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利用模拟建模为降低哥伦比亚特区黑人女性乳腺癌死亡率的策略提供信息。

Using Simulation Modeling to Inform Strategies to Reduce Breast Cancer Mortality in Black Women in the District of Columbia.

作者信息

Near Aimee M, Mandelblatt Jeanne S, Schechter Clyde B, Stoto Michael A

机构信息

Department of Oncology, Georgetown University Medical Center and Cancer Control Program, Lombardi Comprehensive Cancer Center, 3300 Whitehaven St, NW, Suite 4100, Washington, DC 20007.

出版信息

Epidemiol Res Int. 2012 Apr 26;2012(2012). doi: 10.1155/2012/241340.

DOI:10.1155/2012/241340
PMID:23914301
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3731168/
Abstract

BACKGROUND

Black women in the District of Columbia (DC) have the highest breast cancer mortality in the US. Local cancer control planners are interested in how to most efficiently reduce this mortality.

METHODS

An established simulation model was adapted to reflect the experiences of Black women in DC and estimate the past and future impact of changes in use of screening and adjuvant treatment.

RESULTS

The model estimates that the observed reduction in mortality that occurred from 1975 to 2007 attributable to screening, treatment, and both was 20.2%, 25.7%, and 41.0% respectively. The results suggest that, by 2020, breast cancer mortality among Black women in DC could be reduced by 6% more by initiating screening at age 40 vs. age 50. Screening annually may also reduce mortality to a greater extent than biennially, albeit with a marked increase in false positive screening rates.

CONCLUSION

This study demonstrates how modeling can provide data to assist local planners as they consider different cancer control policies based on their individual populations.

摘要

背景

哥伦比亚特区(DC)的黑人女性乳腺癌死亡率在美国最高。当地癌症控制规划者对如何最有效地降低这一死亡率感兴趣。

方法

采用一个既定的模拟模型来反映DC黑人女性的情况,并估计筛查和辅助治疗使用变化的过去和未来影响。

结果

该模型估计,1975年至2007年期间,归因于筛查、治疗以及两者共同作用导致的死亡率下降分别为20.2%、25.7%和41.0%。结果表明,到2020年,与50岁开始筛查相比,DC黑人女性在40岁开始筛查可使乳腺癌死亡率再降低6%。每年进行筛查也可能比每两年进行一次筛查在更大程度上降低死亡率,尽管假阳性筛查率会显著增加。

结论

本研究展示了建模如何能够提供数据,以协助当地规划者根据其各自的人群考虑不同的癌症控制政策。

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本文引用的文献

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Race-specific impact of natural history, mammography screening, and adjuvant treatment on breast cancer mortality rates in the United States.美国自然史、乳腺 X 线筛查和辅助治疗对乳腺癌死亡率的种族特异性影响。
Cancer Epidemiol Biomarkers Prev. 2011 Jan;20(1):112-22. doi: 10.1158/1055-9965.EPI-10-0944. Epub 2010 Nov 30.
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Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms.不同筛查计划下的乳腺 X 线筛查效果:潜在获益和危害的模型评估。
Ann Intern Med. 2009 Nov 17;151(10):738-47. doi: 10.7326/0003-4819-151-10-200911170-00010.
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Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement.
通过患者导航改善乳腺癌治疗结果
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乳腺癌筛查:美国预防服务工作组推荐声明。
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Cost-effectiveness analysis of human papillomavirus vaccination in the Netherlands.荷兰人乳头瘤病毒疫苗接种的成本效益分析
J Natl Cancer Inst. 2009 Aug 5;101(15):1083-92. doi: 10.1093/jnci/djp183. Epub 2009 Jul 1.
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The SPECTRUM population model of the impact of screening and treatment on U.S. breast cancer trends from 1975 to 2000: principles and practice of the model methods.1975年至2000年美国乳腺癌筛查与治疗影响的SPECTRUM人群模型:模型方法的原理与实践
J Natl Cancer Inst Monogr. 2006(36):47-55. doi: 10.1093/jncimonographs/lgj008.
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The Wisconsin Breast Cancer Epidemiology Simulation Model.威斯康星州乳腺癌流行病学模拟模型。
J Natl Cancer Inst Monogr. 2006(36):37-47. doi: 10.1093/jncimonographs/lgj007.
7
Additional common inputs for analyzing impact of adjuvant therapy and mammography on U.S. mortality.用于分析辅助治疗和乳房X线摄影对美国死亡率影响的其他常见输入数据。
J Natl Cancer Inst Monogr. 2006(36):26-9. doi: 10.1093/jncimonographs/lgj005.
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Changing patterns in breast cancer incidence trends.乳腺癌发病率趋势的变化模式。
J Natl Cancer Inst Monogr. 2006(36):19-25. doi: 10.1093/jncimonographs/lgj016.
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Dissemination of adjuvant multiagent chemotherapy and tamoxifen for breast cancer in the United States using estrogen receptor information: 1975-1999.利用雌激素受体信息在美国推广乳腺癌辅助多药化疗和他莫昔芬:1975 - 1999年
J Natl Cancer Inst Monogr. 2006(36):7-15. doi: 10.1093/jncimonographs/lgj003.
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Modeling the dissemination of mammography in the United States.美国乳房X光检查普及情况的建模
Cancer Causes Control. 2005 Aug;16(6):701-12. doi: 10.1007/s10552-005-0693-8.