From measurement to biomarker trajectories: platform-agnostic Z score analysis of serum NfL and GFAP in ocrelizumab-treated multiple sclerosis
摘要
Serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) are promising multiple sclerosis (MS) biomarkers, but biological confounding and inter-assay variability limit real-world use. We assessed whether Z score normalisation enables platform-agnostic monitoring in people with MS (pwMS) under ocrelizumab, and which early timepoint best stratifies subsequent biomarker trajectories.
MethodsThis pooled multicentre analysis of three German cohorts included pwMS treated with ocrelizumab for ≥ 12 months. Elecsys® or Simoa® assays were harmonised using covariate-adjusted Z scores. We evaluated biomarker 24-month trajectories and whether stratification and relative reductions predicted 24-month biomarker-status.
Results430 pwMS were included [78% relapsing MS (RMS), 22% primary progressive MS (PPMS)]. Baseline sNfL Z scores were higher in RMS; sGFAP Z scores were similar. Multivariable analyses linked higher expanded disability status scale to elevation of both biomarkers, while younger age was independently associated with higher sNfL. Following ocrelizumab, sNfL decreased in RMS while sGFAP remained stable. People with RMS and concurrent baseline elevation sustained the highest levels, diverging from the stable PPMS profile. Month-12 combined elevation best predicted persisting 24-month elevation, outperforming baseline and 6-month assessments. Crucially, failing to achieve a ≥ 50% relative reduction at month 12 strongly predicted persistent 24-month elevation for sNfL (OR 7.14, 95% CI 1.35–37.75) and sGFAP (OR 32.08, 95% CI 5.10–201.67).
ConclusionsZ score normalisation enabled platform-agnostic framework for MS monitoring of downstream biological trajectories. We identify a practical 12-month exploratory responder threshold: pwMS failing to reach a ≥ 50% relative Z score reduction represent a group with persistent biomarker elevation, supporting closer clinical surveillance.