Advancing disease monitoring of amyotrophic lateral sclerosis with the compound muscle action potential scan

Boudewijn T H M Sleutjes, Anna Bystrup Jacobsen, Hatice Tankisi, N Gorkem Sirin, A Emre Oge, Robert D Henderson, Pieter A van Doorn, Leonard H van den Berg, Ruben P A van Eijk

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OBJECTIVE: To determine which compound muscle action potential (CMAP) scan-derived electrophysiological markers are most sensitive for monitoring disease progression in amyotrophic lateral sclerosis (ALS), and whether they hold value for clinical trials.

METHODS: We used four independent patient cohorts to assess longitudinal patterns of a comprehensive set of electrophysiological markers including their association with the ALS functional rating scale (ALSFRS-R). Results were translated to trial sample size requirements.

RESULTS: In 65 patients, 225 thenar CMAP scan recordings were obtained. Electrophysiological markers showed extensive variation in their longitudinal trajectories. Expressed as standard deviations per month, motor unit number estimation (MUNE) values declined by 0.09 (CI 0.07-0.12), D50, a measure that quantifies CMAP scan discontinuities, declined by 0.09 (CI 0.06-0.13) and maximum CMAP by 0.05 (CI 0.03-0.08). ALSFRS-R declined fastest (0.12, CI 0.08 - 0.15), however the between-patient variability was larger compared to electrophysiological markers, resulting in larger sample sizes. MUNE reduced the sample size by 19.1% (n = 388 vs n = 314) for a 6-month study compared to the ALSFRS-R.

CONCLUSIONS: CMAP scan-derived markers show promise in monitoring disease progression in ALS patients, where MUNE may be its most suitable derivate.

SIGNIFICANCE: MUNE may increase clinical trial efficiency compared to clinical endpoints.

Original languageEnglish
Pages (from-to)3152-3159
Number of pages8
JournalClinical Neurophysiology
Issue number12
Early online date19 Oct 2021
Publication statusPublished - Dec 2021


  • Clinical trials
  • Compound muscle action potential scan
  • Electrophysiological markers
  • Monitoring disease progression
  • Motor unit number estimation
  • Motor unit sizes


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