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Semiparametric Methods for Secondary Outcomes in Case-control Studies

病例对照研究中次要结果的半参数方法

基本信息

批准号：
8214692
负责人：
Eric Joel Tchetgen Tchetgen
金额：
$ 21.38万
依托单位：
HARVARD SCHOOL OF PUBLIC HEALTH
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-02-01 至 2014-01-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Modern case-control studies typically involve the collection of data on a large number of variables, often at considerable logistical and monetary expense. These data are of potentially great value to subsequent researchers, who although not concerned with the disease that was the subject of the original study, may want to use the available information towards an analysis of the effects of an exposure on a secondary outcome other than the disease that defined the original case series. A difficulty with re-using data in this way is that the case-control sampling scheme used in the original study will likely induce bias in estimates of log odds ratios and other parameters in the secondary study, if conventional analytical approaches are used. In this proposal, we plan to develop novel statistical methodology for making robust and highly efficient inferences on the effects of an exposure on a secondary outcome under case-control sampling on a different outcome. An important advance is that the proposed methodology applies whether or not sampling probabilities are known to the investigator, and is particularly useful when, as in most observational studies, one needs to adjust for a moderate to large number of confounders. We will use the proposed new methodology to accurately evaluate the effects of lead exposure on the risk of osteoporosis and on decline in cognitive function, using data from the Nurses' Health Study case-control study of lead and hypertension. PUBLIC HEALTH RELEVANCE: Modern case-control studies typically involve the collection of data on a large number of variables, often at considerable logistical and monetary expense. These data are of potentially great value to subsequent researchers, who although not concerned with the disease that was the subject of the original study, may want to use the available information towards an analysis of the effects of an exposure on a secondary outcome other than the disease that defined the original case series. A difficulty with re-using data in this way is that the case-control sampling scheme used in the original study will likely induce bias in estimates of regression parameters in the secondary study, if conventional analytical approaches are used. In this proposal, we plan to develop novel statistical methodology for making robust and highly efficient inferences on the effects of an exposure on a secondary outcome of a categorical or continuous nature, under case-control sampling on a different outcome. An important advance is that the proposed methodology applies whether or not sampling probabilities are known to the investigator. Furthermore, the methods are particularly useful when, as in most observational studies, one needs to adjust for a moderate to large number of confounders, and data on some key covariates may be missing for a subset of subjects. The new methodology will be evaluated via extensive simulation studies, and will be used to accurately assess the effects of lead exposure on the risk of osteoporosis and on decline in cognitive function using data from the Nurse's Health Study case-control study of lead and hypertension.

描述(由申请人提供)：现代病例对照研究通常涉及收集关于大量变量的数据，通常需要花费相当大的后勤和金钱费用。这些数据对后来的研究人员具有潜在的巨大价值，他们虽然不关心最初研究的对象是什么疾病，但可能想要使用可用的信息来分析暴露对次要结果的影响，而不是定义原始病例系列的疾病。以这种方式重复使用数据的一个困难是，如果使用传统的分析方法，原始研究中使用的病例对照抽样方案可能会在二次研究中对对数优势比和其他参数的估计产生偏差。在这项建议中，我们计划开发新的统计方法，在病例对照抽样下对不同的结果进行稳健和高效的推断，以确定暴露对次要结果的影响。一个重要的进步是，无论研究人员是否知道抽样概率，建议的方法都适用，并且在大多数观察性研究中，当需要针对中到大量的混杂因素进行调整时，该方法特别有用。我们将使用建议的新方法来准确评估铅暴露对骨质疏松风险和认知功能下降的影响，使用来自护士健康研究病例对照研究的铅和高血压的数据。公共卫生相关性：现代病例对照研究通常涉及收集关于大量变量的数据，通常需要付出相当大的后勤和金钱费用。这些数据对后来的研究人员具有潜在的巨大价值，他们虽然不关心最初研究的对象是什么疾病，但可能想要使用可用的信息来分析暴露对次要结果的影响，而不是定义原始病例系列的疾病。以这种方式重复使用数据的一个困难是，如果使用传统的分析方法，原始研究中使用的病例对照抽样方案可能会在二次研究中对回归参数的估计产生偏差。在这项建议中，我们计划开发新的统计方法，在病例对照抽样下，对暴露对绝对或连续性质的次要结果的影响做出稳健和高效的推断。一个重要的进步是，无论调查人员是否知道抽样概率，建议的方法都适用。此外，在大多数观察性研究中，当一个人需要对中等到大量的混杂因素进行调整，并且一些关键协变量的数据可能对于一部分受试者来说可能缺失时，这些方法特别有用。新方法将通过广泛的模拟研究进行评估，并将使用护士健康研究中铅与高血压病例对照研究的数据，准确评估铅暴露对骨质疏松症风险和认知功能下降的影响。