinical practice and research.

摘要

目的

评估四种乳腺成像模态的检查指征，并描述数据源和确定方法的复杂性及异质性。

方法

在基于人群的个性化方案优化筛查乳腺癌研究中心（PROSPR）中评估指征。分别报告了四种乳腺成像模态（数字乳腺钼靶摄影（DM）、数字乳腺断层合成（DBT）、超声（US）和磁共振成像（MRI））的总体指征数据。

结果

乳腺研究中心提供了来自31个放射科设施的236,262名女性的607,735条乳腺成像记录。我们发现六个数据源内部和之间的指征存在高度异质性。数据源中的结构化编码最常用于识别钼靶摄影的指征（DM为59%，DBT为85%），而超声（45%）和MRI（44%）的指征则通过文本分析来识别。与2%的钼靶摄影检查（DM为1%，DBT为3%）相比，17%的超声检查和26%的MRI检查无法识别指征。

结论

发现了多种不同的数据源、确定方法的异质性以及数据系统内部和之间用于确定指征的编码的不标准化。为确保在临床实践和研究中准确测量癌症筛查率和性能，需要考虑数据源和用于确定指征的标准化方法。