Abstract
Serum brain-enriched biomarkers are increasingly employed in the clinical evaluation of traumatic brain injury (TBI) to assist with triage, neuroimaging decisions, and prognostication. However, the potential of temporal biomarker trajectories to inform disease monitoring and long-term outcomes remains underexplored. We aim to identify distinct biomarker trajectory (TRAJ) profiles in traumatic brain injury patients and to examine their associations with long-term clinical outcomes. The study included 373, CT-positive Intensive Care Unit (ICU) traumatic brain injury patients (256 with initial Glasgow Coma Scale 3–12) from the Collaborative European Neurotrauma Effectiveness Research in TBI (CENTER-TBI) core study who had at least two serum samples collected between days 1 and 5 post-injury. Six biomarkers -glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, neurofilament light chain, Tau, S100B, and neuron-specific enolase- were analyzed. Optimal cluster solutions were determined using a composite validation index derived from seven internal clustering metrics. Distinct high and low trajectory classes emerged for all biomarkers; each comprising at least 40% of the cohort for five of the biomarkers. Cross-biomarker concordance analysis identified composite high (n = 104) and low (n = 110) TRAJ profiles. Key metrics for evaluating patient outcomes include Glasgow Outcome Scale Extended (GOSE), mortality, and Quality of Life after Brain Injury Overall Scale (QoLIBRI-OS) at 3, 6, and 12 months as well as a prognostic incremental value analysis using a conventional prediction model: International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT). High TRAJ membership is strongly associated with poor functional recovery (GOSE 1–4 at 3–12 months; odds ratio (OR) 8.79 [95% confidence interval (CI): 4.56-16.97]—12.29 [95%CI: 6.19–24.40], P < 0.001) and increased 180-day mortality (OR (14.84 [95%CI: 5.56–39.64], P < 0.001). Conversely, low TRAJ membership predicted favorable recovery (GOSE 6–8 at 3–12 months; OR 7.42 [95%CI: 3.10–17.76]—10.83 [95%CI: 3.65–32.14], P < 0.001) and better quality of life (QoLIBRI-OS ≥52; OR 4.98 [95%CI: 1.92–12.89], P < 0.01). Compared to single day-1 biomarker measurements, trajectory-based profiles yielded larger effect sizes and provided incremental prognostic value when added to the IMPACT prediction model (ΔR² 9–17%, P < 0.05). Overall, repeated biomarker measurements across the acute phase yield superior prognostic accuracy relative to single timepoint assessments. These findings underscore the importance of integrating longitudinal biomarker monitoring into ICU-based traumatic brain injury care and suggest that temporal trajectory profiling may improve prognostic modelling and facilitate more precise patient stratification for both clinical management and interventional studies.
Recommended Citation
T. S. Do and C. Carnes and Z. Yang and F. Kobeissy and H. Yadikar and G. R. Olbricht and O. Tenovuo and J. P. Posti and E. W. Steyerberg and L. Wilson and N. Von Steinbüchel and E. Czeiter and A. Buki and D. K. Menon, "Serum Biomarker Trajectory Clusters Predict Functional Outcome and Quality of Life for Traumatic Brain Injury," Brain Communications, vol. 8, no. 2, article no. fcag055, Oxford University Press, Jan 2026.
The definitive version is available at https://doi.org/10.1093/braincomms/fcag055
Department(s)
Mathematics and Statistics
Publication Status
Open Access
Keywords and Phrases
blood-based biomarkers; ensemble cluster validation model; machine learning; traumatic brain injury prognosis
International Standard Serial Number (ISSN)
2632-1297
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2026 Oxford University Press, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Jan 2026
