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在一项基于人群的筛查项目中识别乳腺癌风险增加的女性。

Identification of women at increased risk for breast cancer in a population-based screening program.

作者信息

Bondy M L, Vogel V G, Halabi S, Lustbader E D

机构信息

Community Oncology Program, University of Texas M. D. Anderson Cancer Center, Houston 77030.

出版信息

Cancer Epidemiol Biomarkers Prev. 1992 Jan-Feb;1(2):143-7.

PMID:1306097
Abstract

A multivariate model to assess breast cancer risk was developed by Gail et al. (M. H. Gail, L. A. Brinton, D. B. Byar, D. K. Corle, S. B. Green, C. Schairer, and J. J. Mulvihill, J. Natl. Cancer Inst., 81: 1879-1886, 1989) based on data analysis of the Breast Cancer Detection and Demonstration Project. We evaluated the model's usefulness for assigning women to risk groups for counseling and follow-up by applying it to the 1987 Texas Breast Screening Project data. We identified 3165 women with one or more first-degree relatives affected with breast cancer. The mean risk score for the group was 3.3 (range, 2.7-11.8), indicating a greater than 3-fold elevated risk. The mean risk score for the remaining 27,439 women without affected first-degree relatives was 1.5 (range, 1.24-3.2). Risk perception was found to be a motivator for participation. Women with a risk score greater than 5 perceived themselves to be at high risk for breast cancer. The perception of risk was related to the type of affected first-degree relatives: 80.0% of the women with three affected first-degree relatives and 71.5% of women whose mother and sister were both affected with breast cancer perceived themselves to be at high risk. The Gail model is potentially useful in the clinical setting because women at high risk for breast cancer can be entered into etiological studies, enrolled in primary prevention trials, or referred to programs seeking to improve compliance with screening mammography. The Gail model needs validation, but it is useful for estimating the risk of breast cancer in large populations.

摘要

盖尔等人(M. H. 盖尔、L. A. 布林顿、D. B. 拜尔、D. K. 科尔、S. B. 格林、C. 沙伊勒和J. J. 马尔维希尔,《国家癌症研究所杂志》,81: 1879 - 1886, 1989)基于乳腺癌检测与示范项目的数据分析,开发了一种评估乳腺癌风险的多变量模型。我们将该模型应用于1987年德克萨斯州乳腺癌筛查项目的数据,以评估其在将女性分配到风险组进行咨询和随访方面的实用性。我们确定了3165名有一名或多名患乳腺癌的一级亲属的女性。该组的平均风险评分为3.3(范围为2.7 - 11.8),表明风险升高了3倍以上。其余27439名没有患乳腺癌的一级亲属的女性的平均风险评分为1.5(范围为1.24 - 3.2)。发现风险认知是参与的一个动机。风险评分大于5的女性认为自己患乳腺癌的风险很高。风险认知与受影响的一级亲属类型有关:有三名受影响的一级亲属的女性中有80.0%以及母亲和姐妹都患乳腺癌的女性中有71.5%认为自己处于高风险。盖尔模型在临床环境中可能有用,因为患乳腺癌高风险的女性可以进入病因学研究、参加一级预防试验或被转介到旨在提高乳腺钼靶筛查依从性的项目。盖尔模型需要验证,但它对于估计大量人群中的乳腺癌风险是有用的。

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