Andrew M Penn1, Maximilian B Bibok2, Viera K Saly1, Shelagh B Coutts3, Mary L Lesperance4, Robert F Balshaw5, Kristine Votova2,6, Nicole S Croteau2,4, Anurag Trivedi1, Angela M Jackson7, Janka Hegedus3, Evgenia Klourfeld3, Amy Y X Yu8, Charlotte Zerna3, Jayesh Modi9, Philip A Barber10, Gordon Hoag11, Christoph H Borchers7,12,13,14. 1. a Department of Neurosciences , Stroke Rapid Assessment Clinic, Island Health Authority , Victoria , Canada. 2. b Department of Research and Capacity Building , Island Health Authority , Victoria , Canada. 3. c Departments of Clinical Neurosciences, Radiology, and Community Health Services , University of Calgary , Calgary , Canada. 4. d Department of Mathematics and Statistics , University of Victoria , Victoria , Canada. 5. e George & Fay Yee Centre for Healthcare Innovation , University of Manitoba , Winnipeg , Canada. 6. f Division of Medical Sciences , University of Victoria , Victoria , Canada. 7. g Genome British Columbia Proteomics Centre, University of Victoria , Victoria , Canada. 8. h Department of Medicine , University of Toronto , Toronto , Canada. 9. i Department of Radiology , Foothills Medical Centre , Calgary , Canada. 10. j Department of Clinical Neurosciences , University of Calgary , Calgary , Canada. 11. k Department of Laboratory Medicine, Pathology & Medical Genetics , Island Health Authority , Victoria , Canada. 12. l Department of Biochemistry and Microbiology , University of Victoria , Victoria , Canada. 13. m Gerald Bronfman Department of Oncology , McGill University , Montreal , Canada. 14. n Proteomics Centre, Segal Cancer Centre , Lady Davis Institute , Montreal , Canada.
Abstract
OBJECTIVE: 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.
OBJECTIVE: 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.
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