ECTRIMS eLearning

Multicenter sensory and motor evoked potentials: definition of improvement beyond measurement variability in single subjects
Author(s): ,
M. Hardmeier
Affiliations:
Department of Neurology, Hospital of the University of Basel, Basel, Switzerland
,
F. Jacques
Affiliations:
Clinique Neuro-Outaouais, Gatineau, Quebec JJ A, QC, Canada
,
P. Albrecht
Affiliations:
Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
,
H. Bousleiman
Affiliations:
Department of Neurology, Hospital of the University of Basel, Basel, Switzerland
,
C. Schindler
Affiliations:
Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland
,
L. Leocani
Affiliations:
Depts. Neurology and Neurorehabilitation, Ospedale San Raffaele, Milano, Italy
P. Fuhr
Affiliations:
Department of Neurology, Hospital of the University of Basel, Basel, Switzerland
ECTRIMS Learn. Hardmeier M. 10/10/18; 229409; EP1572
Martin Hardmeier
Martin Hardmeier
Contributions
Abstract

Abstract: EP1572

Type: Poster Sessions

Abstract Category: Pathology and pathogenesis of MS - Biomarkers

Background: Sensory and motor evoked potentials (SEP; MEP) quantitatively measure signal conduction in multiple sclerosis (MS). They may serve as outcomes in clinical trials. Here we suggest cut-offs to define improvement as a significant reduction of latency in single subjects.
Methods: 21 patients with MS (mean age: 47.3 years, median EDSS: 3.0, 74% relapsing MS, 26% progressive MS) were evaluated at two time points (tp) within a 30 day window with median and tibial SEP and upper (UL) and lower limb (LL) MEP in three centers1-3. Five neurophysiologists independently marked all curves using custom server-based software (EPMark). N20, P40, mean (mn) and shortest (sh) cortico-muscular-latencies (CxM) and a modified quantitative EP-score (mqEPS=sum of z-transformed results from each test/number of tests; unit= mean standard deviation) were analyzed.
Using mixed effects linear models (outcome: tp 1 and 2 combined) total variance and its components were estimated. The standard error related to intra-subject longitudinal variability (SElong; assuming 2 central readers) was used to determine the measurement variability D with a margin z above which a difference is not attributable to D in 95% of cases, using: D=SElong*z95, with z95=1.645 (95th percentile of standard normal distribution, one-sided).
Results: Proportions of patients with none, 1-2, 3-4 or >4 pathological tests were 41%, 23%, 27% and 9%, respectively. For MEP, median and tibial SEP, rater variability was < 7%, 10% and 16% of total variance, respectively. Variability of SEP is partly explained by ambiguity in peak definition as tp2 rating was done blinded to tp1 results. In MEP, D ranged from 2.1 to 3.0ms (MEP-UL shCxM: D=2.4ms, mnCxM: D=2.1ms; MEP-LL shCxM: D=3.0ms, mnCxM: D=2.2ms), in SEP from 1.0 to 4.9ms (N20: D=1.0ms, P40: D=4.9ms), in mqEPS: D=0.94. Whether improvement (I) is to be defined as any difference beyond D (I>D) or as (I>C+D) with C denoting a minimal required additional change for security depends on the study setting.
Conclusion: Our results allow the definition of improvement in single EP tests (one limb, one modality) and may be used to define responders to remyelinating drugs, for example as subjects with improvement in at least one test. Using the mqEPS avoids bias in case of improvement in one test but deterioration in the others.
Disclosure: The study was supported by an unconditional research grant (investigator-initiated trial grant) from Biogen Inc., Cambridge, Massachusetts, USA.
Martin Hardmeiers institution has received fees from Roche for consultancy services; his research is or was supported by the Swiss Multiple Sclerosis Society and the Swiss National Science Foundation SPUM 33CM30_124115 and 33CM30_140338. Dr F Jacques has received honorariums and unrestricted grants from Biogen, Sanofi-Genzyme, Merck-Serono for participating in ad boards, doing presentations and for conducting investigator initiated trials. Philipp Albrecht reports grants, personal fees and non-financial support from Allergan, Biogen, Ipsen, Merz Pharmaceuticals, Novartis, and Roche, personal fees and non-financial support from Bayer Healthcare, and Merck, and non-financial support from Sanofi-Aventis/Genzyme. Habib Bousleiman has no conflict of interest to declare. Christian Schindler has no conflicts of interest to disclose. L. Leocani received honoraria for consulting services from Merck, Roche, Biogen and for speaking activities from Teva; research support from Merck, Biogen, Novartis; travel support from Merck, Roche, Biogen, Almirall. Peter Fuhr´s research is or was supported by the Swiss National Science Foundation SPUM 33CM30_124115 and 33CM30_140338 (PI), Swiss Multiple Sclerosis Society, Synapsis Foundation, Parkinson Schweiz, Novartis Research Foundation, Gossweiler Foundation, Freiwillige Akademische Gesellschaft Basel, Mach-Gaensslen-Stiftung, Botnar Foundation, Bangerter Foundation, and by unconditional research grants from industry (Roche, AbbVie, Biogen, General Electrics).

Abstract: EP1572

Type: Poster Sessions

Abstract Category: Pathology and pathogenesis of MS - Biomarkers

Background: Sensory and motor evoked potentials (SEP; MEP) quantitatively measure signal conduction in multiple sclerosis (MS). They may serve as outcomes in clinical trials. Here we suggest cut-offs to define improvement as a significant reduction of latency in single subjects.
Methods: 21 patients with MS (mean age: 47.3 years, median EDSS: 3.0, 74% relapsing MS, 26% progressive MS) were evaluated at two time points (tp) within a 30 day window with median and tibial SEP and upper (UL) and lower limb (LL) MEP in three centers1-3. Five neurophysiologists independently marked all curves using custom server-based software (EPMark). N20, P40, mean (mn) and shortest (sh) cortico-muscular-latencies (CxM) and a modified quantitative EP-score (mqEPS=sum of z-transformed results from each test/number of tests; unit= mean standard deviation) were analyzed.
Using mixed effects linear models (outcome: tp 1 and 2 combined) total variance and its components were estimated. The standard error related to intra-subject longitudinal variability (SElong; assuming 2 central readers) was used to determine the measurement variability D with a margin z above which a difference is not attributable to D in 95% of cases, using: D=SElong*z95, with z95=1.645 (95th percentile of standard normal distribution, one-sided).
Results: Proportions of patients with none, 1-2, 3-4 or >4 pathological tests were 41%, 23%, 27% and 9%, respectively. For MEP, median and tibial SEP, rater variability was < 7%, 10% and 16% of total variance, respectively. Variability of SEP is partly explained by ambiguity in peak definition as tp2 rating was done blinded to tp1 results. In MEP, D ranged from 2.1 to 3.0ms (MEP-UL shCxM: D=2.4ms, mnCxM: D=2.1ms; MEP-LL shCxM: D=3.0ms, mnCxM: D=2.2ms), in SEP from 1.0 to 4.9ms (N20: D=1.0ms, P40: D=4.9ms), in mqEPS: D=0.94. Whether improvement (I) is to be defined as any difference beyond D (I>D) or as (I>C+D) with C denoting a minimal required additional change for security depends on the study setting.
Conclusion: Our results allow the definition of improvement in single EP tests (one limb, one modality) and may be used to define responders to remyelinating drugs, for example as subjects with improvement in at least one test. Using the mqEPS avoids bias in case of improvement in one test but deterioration in the others.
Disclosure: The study was supported by an unconditional research grant (investigator-initiated trial grant) from Biogen Inc., Cambridge, Massachusetts, USA.
Martin Hardmeiers institution has received fees from Roche for consultancy services; his research is or was supported by the Swiss Multiple Sclerosis Society and the Swiss National Science Foundation SPUM 33CM30_124115 and 33CM30_140338. Dr F Jacques has received honorariums and unrestricted grants from Biogen, Sanofi-Genzyme, Merck-Serono for participating in ad boards, doing presentations and for conducting investigator initiated trials. Philipp Albrecht reports grants, personal fees and non-financial support from Allergan, Biogen, Ipsen, Merz Pharmaceuticals, Novartis, and Roche, personal fees and non-financial support from Bayer Healthcare, and Merck, and non-financial support from Sanofi-Aventis/Genzyme. Habib Bousleiman has no conflict of interest to declare. Christian Schindler has no conflicts of interest to disclose. L. Leocani received honoraria for consulting services from Merck, Roche, Biogen and for speaking activities from Teva; research support from Merck, Biogen, Novartis; travel support from Merck, Roche, Biogen, Almirall. Peter Fuhr´s research is or was supported by the Swiss National Science Foundation SPUM 33CM30_124115 and 33CM30_140338 (PI), Swiss Multiple Sclerosis Society, Synapsis Foundation, Parkinson Schweiz, Novartis Research Foundation, Gossweiler Foundation, Freiwillige Akademische Gesellschaft Basel, Mach-Gaensslen-Stiftung, Botnar Foundation, Bangerter Foundation, and by unconditional research grants from industry (Roche, AbbVie, Biogen, General Electrics).

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