Population-based absolute risk estimation with survey data.
Population-based absolute risk estimation with survey data.
复制标题
使用调查数据进行基于人群的绝对风险估计。
DOI：
10.1007/s10985-013-9258-4
复制
发表时间：
2014
影响因子：
1.3
通讯作者：
Pfeiffer,RuthM
中科院分区：
文献类型：
--
作者：
Kovalchik,StephanieA;Pfeiffer,RuthM
绝对风险是指在给定的时间间隔内，在存在竞争事件的情况下，特定原因事件发生的概率。我们提出了从一个复杂的调查队列中估计基于人群的绝对风险的方法，该方法可以容纳多种特定暴露的竞争风险。每种事件类型的风险函数由个性化的相对风险乘以基线风险函数组成，基线风险函数用非参数或参数化的分段指数模型建模。采用影响法推导出绝对风险估计的泰勒线性化方差估计。我们引入了新的测量特定原因影响的方法，这些方法可以指导模型中竞争事件组件的建模选择。为了说明我们的方法，我们使用国家健康和营养检查调查的数据建立并验证了心血管和癌症死亡的特定原因绝对风险模型。我们的应用证明了基于调查的风险预测模型在预测健康结果和量化疾病预防计划在人口水平上的潜在影响方面的有效性。
Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level.