Validation of a proteomic biomarker panel to diagnose minor-stroke and transient ischaemic attack: phase 2 of SpecTRA,a large scale translational study |
| |
Authors: | Andrew M Penn Viera K Saly Shelagh B Coutts Mary L Lesperance Robert F Balshaw |
| |
Institution: | 1. Department of Neurosciences, Stroke Rapid Assessment Clinic, Island Health Authority, Victoria, Canada;2. Departments of Clinical Neurosciences, Radiology, and Community Health Services, University of Calgary, Calgary, Canada;3. Department of Mathematics and Statistics, University of Victoria, Victoria, Canada;4. George &5. Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg, Canada |
| |
Abstract: | AbstractOBJECTIVE: To validate our previously developed 16 plasma-protein biomarker panel to differentiate between transient ischaemic attack (TIA) and non-cerebrovascular emergency department (ED) patients.METHOD: Two consecutive cohorts of ED patients prospectively enrolled at two urban medical centers into the second phase of SpecTRA study (training, cohort 2A, n?=?575; test, cohort 2B, n?=?528). Plasma samples were analyzed using liquid chromatography/multiple reaction monitoring-mass spectrometry. Logistic regression models which fit cohort 2A were validated on cohort 2B.RESULTS: Three of the panel proteins failed quality control and were removed from the panel. During validation, panel models did not outperform a simple motor/speech (M/S) deficit variable. Post-hoc analyses suggested the measured behaviour of L-selectin and coagulation factor V contributed to poor model performance. Removal of these proteins increased the external performance of a model containing the panel and the M/S variable.CONCLUSIONS: Univariate analyses suggest insulin-like growth factor-binding protein 3 and serum paraoxonase/lactonase 3 are reliable and reproducible biomarkers for TIA status. Logistic regression models indicated L-selectin, apolipoprotein B-100, coagulation factor IX, and thrombospondin-1 to be significant multivariate predictors of TIA. We discuss multivariate feature subset analyses as an exploratory technique to better understand a panel’s full predictive potential. |
| |
Keywords: | TIA transient ischaemic attack TIA biomarkers stroke biomarkers stroke proteomic plasma biomarkers |
|
|