Breast Cancer Risk Factors Among Women Aged 75 and Older

描述(申请人提供)：乳腺癌是女性最常见的癌症，也是导致癌症死亡的第二大原因。乳腺癌的发病率在75-79岁之间达到高峰，而75岁的女性是美国人口中增长最快的部分。然而，评估筛查乳房X光检查的随机对照试验中没有一项包括75岁的女性，目前尚不清楚乳房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(对不具威胁的肿瘤的诊断)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她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女性的预期寿命。我们目前的提案将提供有关老年妇女乳腺癌风险的补充基本信息。Gail模型是应用最广泛的乳腺癌预测模型，它是在少数75岁女性(非80岁女性)中开发的，它包含了一些因素(例如，月经初潮)，这些因素对晚期乳腺癌可能并不重要，因为这些因素影响雌激素水平的时间已经过去了。与此同时，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)可能对老年女性患乳腺癌的风险有更大的影响，而这些因素没有包括在盖尔模型中。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针对75岁女性的乳腺癌风险预测模型，该模型的性能优于Gail模型。我们将使用来自：1)护士健康研究(NHS)和2)妇女健康倡议(WHI)的数据。NHS是一项纵向研究，1976年对121,700名年龄在30-55岁的护士进行了两年一次的采访。参与者现在的年龄从66岁到91岁不等。WHI在1993至1998年间招募了约162,000名年龄在50-79岁之间的女性参加了至少三项临床试验或观察性研究中的一项。2005年，在这些没有乳腺癌病史的妇女中，约有11万人同意延长随访；我们将把这些妇女包括在我们的分析中。在NHS和WHI中，参与者的健康行为和病史(包括乳腺癌事件)的数据都被反复收集。我们提出了以下目标：1)我们将比较Gail模型在NHS和WHI中75岁女性和更年轻的绝经后女性中的表现；2)我们将检查乳腺癌风险因素是否随年龄变化，我们将使用竞争风险回归来开发一个预测75岁女性乳腺癌的模型；3)我们将验证该模型在WHI中的表现，并将我们的模型与Gail模型的表现进行比较。影响：需要一种有效的工具来评估老年乳腺癌风险，以便为乳房X光检查决策提供信息。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的潜力。

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.