Identifying Risk Factors for PTSD by Pooled Analysis of Current Prospective Studi

描述（由申请人提供）：创伤后应激障碍（PTSD）是一种常见的严重损害性障碍，发生在暴露于创伤性事件（TEs）之后。症状通常在TE暴露后不久开始，并随着时间的推移发展为慢性或恢复。创伤后应激障碍是最容易预防的精神障碍之一，因为许多暴露于TEs的人在第一反应环境中得到临床关注。对照临床试验表明，早期预防干预可显著降低PTS风险。然而，这些干预措施有不小的成本，由于只有少数人会发展为创伤后应激障碍，因此不可能向所有接触过创伤后应激障碍的人提供这些干预措施。对于许多自然康复的幸存者来说，它们也是不必要的。考虑到样本之间、样本内（例如，男性和女性幸存者之间）以及与TE的不同滞后时间，需要制定风险预测规则，以确定哪些暴露者具有PTSD的高风险。许多研究收集了纵向数据，通过评估创伤后应激障碍的潜在预测因素，从第一反应医疗机构开始，随着时间的推移，并使用基线数据预测随后的创伤后应激障碍，来解决这个问题。然而，这些研究的结果通常被认为是群体平均可能性的变化，而不是以一种实际、有用和预测个体风险的方式综合出来的。因此，我们创建了一个由最重要的此类研究的主要研究人员组成的联盟，将他们的个人和项目水平的数据结合起来，进行汇总的二次分析，以综合有关创伤后应激障碍预测因素的信息。我们的具体目标是：(1)：从16个最重要的纵向研究中构建一个统一的个人水平数据集，这些研究是关于从第一反应医疗机构开始的创伤后应激障碍受害者的PTSD预测因素。这些研究共评估了6390名受访者，其中14%患有急性创伤后应激障碍；(2)：估计约92%的合并样本（n = 5,917）在基线后使用CAPS评估1至3次的PTSD症状轨迹的潜在生长混合模型（LGMM），然后评估模型结果对轨迹和PTSD症状测量的样本间差异的敏感性；(3)：评估基线预测因子与PTSD结局（总样本中的急性PTSD、急性病例中的PTSD持续性、LGMM PTSD类别隶属度和症状轨迹）之间关联的程度和交叉研究一致性；(4)：利用目标3的结果为未来在第一反应环境中评估的创伤后应激障碍风险因素提出建议，并使用软件促进系统数据收集并为临床决策提供信息。我们寻求支持来构建这个统一的数据集，执行和报告分析结果，并开发一种可用于第一反应设置的风险预测工具。

DESCRIPTION (provided by applicant): Posttraumatic stress disorder (PTSD) is a commonly occurring and seriously impairing disorder that occurs after exposure to traumatic events (TEs). Symptoms typically begin shortly after TE exposure and evolve with time to either chronicity or recovery. PTSD is one of the most preventable mental disorders, as many people exposed to TEs come to clinical attention in first response settings. Controlled clinical trials show that PTS risk can be significantly reduced by early preventive interventions. However, these interventions have nontrivial costs, making it infeasible to offer them to all persons exposed to TEs given that only a small minority goes on to develop PTSD. They are also unnecessary for many survivors who recovery spontaneously. To be cost-effective, risk prediction rules are needed to identify which exposed persons are at high risk of PTSD taking into consideration that predictors may vary between samples, within samples (e.g., between male and female survivors) and at different time lags from the TE. A number of research studies have collected longitudinal data addressing this issue by assessing potential predictors of PTSD among TE victims starting in first response healthcare settings, following participants over time, and using baseline data to predict subsequent PTSD. However, these studies' results have often been presented as changes in groups' average likelihood and were not synthesized in a way that would be practical, useful and predictive of individual risk. Therefore, we created a consortium of the principal investigators of the most important such studies to combine their individual- and item-level data towards carrying out a pooled secondary analysis to synthesize information about the predictors of PTSD. Our Specific Aims are: (1): To construct a consolidated dataset of individual-level data from 16 of the most important longitudinal studies of predictors of PTSD among TE victims starting in first response healthcare settings. These studies assessed a total of 6,390 respondents, 14% of whom have developed acute PTSD; (2): To estimate a latent growth mixture model (LGMM) of PTSD symptom trajectories in the roughly 92% of the consolidated sample (n = 5,917) assessed between one and three times after baseline with the CAPS and then to evaluate the sensitivity of model results to between-sample differences in trajectories and PTSD symptom measures; (3): To estimate the magnitude and cross-study consistency of associations between baseline predictors and PTSD outcomes (acute PTSD in the total sample; PTSD persistence among acute cases; LGMM PTSD class membership and symptom trajectories); (4): To use the results in Aim 3 to develop recommendations for the PTSD risk factors to be assessed in the future in first response settings along with software to facilitate systematic data collection and inform clinical decision making. We seek support to construct this consolidated dataset, to carry out and report the results of analyses, and to develop a risk prediction tool that can be used in first response settings.