Predictive Biomarkers & Models Assessing Systemic Response to Injury after Moderate-to-Severe TBI

摘要 尽管创伤性脑损伤(TBI)患者的护理有所改善，但临床医生没有 脑外伤的神经保护治疗选择。此外，调查人员的先验预测能力有限。 颅脑损伤后死亡率。众所周知，雌二醇(E_2)和孕酮(PRO)具有神经保护作用 在临床前脑损伤模型中进行研究时。然而，我们的独立临床数据表明， 创伤性脑损伤后会产生内源性性激素，这种激素来源于性腺外来源，是 放大的芳构化途径。这些途径使用肿瘤坏死因子α产生E2，并与死亡率和 糟糕的结果。文献表明，雌二醇的积累可能反映了对损伤的复杂的全身反应。 这是由交感神经系统(SNS)启动并由SNS诱导的炎症持续的， 导致与全身损害、非神经器官相关的放大的E2产生 功能障碍(NNOD)、死亡率增加和不良结局风险。我们的作品显示了E2和它的额外- 性腺基因组转录因子肿瘤坏死因子α是脑外伤后重要的死亡率预测因子，并与 导致不良结局的系统性并发症。动物研究和第三阶段之间的二分法 PRO的随机临床试验(RCT)特别说明了需要进一步研究的重要问题 协调PRO是否/如何可能是患有脑外伤的亚群的可行神经保护治疗选择 了解雌二醇和肿瘤坏死因子α水平是否/如何可以预测PRO治疗的治疗效果的异质性。 我们的中心假设是血清E_2和肿瘤坏死因子-α是反映全身对脑外伤反应的新指标 死亡/不良结局的基线风险，是可变PRO效应的敏感指标。E_2和肿瘤坏死因子α 可以有效地描述那些风险很高/很低的人(无论接受什么治疗)以及那些 可能会受益，也可能会受到专业人士的伤害。使用保护III研究和生物保护的数据和样本 试验中，我们有一个独特的机会来描绘生物异质性和其他导致无效的因素 结果：治疗结果。这些队列提供了一个严格开发的临床研究平台，从中可以 检验以下假设，即系统性E2和肿瘤坏死因子-α反映了全身对脑外伤的反应，并可以作为 HTE到支持治疗的指标。在学习结束时，我们将了解如何1)有效地计算 中/重型颅脑损伤后基线死亡率和不良结局风险的异质性，2)如何表征 PRO治疗的异质性降低了基线风险，并有助于产生不同但可变的PRO反应 分组，3)确定PRO在治疗反应中是否/如何影响随机化后生物标记物 组4)生成简约的基线风险计算器，以便在其他TBI人群中进行测试，以支持 未来随机对照试验中有效的预随机化患者选择。这项工作结合了基线风险 异质性和肝动脉栓塞术是精确医学方法告知优先治疗反应的关键特征 颅脑损伤后和急性RCT脑损伤患者的选择更一般。

ABSTRACT Despite improvements in care for individuals with traumatic brain injury (TBI), clinicians have no neuroprotective treatment options for TBI. Moreover, investigators have limited ability a priori to predict mortality after TBI. Estradiol (E2) and progesterone (PRO) are well known for their neuroprotective qualities when studied in pre-clinical TBI models. However, our independent clinical data suggest relative increases in endogenous sex hormones occur after TBI that are derived from extra-gonadal sources and are the result of amplified aromatization pathways. These pathways use TNFα to produce E2 and are linked with mortality and poor outcome. The literature indicates that E2 accumulation may reflect a complex systemic response to injury that is initiated by the sympathetic nervous system (SNS) and perpetuated by SNS-induced inflammation, leading to amplified E2 production that is associated with systemic compromise, non-neurological organ dysfunction (NNOD) and increased mortality and poor outcome risk. Our body of work shows E2 and its extra- gonadal genomic transcription factor TNFα are important mortality predictors post-TBI and are associated with systemic complications that contribute to poor outcome. The dichotomy between animal studies and phase III randomized clinical trials (RCTs) for PRO specifically illustrate important questions requiring further study to reconcile if/how PRO might be a viable neuroprotective treatment option for subpopulations with TBI and to understand if/how E2 & TNFα levels can predict heterogeneity of treatment effects (HTE) with PRO therapy. Our central hypothesis is that serum E2 & TNF-α, reflect the systemic response to TBI, are novel indicators of baseline risk for mortality/poor outcome, and are sensitive indicators of variable PRO effects. E2 & TNFα may be effective in characterizing those with very high/low risk (regardless of treatment) as well as those who might benefit or be harmed by PRO. Using data and samples from the ProTECT III study and the BioProTECT trial, we have a unique opportunity to delineate biological heterogeneity and other contributors to the null findings treatment result. These cohorts provide a rigorously developed clinical research platform from which to test the hypothesis that systemic E2, & TNF-α, reflect the systemic response to TBI and can serve as an indicator of HTE to PRO therapy. At study conclusion, we will understand how to 1) effectively calculate heterogeneity in baseline mortality and poor outcome risk after moderate/severe TBI, 2) characterize how heterogeneity in PRO treatment moderates baseline risk and contributes to distinct, yet variable PRO response groups, 3) identify if/how post-randomization biomarkers are affected by PRO among treatment response groups 4) generate a parsimonious baseline risk calculator to test in other TBI populations in support of effective pre-randomization patient selection in future RCTs. Together this work incorporates baseline risk heterogeneity and HTE as key features in a precision medicine approach to informing PRO treatment response after TBI and for acute RCT TBI patient selection more generally.