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Biomarkers for Traumatic Brain Injury: Data Standards and Statistical Considerations
Journal of Neurotrauma ( IF 4.2 ) Pub Date : 2021-08-23 , DOI: 10.1089/neu.2019.6762
J Russell Huie 1 , Stefania Mondello 2 , Christopher J Lindsell 3 , Luca Antiga 4 , Esther L Yuh 1 , Elisa R Zanier 5 , Serge Masson 5 , Bedda L Rosario 6 , Adam R Ferguson 1, 7 ,
Affiliation  

Recent biomarker innovations hold potential for transforming diagnosis, prognostic modeling, and precision therapeutic targeting of traumatic brain injury (TBI). However, many biomarkers, including brain imaging, genomics, and proteomics, involve vast quantities of high-throughput and high-content data. Management, curation, analysis, and evidence synthesis of these data are not trivial tasks. In this review, we discuss data management concepts and statistical and data sharing strategies when dealing with biomarker data in the context of TBI research. We propose that application of biomarkers involves three distinct steps—discovery, evaluation, and evidence synthesis. First, complex/big data has to be reduced to useful data elements at the stage of biomarker discovery. Second, inferential statistical approaches must be applied to these biomarker data elements for assessment of biomarker clinical utility and validity. Last, synthesis of relevant research is required to support practice guidelines and enable health decisions informed by the highest quality, up-to-date evidence available. We focus our discussion around recent experiences from the International Traumatic Brain Injury Research (InTBIR) initiative, with a specific focus on four major clinical projects (Transforming Research and Clinical Knowledge in TBI, Collaborative European NeuroTrauma Effectiveness Research in TBI, Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe, and Approaches and Decisions in Acute Pediatric TBI Trial), which are currently enrolling subjects in North America and Europe. We discuss common data elements, data collection efforts, data-sharing opportunities, and challenges, as well as examine the statistical techniques required to realize successful adoption and use of biomarkers in the clinic as a foundation for precision medicine in TBI.

中文翻译:

创伤性脑损伤的生物标志物:数据标准和统计考虑因素

最近的生物标志物创新具有改变创伤性脑损伤 (TBI) 的诊断、预后模型和精确治疗靶向的潜力。然而,许多生物标志物,包括脑成像、基因组学和蛋白质组学,涉及大量高通量和高内容的数据。这些数据的管理、整理、分析和证据合成并不是微不足道的任务。在这篇综述中,我们讨论了在 TBI 研究背景下处理生物标志物数据时的数据管理概念以及统计和数据共享策略。我们建议生物标志物的应用涉及三个不同的步骤——发现、评估和证据合成。首先,在生物标志物发现阶段,必须将复杂/大数据简化为有用的数据元素。其次,必须将推论统计方法应用于这些生物标志物数据元素,以评估生物标志物的临床实用性和有效性。最后,需要综合相关研究来支持实践指南,并根据现有的最高质量、最新证据做出健康决策。我们的讨论重点是国际创伤性脑损伤研究 (InTBIR) 倡议的最新经验,特别关注四个主要临床项目(TBI 的研究和临床知识转变、TBI 欧洲神经创伤有效性合作研究、急性创伤性脑损伤合作研究)欧洲重症监护医学中的脑损伤,以及急性儿科 TBI 试验的方法和决定),目前正在北美和欧洲招募受试者。我们讨论常见的数据元素、数据收集工作、数据共享机会和挑战,并研究在临床中成功采用和使用生物标志物所需的统计技术,作为 TBI 精准医疗的基础。
更新日期:2021-09-20
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