Lifestyle and Molecular Factors of Bone Health in Breast Cancer Survivors

描述（由申请方提供）：芳香酶抑制剂（AI）已迅速取代他莫昔芬（TAM），作为诊断为激素受体（HR）阳性的早期乳腺癌绝经后女性的一线辅助激素治疗。与TAM相比，AI引发的严重雌激素耗竭是改善结局的原因，但AI治疗会对骨骼健康产生负面影响，提高绝经后女性骨折的高风险。老年骨质疏松性骨折可导致死亡率显著增加，生活质量差，医疗费用惊人。尽管有这些结果，绝经后乳腺癌患者服用AI的骨折风险因素仍然令人惊讶地研究不足。到目前为止，没有有效的工具存在骨折风险评估特定的绝经后妇女开始前AI治疗。 本申请要求首次对2,062例在Pathways研究中接受AI治疗的绝经后乳腺癌患者进行骨健康前瞻性研究，Pathways研究是一项在Kaiser Permanente北方加州（KPNC）医疗护理项目中进行的乳腺癌预后前瞻性队列研究，入组时间为2006-2013年，随访时间为2016年。途径的建立与AI广泛取代TAM作为绝经后患者的激素治疗同时进行。通过利用Pathways中与高质量生物标本相关的丰富的流行病学，临床和药学数据，我们有一个独特的机会对乳腺癌患者中AI相关骨折进行首批深入研究之一。在接受AI治疗早期HR阳性乳腺癌的绝经后妇女中，我们将研究骨折（主要结局）和骨质疏松症（次要结局）的风险与1）可改变的生活方式因素，如体力活动，饮食，维生素D和钙补充剂的使用， 吸烟和饮酒; 2）雌激素和骨代谢途径的生殖系遗传变异，使用全基因组分析验证结果; 3）血清生物标志物的相关性，包括骨形成的BAP和再吸收的TRAP 5 b，六种关键调节细胞因子（RANKL，OPG，IL 1，IL 6，TNF？，CSF）和25-羟基维生素D。最后，将根据生活方式因素、遗传变异和血清生物标志物，开发接受AI治疗的绝经后乳腺癌患者骨折风险的预测模型，并与一般健康人群的模型进行比较。 今天，超过250万患有乳腺癌的女性生活在美国，2011年估计有230，000例新诊断病例。据估计，绝经后幸存者与健康对照组相比，每年有超过13，000例骨折。因此，了解AI治疗对骨骼结局风险的健康影响具有重要的公共卫生意义。在Pathways研究中，我们现在有一个特殊的机会来解决乳腺癌生存研究中的一个重要空白，并在现实世界的临床环境中减少AI诱导的骨质疏松性骨折的负担。

DESCRIPTION (provided by applicant): Aromatase inhibitors (AIs) have been rapidly replacing tamoxifen (TAM) as first-line adjuvant hormonal therapy for postmenopausal women diagnosed with hormone receptor (HR)-positive, early-stage breast cancer. The profound estrogen depletion triggered by AIs is responsible for improved outcomes compared to TAM, yet AI therapy can negatively impact bone health, elevating the already high risk of fractures in postmenopausal women. Osteoporotic fractures at older age can result in markedly increased mortality, poor quality of life, and staggering healthcare costs. Despite these outcomes, risk factors for fracture specific to postmenopausal breast cancer patients taking AIs remain surprisingly understudied. To date, no validated tools exist for fracture risk assessment specific to postmenopausal women prior to initiation of AI therapy. This application requests to conduct for the first time a prospective study on bone health in 2,062 postmenopausal breast cancer patients who received AI therapy in the Pathways Study, a prospective cohort study of breast cancer prognosis in the Kaiser Permanente Northern California (KPNC) Medical Care Program, enrolled from 2006-2013 and followed through 2016. The establishment of Pathways was concurrent with AIs widely replacing TAM as hormonal therapy for postmenopausal patients. By leveraging a rich body of epidemiologic, clinical and pharmacy data linked with high-quality biospecimens in Pathways, we have a unique opportunity to conduct one of the first in-depth studies of AI-associated fractures in breast cancer patients. Among postmenopausal women who received AI therapy for early-stage, HR-positive breast cancer, we will investigate the risk of fractures (primary outcome) and osteoporosis (secondary outcome) in association with 1) modifiable lifestyle factors such as physical activity, diet, vitamin D and calcium supplement use, smoking, and alcohol consumption; 2) germline genetic variations in estrogen and bone metabolism pathways with validation of findings using genome-wide assays; and 3) the associations of serum biomarkers, including BAP for bone formation and TRAP5b for resorption, six key regulatory cytokines (RANKL, OPG, IL1, IL6, TNF¿, CSF), and 25-hydroxyvitamin D. Finally, a prediction model for fracture risk in postmenopausal breast cancer patients on AI therapy will be developed based upon lifestyle factors, genetic variations, and serum biomarkers and compared with models intended for the general healthy population. Over 2.5 million women with breast cancer live in the U.S. today, with an estimated 230,000 newly diagnosed cases in 2011. An excess of 13,000 fractures per year has been estimated among postmenopausal survivors compared to their healthy counterparts. Therefore, understanding the health effects of AI therapy on risk of skeletal outcomes is of great public health importance. In the Pathways Study, we now have an exceptional opportunity to address an important gap in breast cancer survivorship research, and to reduce the burden of AI-induced osteoporotic fractures in a real-world clinical setting.