Choosing Breast Cancer Risk Models: Importance of Independent Validation.
作者信息
Gail Mitchel H
机构信息
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD.
出版信息
J Natl Cancer Inst. 2020 May 1;112(5):433-435. doi: 10.1093/jnci/djz180.
Abstract
摘要
相似文献
1
Choosing Breast Cancer Risk Models: Importance of Independent Validation.选择乳腺癌风险模型：独立验证的重要性。
J Natl Cancer Inst. 2020 May 1;112(5):433-435. doi: 10.1093/jnci/djz180.
2
The contribution of mammography screening to breast cancer incidence trends in the United States: an updated age-period-cohort model.乳腺X线筛查对美国乳腺癌发病趋势的贡献：一个更新的年龄-时期-队列模型
Cancer Epidemiol Biomarkers Prev. 2015 Jun;24(6):905-12. doi: 10.1158/1055-9965.EPI-14-1286. Epub 2015 Mar 18.
3
The incidence of breast cancer from screening women according to predicted family history risk: Does annual clinical examination add to mammography?根据预测的家族病史风险对女性进行乳腺癌筛查的发病率：年度临床检查对乳房X光检查有补充作用吗？
Eur J Cancer. 2001 Sep;37(13):1668-73. doi: 10.1016/s0959-8049(01)00207-6.
4
Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: A case control study.基于乳腺X线摄影形态和密度对乳腺X线筛查中假阳性检测结果的女性进行风险分层：一项病例对照研究。
Cancer Epidemiol. 2017 Aug;49:53-60. doi: 10.1016/j.canep.2017.05.006. Epub 2017 May 27.
5
Evaluation of overdiagnosis of breast cancer in screening with mammography: results of the Nijmegen programme.乳腺钼靶筛查中乳腺癌过度诊断的评估：奈梅亨项目的结果。
Int J Epidemiol. 1989 Jun;18(2):295-9. doi: 10.1093/ije/18.2.295.
6
Predictors of surveillance mammography outcomes in women with a personal history of breast cancer.乳腺癌病史女性监测性乳房 X 光检查结果的预测因素。
Breast Cancer Res Treat. 2018 Aug;171(1):209-215. doi: 10.1007/s10549-018-4808-9. Epub 2018 May 10.
7
Do reproductive and hormonal risk factors for breast cancer associate with attendance at mammography screening?乳腺癌的生殖和激素危险因素是否与参加乳房 X 线筛查有关？
Cancer Causes Control. 2013 Sep;24(9):1687-94. doi: 10.1007/s10552-013-0243-8. Epub 2013 Jun 5.
8
Cohort Profile: The Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA).队列简介：卡罗琳斯卡乳腺癌风险预测乳腺X线摄影项目（KARMA）。
Int J Epidemiol. 2017 Dec 1;46(6):1740-1741g. doi: 10.1093/ije/dyw357.
9
Age-period-cohort modelling of breast cancer incidence in the Nordic countries.北欧国家乳腺癌发病率的年龄-时期-队列模型
Stat Med. 2001 Jan 15;20(1):47-61. doi: 10.1002/1097-0258(20010115)20:1<47::aid-sim613>3.0.co;2-5.
10
Breast cancer screening in a rural Wisconsin community.
WMJ. 2001;100(6):32-4.
引用本文的文献
1
Artificial Intelligence-Powered Imaging Biomarker Based on Mammography for Breast Cancer Risk Prediction.基于乳腺X线摄影的人工智能成像生物标志物用于乳腺癌风险预测。
Diagnostics (Basel). 2024 Jun 7;14(12):1212. doi: 10.3390/diagnostics14121212.
2
Artificial Intelligence in Breast Cancer Diagnosis and Personalized Medicine.人工智能在乳腺癌诊断与个性化医疗中的应用
J Breast Cancer. 2023 Oct;26(5):405-435. doi: 10.4048/jbc.2023.26.e45.
3
BREAst screening Tailored for HEr (BREATHE)-A study protocol on personalised risk-based breast cancer screening programme.基于个体风险的乳腺癌筛查项目的个体化筛查方案（BREATHE）研究方案。
PLoS One. 2022 Mar 31;17(3):e0265965. doi: 10.1371/journal.pone.0265965. eCollection 2022.
4
Mammography screening and mortality by risk status in the California teachers study.加利福尼亚教师研究中的风险状况与乳腺癌筛查和死亡率。
BMC Cancer. 2021 Dec 18;21(1):1341. doi: 10.1186/s12885-021-09071-1.
5
Data Sharing for the Public Good.为公共利益进行数据共享。
J Natl Cancer Inst. 2020 Sep 1;112(9):867-868. doi: 10.1093/jnci/djz242.
本文引用的文献
1
Performance of Breast Cancer Risk-Assessment Models in a Large Mammography Cohort.乳腺癌风险评估模型在大型乳腺 X 线摄影队列中的表现。
J Natl Cancer Inst. 2020 May 1;112(5):489-497. doi: 10.1093/jnci/djz177.
2
Comparative Validation of Breast Cancer Risk Prediction Models and Projections for Future Risk Stratification.比较乳腺癌风险预测模型的验证及对未来风险分层的预测。
J Natl Cancer Inst. 2020 Mar 1;112(3):278-285. doi: 10.1093/jnci/djz113.
3
Performance of BCRAT in high-risk patients with breast cancer.BCRAT在高危乳腺癌患者中的表现。
Lancet Oncol. 2019 Jun;20(6):e285. doi: 10.1016/S1470-2045(19)30301-8.
4
10-year performance of four models of breast cancer risk: a validation study.四种乳腺癌风险模型的 10 年表现：一项验证研究。
Lancet Oncol. 2019 Apr;20(4):504-517. doi: 10.1016/S1470-2045(18)30902-1. Epub 2019 Feb 21.
5
Correction: BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors.更正：BOADICEA：一种综合的乳腺癌风险预测模型，纳入了遗传和非遗传风险因素。
Genet Med. 2019 Jun;21(6):1462. doi: 10.1038/s41436-019-0459-4.
6
Breast Cancer Risk Model Requirements for Counseling, Prevention, and Screening.乳腺癌风险模型的咨询、预防和筛查要求。
J Natl Cancer Inst. 2018 Sep 1;110(9):994-1002. doi: 10.1093/jnci/djy013.
7
Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States.美国白人女性中可改变和不可改变的风险因素与乳腺癌风险。
JAMA Oncol. 2016 Oct 1;2(10):1295-1302. doi: 10.1001/jamaoncol.2016.1025.
8
Combined associations of genetic and environmental risk factors: implications for prevention of breast cancer.遗传和环境风险因素的联合关联：对乳腺癌预防的启示
J Natl Cancer Inst. 2014 Nov 12;106(11). doi: 10.1093/jnci/dju305. Print 2014 Nov.
9
Risk prediction for breast, endometrial, and ovarian cancer in white women aged 50 y or older: derivation and validation from population-based cohort studies.50 岁及以上白人女性的乳腺癌、子宫内膜癌和卵巢癌风险预测：来自基于人群的队列研究的推导和验证。
PLoS Med. 2013;10(7):e1001492. doi: 10.1371/journal.pmed.1001492. Epub 2013 Jul 30.
10
Risk factor modification and projections of absolute breast cancer risk.风险因素的改变和绝对乳腺癌风险的预测。
J Natl Cancer Inst. 2011 Jul 6;103(13):1037-48. doi: 10.1093/jnci/djr172. Epub 2011 Jun 24.
Zotero 插件