Assessing the Impacts of Epidemiologic Biases in WTC Health Studies

描述（由申请人提供）：虽然几乎所有的流行病学研究都涉及一定程度的偏倚，但WTC应答者队列（NY/NJ WTC联盟）的独特特征引起了人们对偏倚在其用于流行病学研究中的潜在影响的担忧。该队列是在9/11事件（2002年4月）后不久建立的，旨在为世贸中心反应人员提供健康筛查，并建立一个快速医疗监测系统。当时，没有明确的程序准则来指导如何快速实施一个医疗筛查系统，在该系统中，数据的收集方式可以在以后用于研究。从那时起，许多问题出现了研究人员试图利用这些队列数据的流行病学研究。这些问题包括：在随访健康监测访视期间多次修订问卷，数据可靠性差（随访期间缺失和不匹配的数据），随访访视的留存率低（失访），以及5个临床中心的健康监测项目转诊至治疗的比率显著降低， 还有其他的前面的例子可能是偏见的根本来源。WTC健康研究经常讨论一些潜在的偏见来解释他们的发现，如健康工人效应，自我选择偏见和回忆偏见。然而，这些研究都没有提供证据证明存在偏见，也没有量化偏见对因果推理的影响。拟议研究的主要目标是通过确定偏见的存在，然后通过量化和调整的偏见影响，以评估流行病学偏见在世贸中心健康研究的影响。为了实现这一目标，我们将评估偏见对四个不同的炎症和严重程度的健康结果的影响：鼻窦炎，哮喘，结节病，创伤后应激障碍。这些健康结果中的每一个都显示了WTC响应者的发病率升高，尽管与WTC暴露的相关性相对较弱。我们假设，通过识别和调整偏差，可以提高WTC健康研究的准确性，可能会加强与健康结果的关联，如我们建议研究的四个。在本研究中，将使用两种方法评价偏倚效应：用于直接量化偏倚效应的内部验证数据和使用已发表的方法或在没有验证数据时量化偏倚效应。虽然不能确定偏倚的“真实”幅度，但可以确定合理的范围，并用于生成偏倚调整后的效应估计值。这些偏差调整后的效应估计值更有可能反映真实的健康影响。成功完成拟定的偏倚分析将 协助其他研究人员通过提供建议来确定偏差的存在并进行调整，从而得出关于世贸中心健康影响的合理推论。此外，该研究将为未来的灾害研究提出指导方针，通过数据解释，最大限度地减少研究设计中的各种偏差。

DESCRIPTION (provided by applicant): While nearly all epidemiologic studies involve a certain level of bias, the unique characteristics of the WTC responder cohort (NY/NJ WTC Consortium) have raised concerns regarding the potential impacts of bias in its use for epidemiologic research. The cohort was established shortly after 9/11 (April 2002) to provide health screenings for WTC responders and to create a rapid medical surveillance system. At that time, there were no clear procedural guidelines for how to quickly implement a medical screening system where data are collected in a manner that can later be used for research. Since then, numerous problems have arisen as researchers attempt to utilize this cohort data for epidemiologic research. These problems include: multiple revisions of questionnaires during follow-up health monitoring visits, poor data reliability (missing and unmatched data across follow-ups), low retention rate for follow-up visits (loss to follow-up), and significantly differet rates of referral to treatment from the health monitoring program across the five clinical centers, among others. The previous examples may be fundamental sources of bias. Often WTC health studies discuss some potential biases to explain their findings, such as the healthy worker effect, self-selection bias, and recall bias. However, none of these studies have provided evidence of the presence of bias, and none have quantified the effect of bias on causal inference. The main goal of the proposed study is to assess the impacts of epidemiologic biases in WTC health studies by identifying the presence of bias and then by quantifying and adjusting for the bias effects. To achieve this goal, we will evaluate the impacts of biases on four differen health outcomes with different latencies and severities: sinusitis, asthma, sarcoidosis, and post-traumatic stress disorder. Each of these health outcomes have shown elevated rates among WTC responders, though the associations with WTC exposure were relatively weak. We hypothesize that by identifying and adjusting for bias, the accuracy of WTC health studies can be improved, potentially strengthening associations with health outcomes like the four we propose to study. In this study, bias effects will be evaluated using two approaches: internal-validation data for direct quantification of bias effects and the utilization of published methods or quantifying bias effects when no validation data are available. While the "true" magnitude of a bias cannot be established with certainty, plausible ranges can be determined and used to generate bias-adjusted estimates of the effects. These bias-adjusted effect estimates are more likely to reflect true health effects. The successful completion of the proposed bias analysis will assist other researchers in drawing plausible inferences on WTC health effects by providing recommendations to identify the presence of, and adjust for bias. In addition, the study will recommend guidelines for future disaster studies which may minimize various sources of bias from the study design through data interpretation.