Statistical assessment of the prognostic and the predictive value of biomarkers-A biomarker assessment framework with applications to traumatic brain injury biomarker studies.

Leonidas E Bantis, Kate J Young, John V Tsimikas, Brian R Mosier, Byron Gajewski, Sharon Yeatts, Renee L Martin, William Barsan, Robert Silbergleit, Gaylan Rockswold, Frederick K Korley
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引用次数: 1

Abstract

Studies that investigate the performance of prognostic and predictive biomarkers are commonplace in medicine. Evaluating the performance of biomarkers is challenging in traumatic brain injury (TBI) and other conditions when both the time factor (i.e. time from injury to biomarker measurement) and different levels or doses of treatments are in play. Such factors need to be accounted for when assessing the biomarker's performance in relation to a clinical outcome. The Hyperbaric Oxygen in Brain Injury Treatment (HOBIT) trial, a phase II randomized control clinical trial seeks to determine the dose of hyperbaric oxygen therapy (HBOT) for treating severe TBI that has the highest likelihood of demonstrating efficacy in a phase III trial. Hyperbaric Oxygen in Brain Injury Treatment will study up to 200 participants with severe TBI. This paper discusses the statistical approaches to assess the prognostic and predictive performance of the biomarkers studied in this trial, where prognosis refers to the association between a biomarker and the clinical outcome while the predictiveness refers to the ability of the biomarker to identify patient subgroups that benefit from therapy. Analyses based on initial biomarker levels accounting for different levels of HBOT and other baseline clinical characteristics, and analyses of longitudinal changes in biomarker levels are discussed from a statistical point of view. Methods for combining biomarkers that are of complementary nature are also considered and the relevant algorithms are illustrated in detail along with an extensive simulation study that assesses the performance of the statistical methods. Even though the discussed approaches are motivated by the HOBIT trial, their applications are broader. They can be applied in studies assessing the predictiveness and prognostic ability of biomarkers in relation to a well-defined therapeutic intervention and clinical outcome.

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生物标志物预后和预测价值的统计评估--应用于脑外伤生物标志物研究的生物标志物评估框架。
调查预后和预测性生物标志物性能的研究在医学界屡见不鲜。在创伤性脑损伤(TBI)和其他情况下,由于时间因素(即从受伤到生物标志物测量的时间)和不同的治疗水平或剂量,评估生物标志物的性能具有挑战性。在评估生物标志物与临床结果的关系时,需要考虑这些因素。高压氧治疗脑损伤(HOBIT)试验是一项二期随机对照临床试验,旨在确定治疗严重创伤性脑损伤的高压氧疗法(HBOT)的剂量,该剂量在三期试验中显示疗效的可能性最大。高压氧治疗脑损伤将对最多 200 名严重创伤性脑损伤患者进行研究。本文讨论了评估该试验所研究的生物标志物的预后和预测性能的统计方法,其中预后指的是生物标志物与临床结果之间的关联,而预测性指的是生物标志物识别从治疗中获益的患者亚组的能力。本文从统计学的角度讨论了根据不同的 HBOT 水平和其他基线临床特征对初始生物标志物水平进行的分析,以及对生物标志物水平的纵向变化进行的分析。此外,还考虑了将具有互补性的生物标志物结合起来的方法,并详细说明了相关算法以及评估统计方法性能的大量模拟研究。尽管所讨论的方法是由 HOBIT 试验激发的,但它们的应用范围更广。它们可用于评估生物标志物与明确定义的治疗干预和临床结果相关的预测性和预后能力的研究。
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