Enhancing the Utility of the Trend-in-Trend Research Design

患者、临床医生和政策制定者通常需要关于药物和其他药物的真实效果的有效信息 曝光有明显的时间-使用趋势。例如，罗非昔布的使用量迅速增长 21世纪初和2000-2013年外源性睾丸素的增加伴随着对知识的迫切需求 关于这些药物对心血管的影响。随机试验很少招募足够数量的受试者，或跟随 足够长的时间，以检查与罕见结果的关联。因此，需要进行非随机研究，甚至 尽管他们很容易受到无法测量的混杂和其他形式的偏见的影响。要解决这些可用的限制， 流行病学设计，我们最近引入了趋势设计：一种新的、混合的流行病学-生态研究 适用于设计时有突出使用趋势的书房曝光。大幅增加 需要发展，以实现趋势研究设计对公众健康的全面影响。最需要的领域 发展包括：评估用于实时上市后安全监测的序贯分析扩展； 对机器学习的评估，以确定趋势设计的潜在累积曝光概率 模型；剂量-反应关系的评估；以及基于基线的治疗效果异质性评估 病人的特征。对于这些方法论需求中的每一种，我们都提出了一种方法：1)评估其 统计性质，特别是通过渐近性和有限样本统计能力的大样本有效性；2) 评估其在深入的模拟研究中的性能；以及3)使用已知的关联来验证该方法 罗非昔布-急性心肌梗死之间的医疗保健数据。最后，我们将把这些发展应用于 心血管、脑血管和血栓栓塞症的影响这一悬而未决的重要问题 男性体内的外源性睾丸素。 这项研究将通过极大地扩展一种新的实用程序，对科学、临床和公共卫生产生广泛的影响 流行病学研究设计，具有证明的有效性，适用于广泛的暴露和 使用趋势突出。它还将评估外源性睾丸素的安全性，这是一个巨大的临床和 公共卫生的重要性。检查处方药的安全性是这一方法的一个极其重要的应用 有可能造福数百万人的设计。由于趋势设计也适用于非药物 具有明显时间趋势的暴露(例如，医疗程序、生活方式因素、环境暴露等)； 它对人口的潜在影响甚至更广泛。

Patients, clinicians, and policymakers often need valid information about the real-world effects of drugs and other exposures for which there have been pronounced time-trends in use. For example, the rapid growth in the use of rofecoxib in the early 2000s and of exogenous testosterone from 2000–2013 was accompanied by an urgent need for knowledge about the cardiovascular effects of those drugs. Randomized trials seldom enroll a sufficient number of subjects, or follow them long enough, to examine associations with rare outcomes. Therefore, non-randomized studies are needed, even though they are susceptible to unmeasured confounding and other forms of bias. To address these limitations of available epidemiologic designs, we recently introduced the trend-in-trend design: a novel, hybrid epidemiologic-ecologic research design that is applicable when there is a prominent trend in the use of the study exposure. Substantial additional development is needed to realize the full public health impact of the trend-in-trend research design. Areas in most need of development include: evaluation of a sequential analysis extension for real-time post-marketing safety surveillance; evaluation of machine learning to specify the trend-in-trend design’s underlying cumulative probability of exposure model; evaluation of dose-response relationships; and evaluation of treatment effect heterogeneity based on baseline patient characteristics. For each of these methodologic needs, we propose an approach for which we will: 1) assess its statistical properties, in particular large-sample validity through asymptotics and finite sample statistical power; 2) evaluate its performance in thorough simulation studies; and 3) proof-test the approach using the known association between rofecoxib-acute myocardial infarction in healthcare data. Finally, we will apply these developments to the unresolved and highly important question of the cardiovascular, cerebrovascular, and thromboembolic effects of exogenous testosterone in men. This study will have broad scientific, clinical, and public health impact by greatly extending the utility of a novel epidemiologic research design with demonstrated validity and is applicable to a broad range of exposures with a prominent trend in use. It will also evaluate the safety of exogenous testosterone, a question of tremendous clinical and public health importance. Examining the safety of prescription drugs is one enormously important application of this design that has the potential to benefit many millions of people. As the trend-in-trend design is also applicable to non-drug exposures that have a pronounced time-trend (e.g., medical procedures, lifestyle factors, environmental exposures, etc.), its potential impact on the population is even broader.