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

Author:

Bantis Leonidas E1,Young Kate J1,Tsimikas John V2,Mosier Brian R1,Gajewski Byron1ORCID,Yeatts Sharon3,Martin Renee L3,Barsan William4,Silbergleit Robert4,Rockswold Gaylan5,Korley Frederick K4

Affiliation:

1. Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA

2. Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, School of Sciences, Samos, Greece

3. Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA

4. Department of Emergency Medicine University, Michigan Medical School, University of Michigan, Ann Arbor, MI, USA

5. Department of Neurosurgery, University of Minnesota, Hennepin County Medical Center, Minneapolis, MN, USA

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.

Funder

Children’s Mercy Hospital, Kansas City

NIH

Masonic Cancer Alliance

Center for Scientific Review

U.S. Department of Defense

The Honorable Tina Brozman Foundation

Ovarian Cancer Research Alliance

Publisher

SAGE Publications

Subject

General Earth and Planetary Sciences

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