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Variation in Breast Cancer Risk Model Estimates Among Women in Their 40s Seen in Primary Care

医学 乳腺癌 置信区间 卡帕 科恩卡帕 乳腺摄影术 相对风险 妇科 风险评估 人口学 指南 一致性 终身风险 癌症 产科 内科学 统计 哲学 语言学 数学 计算机安全 病理 社会学 计算机科学
作者
Mara A. Schonberg,Maria Karamourtopoulos,Adlin Pinheiro,Roger B. Davis,Scot B. Sternberg,Tejas S. Mehta,Elizabeth A. Gilliam,Nadine Tung
出处
期刊:Journal of Womens Health [Mary Ann Liebert, Inc.]
卷期号:31 (4): 495-502 被引量:3
标识
DOI:10.1089/jwh.2021.0299
摘要

Background: The Gail, Breast Cancer Surveillance Consortium (BCSC), and Tyrer-Cuzick breast cancer risk prediction models are recommended for use in primary care. Calculating breast cancer risk is particularly important for women in their 40s when deciding on mammography, with some guidelines recommending screening for those with 5-year risk similar to women age 50 (≥1.1%). Yet, little is known about risk estimate agreement among models for these women. Materials and Methods: Four hundred nine Boston-area women 40-49 years of age completed a risk questionnaire before a primary care visit to compute their breast cancer risk. The kappa statistic was used to examine when (1) Gail and BCSC agreed on 5-year risk ≥1.1%; (2) Gail estimated 5-year risk ≥1.7% and Tyrer-Cuzick estimated 10-year risk ≥5% (guideline thresholds for recommending prevention medications); and when (3) Gail and Tyrer-Cuzick agreed on lifetime risk ≥20% (threshold for breast MRI using Tyrer-Cuzick). Results: Participant mean age was 44.1 years, 56.7% were non-Hispanic white, and 7.8% had a first-degree relative with breast cancer. Of 266 with breast density information to estimate both Gail and BCSC, the models agreed on 5-year risk being ≥1.1% for 36 women, kappa = 0.34 (95% confidence interval: 0.23-0.45). Gail and Tyrer-Cuzick estimates led to agreement about prevention medications for 8 women, kappa 0.41 (0.20-0.61), and models agreed on lifetime risk ≥20% for 3 women, kappa 0.08 (-0.01 to 0.16). Conclusions: There is weak agreement on breast cancer risk estimates generated by risk models recommended for primary care. Using different models may lead to different clinical recommendations for women in their 40s.

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