P 48 The time of the ALSFRS-R to decrease to 50% (D50) in a sigmoidal decay model sufficiently describes the complete disease course of amyotrophic lateral sclerosis. Issue 10 (October 2017)

• Record Type: Journal Article
• Authors: Stubendorff, B.; Grehl, T.; Neuwirth, C.; Rödiger, A.; Gunkel, A.; Radscheidt, M.; Ilse, B.; Prell, T.; Witte, O.W.; Weber, M.; Grosskreutz, J.
• Is Part Of: Clinical neurophysiology. Volume 128:Issue 10(2017:Oct.)
• Page Start: e353
• Page End: e354
• Publication Date: 2017-10
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2017.06.127
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Introduction: The progression of ALSFRS-R is not linear (Gordon et al., 2010; Proudfoot et al., 2016 ); the often used calculated progression rate using PR = ((48-ALSFRS-R)/disease duration) presents the progression at a certain time point rather than reflecting the entire disease course. A model describing the disease progression at different time points would facilitate the stratification of ALS patients according to disease severity and progression type and will in combination with other biomarkers enable identification of effective drugs in clinical trials. Objectives: The aim of our study was to develop a model that describes the disease course mathematically for each individual ALS patient which can be estimated from regularly ascertained ALSFRS-R scores. Methods: The model is based on the observation that after symptom onset the ALSFRS-R does not drop immediately but decays slowly first followed by a period of uniform progression which is captured in most clinical trials due to a relatively late inclusion requiring at least laboratory supported ALS according to EL Escorial/Awaji criteria. With increasing disability, ALSFRS-R seems to reach a plateau again. Thus we used a function which describes the transition between two states, i.e. full health to maximum disease. The model results in two parameters describing the ALS disease course: D50 = time point when ALSFRS-R drops to 24 and dx = slope of ALSFRS-R decrease. Results: Based on the ALSFRS-R scores and the disease duration from onset to ALSFRS-R date from a cohort of 339 patients in our database, we have been able to determine D50 and dx in 90% of patients using the Microsoft® Excel Add-In Solver tool with dynamic presets derived from the conventional estimation of ALSFRS-R progression. Mean age at symptom onset was 59.4 years. ALSFRS-R at the first visit was 36.6+/−7.9 and 28.2+/−10.7 at the last recorded visit. The relationship between D50 and dx was highly linear ( R 2 = 0.993), so that using modeling the whole disease course can be described using only one of these two parameters, i.e. D50. Conclusion: D50 is more accessible to the end user as the number of months passed to reach an ALSFRS-R of 24 along the model based trajectory. In addition, any sampling taken at any given time point can be correlated to any one parameter which allows the exploration of early prognostic markers and possibly improve the readout in clinical trials. Acknowledgment: This research is supported byBMBF (Bundesministerium für Bildung and Forschung) in the framework of the E-RARE programme (PYRAMID) andJPND (OnWebDUALS).