Abstract
Early treatment of moderate/severe traumatic brain injury (TBI) with progesterone does not improve clinical outcomes. This is in contrast with findings from pre-clinical studies of progesterone in TBI. To understand the reasons for the negative clinical trial, we investigated whether progesterone treatment has the desired biological effect of decreasing brain cell death. We quantified brain cell death using serum levels of biomarkers of glial and neuronal cell death (glial fibrillary acidic protein [GFAP], ubiquitin carboxy-terminal hydrolase-L1 [UCH-L1], S100 calcium-binding protein B [S100B], and Alpha II Spectrin Breakdown Product 150 [SBDP]) in the Biomarkers of Injury and Outcome–Progesterone for Traumatic Brain Injury, Experimental Clinical Treatment (BIO-ProTECT) study. Serum levels of GFAP, UCHL1, S100B, and SBDP were measured at baseline (≤4 h post-injury and before administration of study drug) and at 24 and 48 h post-injury. Serum progesterone levels were measured at 24 and 48 h post-injury. The primary outcome of ProTECT was based on the Glasgow Outcome Scale-Extended assessed at 6 months post-randomization. We found that at baseline, there were no differences in biomarker levels between subjects randomized to progesterone treatment and those randomized to placebo (p > 0.10). Similarly, at 24 and 48 h post-injury, there were no differences in biomarker levels in the progesterone versus placebo groups (p > 0.15). There was no statistically significant correlation between serum progesterone concentrations and biomarker values obtained at 24 and 48 h. When examined as a continuous variable, baseline biomarker levels did not modify the association between progesterone treatment and neurological outcome (p of interaction term >0.39 for all biomarkers). We conclude that progesterone treatment does not decrease levels of biomarkers of glial and neuronal cell death during the first 48 h post-injury.
Keywords: adult brain injury, biomarkers, head trauma, traumatic brain injury
Introduction
The Progesterone for Traumatic Brain Injury, Experimental Clinical Treatment (ProTECT) III trial, a phase III, randomized, multi-center trial, demonstrated that early treatment of moderate/severe traumatic brain injury (TBI) with intravenous (i.v.) progesterone does not result in improved neurological outcome, compared to treatment with placebo.1 This finding is discordant with findings from phase II clinical trials and pre-clinical studies that provided preliminary evidence to support this trial.2 One of the proposed explanations for progesterone's failure to demonstrate improvement in neurological outcome is that the dose of progesterone was suboptimal and therefore inadequate to produce the desired biological effect of neuroprotection.3 However, this proposed explanation has not been formally investigated.
The neuroprotective effect of a promising neuroprotective agent may be quantified by serial measurements of blood levels of proteins that are released into the circulation after glial and neuronal cell death. Glial fibrillary acidic protein (GFAP) and S100 calcium-binding protein B (S100B), both structural proteins found in astrocytes, and ubiquitin carboxyl-terminal hydrolase 1 (UCH-L1) and αII-Spectrin Breakdown Product of molecular weight 150 (SBDP150), both found in neurons, are released into the circulation after TBI, in amounts that are proportional to the injury severity.4–7 Blood levels of these biomarkers are predictive of neurologic outcome at 6-months post-injury.8,9 These biomarkers also exhibit different temporal profiles post-release. UCH-L1 and S100B both peak at ∼6–8 h post-injury,10,11 whereas GFAP peaks at ∼24–48 h post-injury.11,12
After reaching peak levels, levels of these biomarkers decline to baseline in a predictable fashion. However, in the presence of ongoing secondary brain injury, levels may continue to increase or have a prolonged decline.11 Brain injury biomarker levels may be decreased by efficacious neuroprotective agents. A study of porcine closed cortical impact TBI models randomized animals to treatment with high-dose valproic acid (VPA) versus placebo. Although GFAP levels in both study groups were similar, swine treated with VPA had GFAP values at days 1 and 3 that were lower than those treated with placebo.13 Similar findings were reported in rodent TBI models.14
The primary aims of this study were to determine whether: 1) the dose of progesterone utilized in the ProTECT study produced the desired biological effect of neuroprotection as measured by blood-based biomarkers of glial and neuronal cell death; and 2) there is a dose-dependent association between progesterone concentration and brain injury biomarker level. We also examined whether baseline biomarker levels modify the association between progesterone treatment and clinical outcome.
Methods
Details of the ProTECT III and the ancillary biomarkers of injury and outcome in the ProTECT III (BIO-ProTECT) study have been previously published.15,16 In summary, ProTECT III studied blunt TBI subjects with a Glasgow Coma Scale (GCS) ranging from 4 to 12 (on a scale of 3–15) and who could receive study treatment within 4 h of injury. Patients with hypoxia (oxygen saturation <90%), hypotension (systolic blood pressure <90 mm Hg), spinal cord injury, status epilepticus, bilaterally unreactive pupils, or a GCS of 3 were deemed ineligible. Subjects were randomized in a 1:1 ratio to receive either i.v. progesterone dissolved in Intralipid or placebo (Intralipid alone) for a total of 96 h. ProTECT III was stopped early for futility in November 2013, after 882 subjects had been randomized.
BIO-ProTECT procedures were included in version 7 of the ProTECT III protocol. Although the ProTECT III trial began subject enrollment in April 2010, the first Bio-ProTECT sample was not collected until August 2011. Serum samples were collected at baseline (within 4 h of injury) and at 24 and 48 h post-injury. They were processed and stored in −80°C freezer within 60 min of phlebotomy and shipped on dry ice to Banyan Biomarkers Inc. (San Diego, CA) for long-term storage and analysis.
Serum samples were analyzed by Banyan Biomarkers' laboratory technicians who were blinded to subjects' clinical and study data. Analysis occurred in batches and in technical duplicates. GFAP, UCHL1, and SBDP150 were measured using Banyan Biomarkers' proprietary assays and according to previously published methods.15–19 S100B was measured using the Roche Cobas 6000 assay (Roche Diagnostics, Rotkreuz, Switzerland). The lower limit of quantification (LLOQ) and the upper limit of quantification (ULOQ) for GFAP, UCH-L1, S100B and SBDP150 were 0.03 and 50, 0.1 and 9.0, 0.015 and 2.0, and 0.02 and 6.4 ng/mL, respectively. Serum progesterone levels were measured in samples obtained at 24 and 48 h. A total of 7.5% of samples were below the LLOQ, and a total of 3.8% of samples were above the ULOQ. The lower limit and the upper limit of testable values were 0.1 and 2000 ng/mL, respectively.
The primary outcome for the ProTECT III study was functional outcome measured using the Glasgow Outcome Scale-Extended (GOS-E) at 6 months (±30 days) post-randomization. The GOS-E ranks functional outcome on a scale of 1–8, with 1 indicating death and 8 indicating upper good recovery. A favorable outcome was defined using a stratified dichotomy of the GOS-E scores, such that subjects with a severe initial injury (an index GCS score of 4–5 or, if the patient was intubated, an index GCS motor score of 2–3) were considered to have a favorable outcome if the 6-month GOS-E score was 3 or higher. Patients with a moderate-to-severe initial injury (an index GCS score of 6–8 or, if the patient was intubated, an index GCS motor score of 4–5) were considered to have a favorable outcome if the 6-month GOS-E score was 5 or higher, and those with a moderate initial injury (an index GCS score of 9–12) were considered to have a favorable outcome if the 6-month GOS-E score was 7 or higher.
Statistical analysis
Continuous variables were summarized as means (± standard deviations) or medians (with the corresponding interquartile range [IQR]), depending on whether the corresponding distribution appeared normal. Categorical variables were summarized as numbers and percentages. Consistent with previous studies, biomarker values below the assay's LLOQ were all assigned a value half of the LLOQ, whereas biomarker values above the ULOQ were assigned a value 1.5 times the ULOQ.20 Progesterone values beyond the testable limits were excluded. Mixed-effects models were used in order to compare the biomarker profile according to randomized treatment assignment (progesterone vs. placebo). An unstructured covariance matrix was used to allow for the correlation between repeated observations within a given subject. Given that all biomarker values had right-skewed distributions, they were log-transformed before inclusion in the regression models. Models were adjusted for potential confounders: age, severity of injury on head computed tomography (CT) using the Rotterdam head CT score, and GCS. Given the small number of subjects in the Rotterdam head CT score categories 1 and 6, categories 1 and 2 were combined into a single category, as were categories 5 and 6.
We also evaluated the association between steady-state progesterone values and biomarker levels at 24 and 48 h in the progesterone arm using Spearman's rank-order correlation coefficient. Given that progesterone levels measured at 24 and 48 h were similar, we estimated steady-state progesterone level as the mean progesterone value of the two time points. Using a logistic regression model, we investigated whether baseline biomarker level (modeled as a continuous variable) modifies the association between progesterone and neurological outcome. Statistical analyses were performed using SAS (SAS Institute Inc., Cary, NC), Stata/MP (version 11.2; StataCorp LP, College Station, TX), and RStudio (version 1.1.463; R Foundation for Statistical Computing, Vienna, Austria). Two-tailed p values <0.05 were considered statistically significant.
Results
Among the 882 subjects enrolled in ProTECT III, 566, 537, and 512 subjects had at least one biomarker measurement at baseline, 24 and 48 h, respectively. Further, 497 and 429 subjects had progesterone levels and levels of all four biomarkers at 24 and 48 h, respectively. Subjects were predominantly male (75.3%) and white (75.1%), with a median age of 34 (IQR, 23–52) years. The majority of subjects (65.3%) had a GCS of 3–8, and 87.5% had traumatic intracranial abnormalities on head CT. At 6 months post-injury, 284 (50.2%) subjects had a favorable neurological outcome. A detailed description of the demographic and clinical characteristics of the study population can be found in Table 1.
Table 1.
Demographic and Clinical Characteristics of the Study Population
| Demographic/characteristic | N = 566 |
|---|---|
| Age, median, IQR | 34 (23–52) |
| Sex, men, N (%) | 426 (75.27) |
| Race | |
| • White | 425 (75.09%) |
| • Black/African American | 84 (14.84%) |
| • Others | 57 (10.07%) |
| GCS | |
| • Moderate (iGCSǂ 9–12) | 179 (31.63%) |
| • iGCS 6–8/iMOTOR 4–5) | 289 (51.06%) |
| • iGCS 4–5/iMOTOR 2–3) | 81 (14.31%) |
| • Missing | 17 (3.00%) |
| Rotterdam head CT classification | |
| • 1 and 2 | 203 (35.87%) |
| • 3 | 249 (43.99%) |
| • 4 | 54 (9.54%) |
| • 5 and 6 | 60 (10.60%) |
| Injury mechanism | |
| • Motor vehicle crash | 201 (35.51%) |
| • Pedestrian struck by moving vehicle | 69 (12.19%) |
| • Motorcycle/scooter/ATV crash | 113 (19.96) |
| • Other | 183 (32.33%) |
IQR, interquartile range; GCS, Glasgow Coma Scale; iGCS, initial GCS; CT, computed tomography; ATV, all-terrain vehicle.
Baseline biomarker values in subjects randomized to progesterone treatment compared to those randomized to placebo were similar.15 There was no significant effect of treatment (progesterone vs. placebo) for any of the biomarkers examined and at any of the time points examined; see Table 2 for detailed results and Figure 1 for a graphical representation of results. GFAP values at 24 h were slightly higher than at baseline (0–4 h after injury); however, 48-h values were lower than baseline and 24-h values. In contrast, UCH-L1, S100B, and SBDP values were highest at baseline and were progressively lower at 24 and 48 h (Fig. 2). Longitudinal, within-person analysis of biomarker levels during the first 48 h, adjusted for age, initial GCS, and injury severity based on head CT findings, did not reveal statistically significant differences between treatment arms in the biomarker profile (Table 3). The correlation between steady-state progesterone concentrations and biomarker values obtained at 24 and 48 h in the progesterone arm were not statistically significant (Fig. 3). Baseline biomarker level (modeled as a continuous variable) did not modify the association between progesterone treatment and neurologic outcome (p values for interaction term were 0.40 for S100B, 0.81 for GFAP, 0.75 for UCH-L1, and 0.46 for SBDP).
Table 2.
Unadjusted Biomarker Levels in Subjects Assigned to Progesterone vs. Placebo
| Biomarker | Placebo | Progesterone | p value |
|---|---|---|---|
| Baseline (in ng/mL) | |||
| GFAP | 2.575 (0.773–7.664) | 3.102 (1.052–9.861) | 0.10 |
| UCH-L1 | 3.471 (1.856–8.041) | 3.563 (1.904–8.180) | 0.75 |
| S100B | 0.272 (0.120–0.574) | 0.296 (0.131–0.545) | 0.50 |
| SBDP | 0.156 (0.078–0.281) | 0.156 (0.089–0.310) | 0.49 |
| 24 hours (in ng/mL) | |||
| GFAP | 3.985 (1.447–7.219) | 3.415 (1.710–7.134) | 0.96 |
| UCH-L1 | 0.404 (0.262–0.790) | 0.425 (0.232–0.753) | 0.86 |
| S100B | 0.054 (0.032–0.083) | 0.045 (0.031–0.086) | 0.30 |
| SBDP | 0.053 (0.036–0.081) | 0.055 (0.035–0.083) | 0.66 |
| 48 hours (in ng/mL) | |||
| GFAP | 1.697 (0.593–5.067) | 1.642 (0.673–4.372) | 0.81 |
| UCH-L1 | 0.193 (0.107–0.357) | 0.177 (0.050–0.338) | 0.39 |
| S100B | 0.031 (0.019–0.057) | 0.029 (0.018–0.044) | 0.15 |
| SBDP | 0.045 (0.031–0.070) | 0.048 (0.033–0.069) | 0.71 |
GFAP, glial fibrillary acidic protein; UCH-L1, ubiquitin carboxy-terminal hydrolase-L1; S100B, S100 calcium-binding protein B; SBDP150, Alpha II Spectrin Breakdown Product 150.
FIG. 1.
Temporal changes in biomarker levels in subjects randomized to progesterone treatment versus placebo. This is a graphical display of biomarker levels in the progesterone versus placebo arms during the first 48 hours post-injury. The gray line represents smoothed conditional means for each plot. GFAP, glial fibrillary acidic protein; S100B, S100 calcium-binding protein B; SBDP150, Alpha II Spectrin Breakdown Product 150; UCH-L1, ubiquitin carboxy-terminal hydrolase-L1.
FIG. 2.
Changes in biomarker levels during the first 48 h after injury. Twenty-four hour GFAP values were slightly higher than baseline (0-4 hours after injury) values, however 48 hour values were lower than baseline and 24 hour values. In contrast, UCH-L1, S100B, and SBDP values were highest at baseline and were progressively lower at 24 and 48 hours. GFAP, glial fibrillary acidic protein; S100B, S100 calcium-binding protein B; SBDP150, Alpha II Spectrin Breakdown Product 150; UCH-L1, ubiquitin carboxy-terminal hydrolase-L1.
Table 3.
Longitudinal Models of the Association between Biomarker Levels and Randomized Treatment Assignment
| Biomarker | Percent change in biomarker level | 95% | CI | p value |
|---|---|---|---|---|
| S100B | ||||
| Interaction between time and treatment | 0.3228 | |||
| 24 h vs. baseline | ||||
| Progesterone | –81.7 | –83.5 | –79.7 | <0.0001 |
| Placebo | –79.6 | –81.6 | –77.4 | <0.0001 |
| 48 h vs. baseline | ||||
| Progesterone | –89.8 | –91.1 | –88.3 | <0.0001 |
| Placebo | –88.4 | –89.9 | –86.7 | <0.0001 |
| GFAP | ||||
| Interaction between time and treatment | 0.1558 | |||
| 24 h vs. baseline | ||||
| Progesterone | 22.8 | 7.3 | 40.5 | 0.0029 |
| Placebo | 43.6 | 25.5 | 64.4 | <0.0001 |
| 48 h vs. baseline | ||||
| Progesterone | –40.5 | –48.5 | –31.4 | <0.0001 |
| Placebo | –27.5 | –37.2 | –16.3 | <0.0001 |
| UCH-L1 | ||||
| Interaction between time and treatment | 0.2125 | |||
| 24 h vs. baseline | ||||
| Progesterone | –88.9 | –89.9 | –87.8 | <0.0001 |
| Placebo | –88.4 | –89.4 | –87.3 | <0.0001 |
| 48 h vs. baseline | ||||
| Progesterone | –95.5 | –96.1 | –95.0 | <0.0001 |
| Placebo | –94.8 | –95.4 | –94.1 | <0.0001 |
| SBDP150 | ||||
| Interaction between time and treatment | 0.2903 | |||
| 24 h vs. baseline | ||||
| Progesterone | –65.6 | –68.6 | –62.4 | <0.0001 |
| Placebo | –65.9 | –68.8 | –62.7 | <0.0001 |
| 48 h vs. baseline | ||||
| Progesterone | –72.1 | –74.9 | –69.0 | <0.0001 |
| Placebo | –70.1 | –73.1 | –66.7 | <0.0001 |
The models adjusted for age, head CT results based on the Rotterdam Head CT classification, and injury severity based on GCS.
S100B, S100 calcium-binding protein B; GFAP, glial fibrillary acidic protein; UCH-L1, ubiquitin carboxy-terminal hydrolase-L1; SBDP150, Alpha II Spectrin Breakdown Product 150; CI, confidence interval; CT, computed tomography; GCS, Glasgow Coma Scale.
FIG. 3.
Correlation between steady-state progesterone and biomarker level. The correlation between steady state progesterone concentrations and biomarker values obtained at 24 and 48 hours in progesterone arm were not statistically significant. GFAP, glial fibrillary acidic protein; S100B, S100 calcium-binding protein B; SBDP150, Alpha II Spectrin Breakdown Product 150; UCH-L1, ubiquitin carboxy-terminal hydrolase.
Discussion
In this secondary analysis of the BIO-ProTECT study, we were unable to show that progesterone treatment decreases levels of TBI biomarkers of glial and neuronal cell death. In addition, there was not a significant association between steady-state progesterone and biomarker levels. These findings are consistent with findings from the primary ProTECT III trial, which did not show a benefit of progesterone over placebo in the improvement of functional outcomes in patients with moderate/severe TBI. It is worth noting, however, that at 24 h GFAP values were 22.8% higher than baseline in the progesterone group and 43.6% higher than baseline in the placebo group (i.e., less of an increase in the progesterone group). Similarly, at 48 h, GFAP values were 40.5% lower than baseline in the progesterone group and 27.5% lower than baseline in the placebo group (i.e., more of a decrease in the progesterone group). Although these differences may be scientifically relevant, the study was not powered to detect the interaction between treatment group allotment and time.
A few human clinical trials have examined the use of blood-based biomarkers for monitoring response to experimental treatment. In a randomized control trial of severe TBI subjects randomized to early resuscitation with hypertonic saline and dextran versus normal saline only, serum S100B and neuron-specific enolase were found to be significantly higher in the normal saline group (n = 64) during the first 12 h.21 However, in that study (unlike ours), baseline biomarker levels were higher in the normal saline group compared to the hypertonic saline group, suggesting an imbalance in injury severity among treatment groups at randomization. A randomized control trial of erythropoietin versus placebo in moderate-to-severe TBI (n = 44) reported no differences in serum UCH-L1 and phosphorylated neurofilament heavy-chain levels during the first 5 days among subjects treated with erythropoietin compared to placebo.22
These findings were also consistent with the findings of no improvement in neurological outcome with erythropoietin treatment. The concordance in association between progesterone treatment and 1) neurological outcome and 2) biomarker levels suggests that there is a low probability that a future trial of the same dose of progesterone in moderate/severe TBI will yield different results. In addition, it suggests that these biomarkers may be useful adjuncts in early-phase TBI clinical trials for determining whether a promising neuroprotective agent ought to proceed to a phase III clinical trial.
We also found that when modeled as continuous variables, baseline biomarker levels did not modify the association between progesterone treatment and outcome. In other words, baseline biomarker values did not indicate a differential effect of treatment according to baseline biomarker level. Given that baseline biomarker levels are associated with TBI severity, we conclude that, regardless of the initial severity of TBI, progesterone does not improve clinical outcomes in moderate/severe TBI.
Our study has a number of limitations. These include the: 1) lack of biomarker measurements beyond the first 48 h of injury; 2) focus on biomarkers of glial and neuronal cell death and not on other biomarkers that may be more reflective of “target engagement”; and 3) our study may not have been adequately powered to test for significant interactions between biomarker values versus time and study group allotment.
Conclusions
Progesterone treatment does not result in a decrease in blood levels of selected biomarkers of glial and neuronal cell death.
Supplementary Material
Acknowledgments
We thank the staff of the Emory University Investigational Drug Service for drug compounding and preparation of the drug kits; the members of the data and safety monitoring board (T. Bleck [chair], G. Anderson, J. Collins, J. Chamberlain, J. Saver, and L. Gutmann); the independent data safety monitors (C. Robertson and D. Gress); the study coordinators, research assistants, and local site staff; R. Conwit and P. Gilbert (National Institutes of Health); and the patients who participated in this study and the family members who entrusted us with their care.
The views expressed in this article are those of the authors and do not necessarily represent the official views of the National Institutes of Health or other supporting entities.
Contributor Information
Collaborators: for the NETT Investigators
Funding Information
Supported by grants from the National Institute of Neurological Disorders and Stroke of the National Institutes of Health (NS062778, 5U10NS059032, and U01NS056975) and the National Center for Advancing Translational Sciences of the National Institutes of Health (UL1TR000454) and by the Emory Emergency Neurosciences Laboratory in the Department of Emergency Medicine, Emory School of Medicine, and Grady Memorial Hospital.
Author Disclosure Statement
Dr. Wright reports receiving royalties from a patent related to progesterone for the treatment of traumatic brain injury (U.S. patents 7,473,687, 7,915,244, and 8,455,468), which was licensed to BHR Pharma.
Supplementary Material
Supplementary Appendix: Neurological Emergencies Treatment Trials (NETT) Investigators
References
- 1. Wright, D.W., Yeatts, S.D., Silbergleit, R., Palesch, Y.Y., Hertzberg, V.S., Frankel, M., Goldstein, F.C., Caveney, A.F., Howlett-Smith, H., Bengelink, E.M., Manley, G.T., Merck, L.H., Janis, L.S., and Barsan, W.G. (2014). Very early administration of progesterone for acute traumatic brain injury. N. Engl. J. Med. 371, 2457–2466 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Schumacher, M., Denier, C., Oudinet, J. P., Adams, D., and Guennoun, R. (2016). Progesterone neuroprotection: the background of clinical trial failure. J. Steroid Biochem. Mol. Biol. 160, 53–66 [DOI] [PubMed] [Google Scholar]
- 3. Stein, D.G. (2015). Embracing failure: What the Phase III progesterone studies can teach about TBI clinical trials. Brain Inj. 29, 1259–1272 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Korley, F.K., Yue, J.K., Wilson, D.H., Hrusovsky, K., Diaz-Arrastia, R., Ferguson, A.R., Yuh, E.L., Mukherjee, P., Wang, K.K.W., Valadka, A.B., Puccio, A.M., Okonkwo, D.O., and Manley, G.T. (2018). Performance evaluation of a multiplex assay for simultaneous detection of four clinically relevant traumatic brain injury biomarkers. J. Neurotrauma 36, 182–187 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Diaz-Arrastia, R., Wang, K.K., Papa, L., Sorani, M.D., Yue, J.K., Puccio, A.M., McMahon, P.J., Inoue, T., Yuh, E.L., Lingsma, H.F., Maas, A.I., Valadka, A.B., Okonkwo, D.O., and Manley, G.T. (2014). Acute biomarkers of traumatic brain injury: relationship between plasma levels of ubiquitin C-terminal hydrolase-L1 and glial fibrillary acidic protein. J. Neurotrauma 31, 19–25 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Papa, L., Silvestri, S., Brophy, G.M., Giordano, P., Falk, J.L., Braga, C.F., Tan, C.N., Ameli, N.J., Demery, J.A., Dixit, N.K., Mendes, M.E., Hayes, R.L., Wang, K.K., and Robertson, C.S. (2014). GFAP out-performs S100β in detecting traumatic intracranial lesions on computed tomography in trauma patients with mild traumatic brain injury and those with extracranial lesions. J. Neurotrauma 31, 1815–1822 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Chen, S., Shi, Q., Zheng, S., Luo, L., Yuan, S., Wang, X., Cheng, Z., and Zhang, W. (2016). Role of alpha-II-spectrin breakdown products in the prediction of the severity and clinical outcome of acute traumatic brain injury. Exp. Ther. Med. 11, 2049–2053 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Korfias, S., Stranjalis, G., Boviatsis, E., Psachoulia, C., Jullien, G., Gregson, B., Mendelow, A.D., and Sakas, D.E. (2007). Serum S-100B protein monitoring in patients with severe traumatic brain injury. Intensive Care Med. 33, 255–260 [DOI] [PubMed] [Google Scholar]
- 9. Lei, J., Gao, G., Feng, J., Jin, Y., Wang, C., Mao, Q., and Jiang, J. (2015). Glial fibrillary acidic protein as a biomarker in severe traumatic brain injury patients: a prospective cohort study. Crit. Care 19, 362–368 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Ercole, A., Thelin, E.P., Holst, A., Bellander, B.M., and Nelson, D.W. (2016). Kinetic modelling of serum S100b after traumatic brain injury. BMC Neurol. 16, 93–93 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Thelin, E.P., Zeiler, F.A., Ercole, A., Mondello, S., Buki, A., Bellander, B.M., Helmy, A., Menon, D.K., and Nelson, D.W. (2017). Serial sampling of serum protein biomarkers for monitoring human traumatic brain injury dynamics: a systematic review. Front. Neurol. 8, 300. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Papa, L., Brophy, G.M., Welch, R.D., Lewis, L.M., Braga, C.F., Tan, C.N., Ameli, N.J., Lopez, M.A., Haeussler, C A., Mendez Giordano, D.I., Silvestri, S., Giordano, P., Weber, K.D., Hill-Pryor, C., and Hack, D.C. (2016). Time course and diagnostic accuracy of glial and neuronal blood biomarkers GFAP and UCH-L1 in a large cohort of trauma patients with and without mild traumatic brain injury. JAMA Neurol. 73, 551–560 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Korley, F.K., Nikolian, V.C., Williams, A.M., Dennahy, I.S., Weykamp, M., and Alam, H.B. (2018). Valproic acid treatment decreases serum glial fibrillary acidic protein and neurofilament light chain levels in swine subjected to traumatic brain injury. J. Neurotrauma 35, 1185–1191 [DOI] [PubMed] [Google Scholar]
- 14. Browning, M., Shear, D.A., Bramlett, H.M., Dixon, C.E., Mondello, S., Schmid, K.E., Poloyac, S.M., Dietrich, W.D., Hayes, R.L., Wang, K.K., Povlishock, J.T., Tortella, F.C., and Kochanek, P.M. (2016). Levetiracetam treatment in traumatic brain injury: Operation Brain Trauma Therapy. J. Neurotrauma 33, 581–594 [DOI] [PubMed] [Google Scholar]
- 15. Frankel, M., Fan, L., Yeatts, S.D., Jeromin, A., Vos, P.E., Wagner, A.K., Wolf, B.J., Pauls, Q., Lunney, M., Merck, L.H., Hall, C.L., Palesch, Y., Silbergleit, R., and Wright, D.W. (2019). The association of very early serum levels of S100B, GFAP, UCH-L1, and SBDP with outcome in ProTECT III. J. Neurotrauma 36, 2863–2871 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Wright, D.W., Yeatts, S.D., Silbergleit, R., Palesch, Y.Y., Hertzberg, V.S., Frankel, M., Goldstein, F.C., Caveney, A.F., Howlett-Smith, H., Bengelink, E.M., Manley, G.T., Merck, L.H., Janis, L.S., and Barsan, W.G.; NETT Investigators. (2014). Very early administration of progesterone for acute traumatic brain injury. N. Engl. J. Med. 371, 2457–2466 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Papa, L., Robertson, C.S., Wang, K.K., Brophy, G.M., Hannay, H.J., Heaton, S., Schmalfuss, I., Gabrielli, A., Hayes, R.L., and Robicsek, S.A. (2015). Biomarkers improve clinical outcome predictors of mortality following non-penetrating severe traumatic brain injury. Neurocrit. Care 22, 52–64 [DOI] [PubMed] [Google Scholar]
- 18. Meier, T.B., Nelson, L.D., Huber, D.L., Bazarian, J.J., Hayes, R.L., and McCrea, M.A. (2017). Prospective assessment of acute blood markers of brain injury in sport-related concussion. J. Neurotrauma 34, 3134–3142 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Papa, L., Akinyi, L., Liu, M.C., Pineda, J.A., Tepas, J.J. III, Oli, M.W., Zheng, W., Robinson, G., Robicsek, S.A., Gabrielli, A., Heaton, S.C., Hannay, H.J., Demery, J.A., Brophy, G.M., Layon, J., Robertson, C.S., Hayes, R.L., and Wang, K.K. (2010). Ubiquitin C-terminal hydrolase is a novel biomarker in humans for severe traumatic brain injury. Crit. Care Med. 38, 138–144 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Office of Environmental Information. (2006). Data Quality Assessment: Statistical Methods for Practitioners EPA QA/G-9S. United States Environmental Protection Agency 1-190. Office of Environmental Information: Washington D.C [Google Scholar]
- 21. Baker, A.J., Rhind, S.G., Morrison, L.J., Black, S., Crnko, N.T., Shek, P.N., and Rizoli, S.B. (2009). Resuscitation with hypertonic saline-dextran reduces serum biomarker levels and correlates with outcome in severe traumatic brain injury patients. J. Neurotrauma 26, 1227–1240 [DOI] [PubMed] [Google Scholar]
- 22. Hellewell, S.C., Mondello, S., Conquest, A., Shaw, G., Madorsky, I., Deng, J.V., Little, L., Kobeissy, F., Bye, N., Bellomo, R., Cooper, D.J., Vallance, S., Board, J., and Morganti-Kossmann, M.C. (2018). Erythropoietin does not alter serum profiles of neuronal and axonal biomarkers after traumatic brain injury: findings from the Australian EPO-TBI Clinical Trial. Crit. Care Med. 46, 554–561 [DOI] [PubMed] [Google Scholar]
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