To evaluate the sensitivity to change of differently calculated quantitative scores from motor evoked potentials (MEP) in patients with primary progressive multiple sclerosis (PPMS). Twenty patients with PPMS had MEP to upper and lower limbs at baseline, years 1 and 2 measured in addition to clinical assessment [Expanded Disability Status Scale (EDSS), ambulation score]; a subsample ( = 9) had a nine-hole peg test (NHPT) and a timed 25-foot walk (T25FW). Quantitative MEP scores for upper limbs (qMEP-UL), lower limbs (qMEP-LL), and all limbs (qMEP) were calculated in three different ways, based on -transformed central motor conduction time (CMCT), shortest corticomuscular latency (CxM-sh), and mean CxM (CxM-mn). Changes in clinical measures and qMEP metrics were analyzed by repeated-measures analysis of variance (rANOVA), and a factor analysis was performed on change in qMEP metrics. Expanded Disability Status Scale and ambulation score progressed in the rANOVA model ( < 0.05; comparison baseline-year 2, < 0.1). Lower limb and combined qMEP scores showed significant deterioration of latency ( < 0.01, MEP-LL_CxM-sh: < 0.05) and in comparisons (baseline-year 2, < 0.05), qMEP_CxM-mn even over 1 year ( < 0.05). Effect sizes were higher for qMEP scores than for clinical measures, and slightly but consistently higher when based on CxM-mn compared to CxM-sh or CMCT. Subgroup analysis yielded no indication of higher sensitivity of timed clinical measures over qMEP scores. Two independent factors were detected, the first mainly associated with qMEP-LL, the second with qMEP-UL, explaining 65 and 29% of total variability, respectively. Deterioration in qMEP scores occurs earlier than EDSS progression in patients with PPMS. Upper and lower limb qMEP scores contribute independently to measuring change, and qMEP scores based on mean CxM are advantageous. The capability to detect subclinical changes longitudinally is a unique property of EP and complementary to clinical assessment. These features underline the role of EP as candidate biomarkers to measure effects of therapeutic interventions in PPMS.
Copyright © 2020 Hardmeier, Schindler, Kuhle and Fuhr.