Statistical Methods for Causal Inference in Observational Studies

 描述(申请人提供)：该项目的目标是开发观察性研究中因果推断的创新统计方法，除了选择偏差外，还可以处理时变混杂因素、死亡审查和缺失数据，并回答有关肌萎缩侧索硬化症(ALS)疾病管理的重要临床问题。现有的解决这些问题的研究有几个局限性，包括样本量小到中等，使用的临床数据和统计方法有限，不能充分解决复杂的问题，包括观察性研究中经常遇到的选择偏差。这项研究将使用来自埃默里肌萎缩侧索硬化症注册中心的数据，这些数据具有几个显著的优势，包括对1700多名患者进行长期随访的大样本，以及自1997年以来每次就诊时收集的广泛临床信息。因此，Emory ALS注册中心特别适合回答重要的临床问题。对肌萎缩侧索硬化症注册表的分析提出了几个挑战，包括时变的混杂因素、死亡审查和丢失数据。现有的统计方法不能直接用来解决所有这些问题。这些考虑导致了三个具体目标：1)开发一个新的倾向评分来平衡观察性研究中的时变协变量，即倾向过程，并开发基于倾向过程的估计因果效应的统计方法；2)开发统计方法来评估带有时变协变量的观察性研究中存在缺失数据的幸存者平均因果影响(SACE)；以及3)通过广泛的模拟对AIMS 1和2中建议的方法进行系统评估，并对Emory ALS注册中心的数据进行分析。所有AIMS的进展将由Emory ALS注册中心和广泛的模拟研究指导和评估。所提出的方法将使我们能够回答重要的临床问题，例如评估包括经皮内窥镜胃造口术(PEG)和无创正压通气(NIPPV)在内的操作对患者预后的影响。拟议的方法是一般性的，并有望为广泛的观察性研究和登记册带来类似的好处，因为在这些类型的研究中经常遇到类似的数据结构和分析问题。

 DESCRIPTION (provided by applicant): The goal of this project is to develop innovative statistical methods for causal inference in observational studies that can handle time-varying confounders, censoring by death, and missing data in addition to selection bias, and to answer important clinical questions on management of the Amyotrophic Lateral Sclerosis (ALS) disease. The existing studies on addressing these questions have several limitations including their small to moderate sample sizes and the use of limited clinical data and statistical methods that did not adequately address complicating issues including selection bias commonly encountered in observational studies. This study will use the data from the Emory ALS Registry with several notable strengths including a large sample size of over 1,700 patients with long-term follow-ups and collection of extensive clinical information at each clinic visit since 1997. A a result, the Emory ALS Registry is uniquely suited for answering important clinical questions. The analysis of the ALS Registry presents several challenges including time-varying confounders, censoring by death, and missing data. The existing statistical methods cannot be applied directly to address all these issues. These considerations lead to three specific aims: 1) develop a new propensity score for balancing time-varying covariates in observational studies, the propensity process, and develop statistical methods for estimating causal effects based on the propensity process; 2) develop statistical methods for assessing the survivor average causal effects (SACE) in the presence of missing data in observational studies with time-varying covariates; and 3) perform systematic evaluation of the proposed methods in Aims 1 and 2 through extensive simulations and perform analysis of the Emory ALS Registry data. Progress in all aims will be guided by and evaluated on the Emory ALS Registry, and by extensive simulation studies. The proposed methods will enable us to answer important clinical questions, e.g., assessing the effects of procedures including the percutaneous endoscopic gastrostomy (PEG) and the non-invasive positive pressure ventilation (NIPPV) on patient outcomes. The proposed methods are general and promise similar benefits to a wide range of observational studies and registries, since similar data structures and analytical issues are often encountered in these types of studies.