Development of Clinical Prediction Models for Pulmonary Outcomes in Sarcoidosis

项目摘要 这项建议的目的是开发临床预测工具，以对患者进行风险分层 肺结节病。因为结节样炎症的病程甚至会持续很多年 在那些患有自限性结节的人中，缺乏预后指标来发展 管理计划对患者和医生来说都不是一个微不足道的问题。因此，如果没有 预测工具，临床医生将无法改善他们提供的纵向护理 临床上使用的结果类型。这项研究的构思是由 初步数据显示，与干扰素相关的血液蛋白质和RNA转录本的水平 用COX比例风险预测炎症对未来肺功能下降的预测 模特儿。研究设计的一个重要特征是关注临床相关的结果 和临床变量，以便结果可以立即转化为临床实践。这个目标 在目标1中实现，我们将提供性能最好的临床预测模型，该模型依赖于 仅根据临床可用数据和实验室测试来预测用于肺疾病的临床结果 临床以确定结节病的疾病进展。这一结果是临床上有意义的下降。 在肺功能方面。在目标2中，我们将衡量加入新型血基材料的附加值 将干扰素相关标志物纳入临床预测模型。这一目标的目标是确定 哪些新的标志物应该被开发并进入临床舞台以用于结节病 预言。最后，在目标3中，我们将把这些模型应用于一个重要的临床管理。 结节病中的问题，即为特定患者确定最佳监测频率。 解决最后一个问题是朝着更好地预测疾病迈出的第一步 在广泛的器官损伤发生之前进展。结节病调查小组是 非常有资格进行这项研究，因为他们有进行结节病的记录 临床研究，有持续的合作，并参与了先前的研究，包括 包括NIH赞助的联盟研究在内的患者的生物胺收集。执行，执行 在这项研究中，研究人员将贡献来自357个纵向生物样本和临床数据 美国各地中心的纵向队列中登记的结节病患者。 将再招募200名患者，并对其进行长达39个月的跟踪调查，从而实现 总样本量为557人，其中大部分将是非裔美国人。我们的团队还包括一名 独一无二的合格生物统计学家查尔斯·麦卡洛克博士，他开创了 我们将使用纵向建模方法。因此，提出的目标具有很高的 解决这一拖延已久的临床问题的成功可能性。

PROJECT ABSTRACT The purpose of this proposal is to develop clinical prediction tools to risk stratify patients with pulmonary sarcoidosis. Because the course of sarcoidal inflammation lasts for many years even in those with self-limiting sarcoid, the lack of prognostic indicators upon which to develop a management plan is not a trivial issue for both patient and physician. Thus, without prognostication tools, clinicians will not be able to improve the longitudinal care they provide for the types of outcomes that are used in the clinic. The conception of this study was motivated by the preliminary data showing that levels of blood protein and RNA transcripts related to interferon inflammation were predictive of future declines in lung function using Cox proportional hazards modeling. An important feature of the study design is the focus on clinically relevant outcomes and clinical variables so that results can be immediately translated into clinical practice. This goal is realized in Aim 1 in which we will deliver the best performing clinical prediction model that relies only on clinically available data and lab tests to predict a clinical outcome used in pulmonary clinics to define sarcoidosis disease progression. This outcome is a clinically meaningful decline in lung function. In Aim 2, we will measure the added value of incorporating novel blood-based interferon related markers into the clinical prediction models. The goal of this Aim is to identify which novel markers should be developed and moved into the clinical arena for use in sarcoidosis prognostication. Finally, in Aim 3 we will apply these models to an important clinical management problem in sarcoidosis which is identifying the optimal monitoring frequency for a given patient. Addressing this last question is the first step towards being able to better anticipate disease progression before extensive organ damage occurs. The team of sarcoidosis investigators are highly qualified to execute this study because they have a track record of performing sarcoidosis clinical research, have ongoing collaborations and have participated in prior studies that involve biospecimen collection from patients including NIH-sponsored consortium studies. To execute this study, the investigators will contribute longitudinal biospecimens and clinical data from 357 patients with sarcoidosis that have been enrolled in longitudinal cohorts at centers across the US. Two hundred additional patients will be enrolled and followed for up to 39 months leading to a total sample size of 557, of which a majority will be African American. Our team also includes a uniquely qualified biostatistician, Dr. Charles McCulloch, who has pioneered aspects of the longitudinal modeling approach we will be using. Therefore, the proposed Aims have a high likelihood of success for tackling this long-overdue clinical problem.