Statistical methods for vitamin D targets for functional outcomes in older adults

 描述(由申请人提供)：老年人维持最佳身体功能所需的25-羟基维生素D[25(OH)D]浓度尚不清楚。医学研究所和内分泌学会分别就20 ng/ml或30 ng/mL作为骨骼健康的目标进行了公开辩论，但两个小组都同意，需要更有力的证据来确定骨骼外结果的目标浓度，例如跌倒和身体功能。问题很明显：25%的老年人身体机能不佳，50%的25(OH)D浓度在20到30 ng/ml之间。为老年人确定25(OH)D目标将通过为维生素D补充试验的设计和分析提供信息而立即产生影响。也就是说，目标充当纳入/排除标准或基线分组，并作为次要成果。我们的解决方案是使用现有的NIH资助的数据集，经验地识别和验证老年人(=65岁)中与跌倒风险和更好的身体功能相关的特定性别(可能按其他因素分层；例如，种族、遗传变异)的25(OH)D目标。严峻的挑战 25(OH)D不能随机化；因此，观测数据是解决方案的关键部分。传统的统计方法不能很好地解决这个问题；因此，我们将发展 通过调整和改进结构建模和机器学习方法，采用新的统计方法，并将它们应用于我们的目标。我们将使用包括12,500名老年人的4项前瞻性队列研究来实现这些目标：健康、老龄化和身体成分、基安蒂红酒中的Invechiare、男性的骨质疏松性骨折以及骨质疏松性骨折的研究。我们将：1)确定和验证25(OH)D目标，用于减少跌倒、活动能力、日常生活活动和日常生活的工具性活动(功能结果)；以及步态速度、肌肉力量和 脆弱(近端条件)(目标1)；2)表征25(OH)D以及血清钙和磷浓度对功能结果/近端条件的联合影响(目标2)；以及3)量化内分泌和代谢因素(甲状旁腺素、血清碱性磷酸酶、阿卡托品、成纤维细胞生长因子23)对功能结果/近端条件的调节作用(目标3)。我们将用SAS和R统计语言编写代码，并将其分发给科学 用于其他研究的社区。

 DESCRIPTION (provided by applicant): The concentration of 25-hydroxyvitamin D [25(OH)D] needed for older adults to maintain optimal physical function is unknown. Institute of Medicine and Endocrine Society have publicly debated on 20 ng/mL or 30 ng/mL, respectively, as targets for skeletal health, but both groups agree that stronger evidence is needed to identify target concentrations for extra-skeletal outcomes, e.g., falls and physical function. The problem is significant: >25% of older adults have poor physical function, 50% have 25(OH)D concentrations between 20 and 30 ng/mL. Identifying 25(OH)D targets for older adults will have immediate impact by informing design and analysis of vitamin D supplementation trials. Namely, targets serve as inclusion/exclusion criteria or baseline subgroups and as secondary outcomes. Our solution is to empirically identify and validate sex-specific (possibly stratified by other factors; e.g., race, genetic variants) 25(OH)D targets in older adults (= 65 years) related to lowe risk of falls and better physical function using existing NIH-funded datasets. A critical challenge is that 25(OH)D cannot be randomized; therefore observational data are a crucial part of the solution. Conventional statistical methods are ill-equipped for this problem; thus, we will develop novel statistical methods by adapting and refining structural modeling and machine-learning methods, and apply them to our aims. We will carry out the aims using 4 prospective cohort studies comprising >12,500 older adults: Health, Aging, and Body Composition, Invecchiare in Chianti, Osteoporotic Fractures in Men, and Study of Osteoporotic Fractures. We will: 1) identify and validate 25(OH)D targets for falls reduction, mobility, activities of daily living, and instrumental activities of daily living (functional outcomes); and gait speed, muscle strength, and frailty (proximal conditions) (aim 1); 2) characterize the joint impact of 25(OH)D and serum calcium and phosphorus concentrations on functional outcomes/proximal conditions (aim 2); and 3) quantify mediation of 25(OH)D on functional outcomes/proximal conditions by endocrine and metabolic factors (PTH, serum alkaline phosphatase, aklotho, fibroblast growth factor 23) (aim 3). We will write code in SAS and R statistical languages and disseminate it to the scientific community for use in additional research.