Multiple Sclerosis Journal · 2023 · 17 citations · 27 references
MedicineNeurologyNeuroscienceDiagnostic ImagingDiagnostic RadiologyNeuropathologyBrain ImagingImaging BiomarkersInflammatory BiomarkersMagnetic Resonance ImagingMultiple SclerosisNeuroinflammationBland-altman PlotNeurofilament AbnormalitiesNeurofilament BiomarkersNeurofilament ProteinsNeuroinflammatory BiomarkersNeuroinflammatory MarkersNeurological Disease BiomarkersSerum Biomarkers
BACKGROUND: Contrast-enhancing magnetic resonance imaging (MRI) lesions (CELs) indicate acute multiple sclerosis inflammation. Serum biomarkers, neurofilament light (sNfL), and glial fibrillary acidic protein (sGFAP) may increase in the presence of CELs, and indicate a need to perform MRI. OBJECTIVE: We assessed the accuracy of biomarkers to detect CELs. METHODS: = 557, 66% female). Optimal cut-points from Bland-Altman analysis for spot biomarker level and Youden's index for delta-change from remission were evaluated. RESULTS: A total of 116 patients (21%) had CELs. A spot sNfL measurement >23.0 pg/mL corresponded to 7.0 times higher odds of CEL presence (95% CI: 3.8, 12.8), with 25.9% sensitivity, 95.2% specificity, operating characteristic curve (AUC) 0.61; while sNfL delta-change >30.8% from remission corresponded to 5.0 times higher odds (95% CI: 3.2, 7.8), 52.6% sensitivity, 81.9% specificity, AUC 0.67. sGFAP had poor CEL detection. In patients > 50 years, neither cut-point remained significant. sNfL delta-change outperformed spot levels at identifying asymptomatic CELs (AUC 0.67 vs 0.59) and in patients without treatment escalation between samples (AUC 0.67 vs 0.57). CONCLUSION: Spot sNfL >23.0 pg/mL or a 30.8% increase from remission provides modest prediction of CELs in patients <50 years; however, low sNfL does not obviate the need for MRI.
27
Classification accuracy and cut point selection
Xinhua Liu · Statistics in Medicine · 2012 · 678 citations