Fracture Risk Prediction After Age 80 Years

80 岁后骨折风险预测

• 批准号: 10266823
• 负责人: KRISTINE ENSRUD
• 金额: $ 16.5万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10266823
• 关键词: Accounting; Achievement; Address; Adult; Age; Aged, 80 and over; Aging; Assessment tool; Body Composition; Bone Density; Calibration; Cessation of life; Characteristics; Chronic; Clinical; Cohort Studies; Communities; Data; Discrimination; Elderly; Electronic Health Record; Enrollment; Epidemiology; Equilibrium; Ethnic Origin; Event; Fall prevention; Fracture; Gait speed; Guidelines; Health; Health Status; Height; High Prevalence; Hip Fractures; Hip region structure; Individual; Intervention; Lead; Life; Life Expectancy; Longitudinal Studies; Measurement; Measures; Medical; Modeling; Morbidity - disease rate; Osteoporosis; Participant; Patients; Performance; Pharmacotherapy; Phenotype; Polypharmacy; Population; Predictive Value; Prevention; Prevention Measures; Prevention approach; Prevention strategy; Probability; Race; Recording of previous events; Risk; Risk Assessment; Risk Factors; Role; Subgroup; Testing; Time; United States; Vital Status; Weight; Woman; aged; base; bone aging; clinical decision-making; clinical practice; clinical risk; cost; disability; experience; falls; fracture risk; frailty; functional outcomes; high risk; hip bone; improved; individual patient; lifetime risk; male health; men; middle age; mortality; mortality risk; multiple chronic conditions; osteoporosis with pathological fracture; patient population; patient subsets; practice setting; predictive modeling; response; risk prediction; risk sharing; screening; secondary analysis; sex; tool

The majority of clinical fractures including hip fractures occur among adults aged 80 years and older, but there is a paucity of evidence to guide assessment of fracture risk versus competing mortality risk in this expanding patient population. Clinicians have difficulty identifying late life patients who are at highest risk of fracture since expected survival strongly impacts this risk. No currently available fracture risk assessment tool adequately addresses important issues relevant to fracture prediction in the oldest old, including selection of appropriate timeframes for fracture prediction, inclusion of key risk factors for late life fractures and mortality, and consideration of a patient's competing mortality risk given his/her set of risk factors. Our preliminary data suggests that addition of non-skeletal risk factors such as the frailty phenotype to a fracture prediction model will improve its performance in late life adults. Thus, there is a critical need for pragmatic fracture risk assessment models that better identify women and men in the 9th and 10th decades of life at high risk of fracture. Our study will combine comprehensive data collected in three large epidemiologic cohorts (Study of Osteoporotic Fractures [SOF]; Osteoporotic Fractures in Men Study [MrOS]; Health Aging and Body Composition Study [Health ABC]) to yield fracture prediction models in community-dwelling women and in men aged 80 years and older that clearly define relationships between individual and combined risk factors for fracture accounting for the competing risk of mortality and demonstrate superior performance to that of existing tools. We will generate estimates of 5-year and lifetime risks considering relevant late life non-skeletal predictors of both fracture and mortality including multimorbidity, functional limitations, polypharmacy, the frailty phenotype and its components such as shrinking, weakness and slowness. In addition, we will evaluate the role of BMD in fracture prediction including its interaction with late life non-skeletal risk factors. Valid lifetime risk assessment with adequate consideration of a patient's competing mortality risk is warranted to identify those at highest risk of fracture prior to death. In addition, a 5-year prediction time frame among these high risk patients accounting for competing mortality risk is needed for clinical decision making given the anticipated time horizon of benefit of interventions to lower fracture risk and reduced life expectancy. Successful achievement of our aims will improve clinical decision making by clearly identifying higher risk patient subgroups who should be targeted for fracture screening and prevention approaches as fracture risk is high despite consideration of competing mortality risk and lower risk subgroups where these strategies may have minimal benefit as competing risk of death far outweighs fracture risk. These results are essential to guide fracture risk assessment and shared clinical decision making in this rapidly growing segment of the US population with its high burden of shared risk factors for both fracture events and competing non-fracture related mortality.

包括髋部骨折在内的大多数临床骨折发生在80岁及以上的成年人中， 缺乏证据来指导骨折风险与竞争性死亡风险的评估， 患者人群。临床医生很难确定老年患者谁是骨折的最高风险，因为 预期存活率强烈影响该风险。目前没有适当的骨折风险评估工具 解决了与最古老的裂缝预测相关的重要问题，包括选择合适的 骨折预测的时间框架，包括晚年骨折和死亡率的关键风险因素，以及 考虑到患者的一系列风险因素，患者的竞争性死亡风险。我们的初步数据 提示在骨折预测模型中加入非骨骼危险因素如脆弱表型 将改善其在老年人中的表现。因此，迫切需要务实的骨折风险 评估模型，更好地确定妇女和男子在第9和第10个几十年的生活在高风险的 骨折我们的研究将结合联合收割机在三个大型流行病学队列中收集的综合数据（ 骨质疏松性骨折[SOF];男性骨质疏松性骨折研究[MrOS];健康、老化和身体 组成研究[健康ABC]），以产生社区居住妇女和男子的骨折预测模型 年龄在80岁及以上，明确定义个体和综合风险因素之间的关系， 骨折占死亡率的竞争风险，并表现出优于现有的上级性能 工具.我们将在考虑相关晚期非骨骼疾病的情况下估计5年和终生风险 骨折和死亡率的预测因素包括多发病、功能受限、多药治疗、 表型及其组成部分，如萎缩，虚弱和缓慢。此外，我们将评估 BMD在骨折预测中的作用，包括其与晚年非骨骼危险因素的相互作用。有效寿命 充分考虑患者的竞争性死亡风险的风险评估是必要的， 死亡前骨折风险最高的人此外，在这些高风险中， 考虑到预期的死亡风险，临床决策需要考虑竞争性死亡风险的患者 降低骨折风险和缩短预期寿命的干预措施的受益时间范围。成功 我们目标的实现将通过明确识别高风险患者来改善临床决策 由于骨折风险高，应针对骨折筛查和预防方法的亚组 尽管考虑到竞争性死亡风险和风险较低的亚组，这些策略可能 受益极小，因为死亡竞争风险远远超过骨折风险。这些结果对于指导 骨折风险评估和共享的临床决策在这个快速增长的部分，美国 骨折事件和竞争性非骨折事件共同风险因素负担高的人群 相关死亡率。