Ms. LILAC: Muscle Mass in the Life and Longevity After Cancer (LILAC) Study

摘要 有新的证据表明，癌症及其治疗可能会加速正常衰老。 这一过程，增加了功能能力下降的幅度和速度。这加速了 假设衰老过程会加速常见的与年龄相关的不良反应的发生 癌症幸存者的结果，包括肌肉质量的丧失和身体功能的下降。 然而，没有数据描述与年龄相关的肌肉质量损失及其与生理因素的关系 对癌症幸存者的长期作用。该项目将直接解决三个关键问题 癌症存活率研究的方法学挑战：1)获得准确的测量方法 在居住在社区老年人中的以人口为基础的大型队列中的骨骼肌群，2) 解开年龄与癌症对肌肉质量、体力之间关系的影响 功能(步态速度、平衡、力量)和功能衰退；3)大样本量 需要了解使用大数据预测低肌肉质量的因素(机器学习) 接近了。将使用D3-肌酸稀释法(D3Cr)直接测量 远程肌肉质量，使用先前已在临床和 流行病学研究。这项研究将测量6614名参与者(3044名)的D3Cr肌质量 癌症幸存者和3570名无癌对照)在妇女健康倡议(WHI)，一个大型的 随访超过25年的绝经后妇女前瞻性队列研究(n=161,808)。 参与者将从嵌入WHI的两个子队列中使用事件 密度抽样法。癌症幸存者将从现有的NCI资助的 生存队列、癌症后寿命和长寿(Lilac)队列和无癌对照 将来自WHI长寿命研究2。这项申请的总体目标是 研究癌症幸存者低肌肉质量的前因和后果，使用 创新的方法，以克服癌症研究中常见的主要偏见来源。这项研究 目标是：1)创建年龄标准化肌肉质量百分位数曲线和z分数，以 描述癌症幸存者和非癌症对照组D3肌肉质量的分布，2) 比较癌症幸存者和非癌症患者的肌肉质量、身体功能和功能下降 癌症控制，以及3)使用机器学习方法来生成多变量风险预测 检测低肌肉质量的算法。该项目解决了由 NCI用于老年和长期癌症幸存者的研究。这项研究的结果将用于 制定干预措施以减轻老年人低肌肉质量的有害影响 促进老年(&gt；65)和高龄(&gt；85)年龄组癌症幸存者的健康生存。

ABSTRACT There is emerging evidence that cancer and its treatments may accelerate the normal aging process, increasing the magnitude and rate of decline in functional capacity. This accelerated aging process is hypothesized to hasten the occurrence of common adverse age-related outcomes in cancer survivors, including loss of muscle mass and decrease in physical function. However, there is no data describing age-related loss of muscle mass and its relation to physical function in the long-term in cancer survivors. This project will directly address three key methodological challenges in research on cancer survivorship: 1) obtaining accurate measures of skeletal muscle mass in large population-based cohorts of community dwelling older adults, 2) disentangling the effect of age versus cancer on the relationship between muscle mass, physical function (gait speed, balance, strength), and functional decline, and 3) the large sample size required to understand predictors of low muscle mass using big data (machine learning) approaches. The D3-creatine dilution method (D3Cr) will be used to obtain a direct measure of muscle mass remotely, using a protocol that has been previously validated in clinical and epidemiologic research. This study will measure D3Cr muscle mass in 6614 participants (3044 cancer survivors and 3570 cancer-free controls) in the Women’s Health Initiative (WHI), a large prospective cohort study (n=161,808) of postmenopausal women with over 25 years of follow-up. Participants will be drawn from two sub-cohorts embedded within the WHI using an incidence density sampling approach. Cancer survivors will be drawn from an existing NCI-funded survivorship cohort, the Life and Longevity After Cancer (LILAC) cohort, and cancer-free controls will be drawn from the WHI Long Life Study 2. The overall objective of this application is to examine the antecedents and consequences of low muscle mass in cancer survivors, using innovative methods to overcome major sources of bias common in cancer research. The study aims are to: 1) create age-standardized muscle mass percentile curves and z-scores to characterize the distribution of D3- muscle mass in cancer survivors and non-cancer controls, 2) compare muscle mass, physical function, and functional decline in cancer survivors and non- cancer controls, and 3) use machine learning approaches to generate multivariate risk-prediction algorithms to detect low muscle mass. This project addresses an urgent need identified by the NCI for research in older and long-term cancer survivors. The results of this study will be used to develop interventions to mitigate the harmful effects of low muscle mass in older adults and promote healthy survivorship in cancer survivors in the old (>65) and oldest-old (>85) age groups.