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Benefits of Breast Cancer Screening and Treatment on Mortality.

作者信息

Wheeler Stephanie B, Rocque Gabrielle, Basch Ethan

机构信息

Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill.

Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill.

出版信息

JAMA. 2024 Jan 16;331(3):199-200. doi: 10.1001/jama.2023.26730.

DOI:10.1001/jama.2023.26730
PMID:38227044
Abstract
摘要

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Benefits of Breast Cancer Screening and Treatment on Mortality.乳腺癌筛查与治疗对死亡率的益处。
JAMA. 2024 Jan 16;331(3):199-200. doi: 10.1001/jama.2023.26730.
2
[Population-based breast cancer screening is not worthwhile. Screening has little effect on mortality].基于人群的乳腺癌筛查并不值得。筛查对死亡率几乎没有影响。
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Most Women With Early Invasive Breast Cancer Survive.大多数早期浸润性乳腺癌女性患者可存活。
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Screening women at intermediate risk: harm or charm?对中度风险女性进行筛查:有害还是有益?
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Harms from breast cancer screening outweigh benefits if death caused by treatment is included.如果将治疗导致的死亡纳入考量,乳腺癌筛查的危害超过益处。
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6
European breast cancer service screening outcomes: a first balance sheet of the benefits and harms.欧洲乳腺癌筛查服务的结果:收益与危害的首份资产负债表。
Cancer Epidemiol Biomarkers Prev. 2014 Jul;23(7):1159-63. doi: 10.1158/1055-9965.EPI-13-0320.
7
Breast cancer screening halves the risk of breast cancer death: a case-referent study.乳腺癌筛查可使乳腺癌死亡风险减半:一项病例对照研究。
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US breast cancer mortality is consistent with European data.美国乳腺癌死亡率与欧洲数据一致。
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The relative effect of mammographic screening on breast cancer mortality by socioeconomic status.乳腺钼靶筛查对不同社会经济地位人群乳腺癌死亡率的相对影响。
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Screening mammography: There is a golden mammoth in the room!乳腺钼靶筛查:房间里有一头金色的猛犸象! (此译文可能因原文表述比较奇特,实际含义不太明确,需结合更多背景信息理解,正常情况下乳腺钼靶筛查相关内容不太会出现这样奇怪的表述)
Int J Cancer. 2016 Jun 1;138(11):2762. doi: 10.1002/ijc.30000. Epub 2016 Feb 5.

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Deep learning mammography-based breast cancer risk model, its serial change, and breast cancer mortality.基于深度学习乳腺X线摄影的乳腺癌风险模型、其系列变化及乳腺癌死亡率。
Breast Cancer. 2025 Sep 3. doi: 10.1007/s12282-025-01772-w.
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较高的红细胞分布宽度(RDW)与乳腺癌患者全因死亡率和心血管死亡率升高相关:对美国国家健康与营养检查调查(NHANES)数据(1999 - 2018年)的回顾性分析
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