Breast Cancer Risk Factors Among Women Aged 75 and Older

描述（由申请人提供）：乳腺癌是最常见的癌症，也是女性癌症死亡的第二大原因。乳腺癌发病率在75-79岁之间达到高峰，75岁以上的女性是美国人口中增长最快的部分。然而，评估筛查性乳房x光检查的随机对照试验中，没有一项包括75岁以上的女性，也不清楚乳房x光检查是否有助于老年女性活得更长。与此同时，过度诊断（诊断出没有威胁的肿瘤）和乳腺癌治疗的危害随着年龄的增长而增加。筛查决定需要根据女性的预期寿命和患乳腺癌的风险来决定。我们之前开发了一个模型来估计老年妇女的预期寿命。我们目前的建议将提供有关老年妇女乳腺癌风险的补充基本信息。Gail模型是最广泛使用的乳腺癌预测模型，它是在少数75岁以下的妇女中开发的（没有80岁以下的妇女），其中包括一些因素（例如，月经初潮），由于这些因素影响雌激素水平的时间已经过去，这些因素对晚年乳腺癌可能不重要。同时，新出现的数据表明，肥胖和骨量增加（雌激素终生升高的标志）可能对老年妇女患乳腺癌的风险有更大的影响，这些因素没有包括在Gail模型中。我们是一个由内科医生、老年病学家、流行病学家、生物统计学家、卫生服务研究人员和肿瘤学家组成的跨学科团队，旨在开发和验证一种新的乳腺癌风险预测模型，该模型适用于75岁以上的女性，优于盖尔模型。我们将使用的数据来自：1)护士健康研究（NHS）和2)妇女健康倡议（WHI）。NHS是一项对121700名年龄在30-55岁之间的护士进行的纵向研究，这些护士每两年接受一次采访。现在参与者的年龄从66岁到91岁不等。1993年至1998年间，WHI在三项临床试验或观察性研究中至少招募了162,000名年龄在50-79岁之间的女性。2005年，约11万名没有乳腺癌病史的妇女同意延长随访时间；我们将把这些女性纳入我们的分析。在NHS和WHI中，反复收集参与者的健康行为和病史数据，包括乳腺癌事件。我们提出以下目标：1)我们将比较盖尔模型在NHS和WHI中75岁以上妇女和更年轻的绝经后妇女之间的表现；2)我们将研究乳腺癌的危险因素是否随年龄的变化而变化，我们将使用竞争风险回归建立一个预测模型，在75岁以上的妇女中乳腺癌；3)我们将在WHI中验证该模型的性能，并将我们的模型与Gail模型的性能进行比较。影响：一个有效的工具来评估晚期乳腺癌的风险是非常需要的，以告知乳房x光检查的决定。随着越来越多的女性活到高龄，我们的工作对于确保乳腺癌筛查的资源得到最佳分配至关重要。我们的工作在改善老年妇女的护理质量和生活质量方面具有巨大潜力。

DESCRIPTION (provided by applicant): Breast cancer is the most common cancer and the second leading cause of cancer death among women. The incidence of breast cancer peaks between ages 75-79 and women >75 years are the fastest growing segment of the US population. However, none of the randomized controlled trials evaluating screening mammography included women >75 years and it is not known whether mammography screening helps older women live longer. Meanwhile, overdiagnosis (diagnosis of tumors that are of no threat) and harms from breast cancer treatment increase with age. Screening decisions need to be informed by a woman's life expectancy and her risk of developing breast cancer. We previously developed a model to estimate older women's life expectancy. Our current proposal will provide the complementary essential information on older women's breast cancer risk. The Gail model, the most widely available breast cancer prediction model, was developed among few women >75 years (none >80) and includes factors (e.g., early menarche) that may not be important for late-life breast cancer due the time that has passed since these factors influenced estrogen levels. Meanwhile, emerging data suggest that obesity and increased bone mass (markers of life-long elevations in estrogen) may have greater impact on older women's breast cancer risk and these factors are not included in the Gail model. We, an interdisciplinary team of internists, geriatricians, epidemiologists, biostatisticians, health servces researchers, and an oncologist, aim to develop and validate a novel breast cancer risk prediction model for women >75 years that outperforms the Gail model. We will use data from: 1) Nurses' Health Study (NHS) and 2) Women's Health Initiative (WHI). The NHS is a longitudinal study of 121,700 nurses aged 30-55 in 1976 who have been interviewed biennially. Participants now range in age from 66-91. The WHI enrolled ~162,000 women ages 50-79 in at least one of three clinical trials or an observational study between 1993 and 1998. In 2005, ~110,000 of these women without a history of breast cancer agreed to extended follow-up; we will include these women in our analyses. In both NHS and WHI, data are repeatedly collected on participants' health behaviors and medical history, including incident breast cancer. We propose the following Aims: 1) We will compare the Gail model's performance between women >75 years and younger postmenopausal women in the NHS and WHI; 2) We will examine whether breast cancer risk factors change with age and we will use competing risks regression to develop a prediction model for breast cancer among women >75 years; and 3) We will validate the performance of this model in the WHI and will compare the performance of our model with the Gail model. Impact: A valid tool to assess late-life breast cancer risk is greatly needed to inform mammography screening decisions. As more women are living to advanced age, our work is crucial to ensure that resources around breast cancer screening are allocated optimally. Our work has great potential to improve quality of care and quality of life for older women.