Progression in ALS is not linear but is curvilinear

J Neurol. 2010 Oct;257(10):1713-7. doi: 10.1007/s00415-010-5609-1. Epub 2010 Jun 8.


The aim of the study is to determine the shape of the progression curve in ALS, assess the impact of clinical variables on the rate of progression, and evaluate the association between functional decline and survival. Data were prospectively collected and entered into a clinical database from all patients seen in 2002-2008 at the Centre SLA, Hôpital de la Salpêtrière, Paris. Variables analyzed were demographic and baseline information, the ALS functional rating scale (ALSFRS-R), strength testing (MMT), and survival. Generalized additive mixed models characterized changes in ALSFRS-R and MMT scores over time. Linear mixed effects assessed the impact of demographic and clinical measures on rate of progression and Cox models examined their effect on survival. Of 2,452 patients with ALS identified, 1,884 had adequate data for analysis. The ALSFRS-R and MMT declined in a curvilinear way; a quadratic fit described the trends but a linear fit did not. The total ALSFRS-R score was negatively associated with age-of-onset (p < 0.001), and positively associated with baseline ALSFRS-R (p < 0.001) as well as more severe bulbar features (p < 0.001). Higher rate of decline in ALSFRS-R and MMT, older age-at-onset and bulbar-onset predicted shorter survival. Deterioration in ALS is non-linear. The early and late phases of the illness show the most rapid rates of decline. Older age and bulbar signs are associated with a steeper decline, and along with more rapid initial rate of decline, but not current functional status, also predict survival.

MeSH terms

  • Adult
  • Aged
  • Amyotrophic Lateral Sclerosis / epidemiology
  • Amyotrophic Lateral Sclerosis / mortality
  • Amyotrophic Lateral Sclerosis / physiopathology*
  • Disease Progression*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Nonlinear Dynamics*
  • Predictive Value of Tests
  • Proportional Hazards Models
  • Retrospective Studies
  • Survival Analysis
  • Time Factors