Linear estimates of rates of disease progression as predictors of survivalin patients with ALS entering clinical trials

Authors
Citation
C. Armon et D. Moses, Linear estimates of rates of disease progression as predictors of survivalin patients with ALS entering clinical trials, J NEUR SCI, 160, 1998, pp. S37-S41
Citations number
9
Categorie Soggetti
Neurosciences & Behavoir
Journal title
JOURNAL OF THE NEUROLOGICAL SCIENCES
ISSN journal
0022510X → ACNP
Volume
160
Year of publication
1998
Supplement
1
Pages
S37 - S41
Database
ISI
SICI code
0022-510X(199810)160:<S37:LEOROD>2.0.ZU;2-U
Abstract
Maximal voluntary isometric grip and foot dorsiflexion (FD) strength and fo rced vital capacity (FVC) were obtained in 62 patients with ALS at or close to enrollment into two clinical trials. The agents tested did not slow dis ease progression. Isometric strength data were standardized, and the worse side was taken. FVC was expressed as a percentage of the predicted value (F VC%). We derived linear estimates of rates of disease progression based on the isometric myometry and FVC measures and on disease duration. Forty one patients were known to have died or to have undergone tracheostomy for vent ilatory support. Probability of tracheostomy-free survival was calculated u sing the Kaplan-Meier method. The measured values, the linear estimates for rates of decline of these values, gender, age at onset, bulbar vs. spinal onset, height and weight were tested as risk factors within the Cox proport ional hazards model, using regression techniques. When tested individually, estimates of rates of decline based on all three measures (FD, grip and FV C%) were the only statistically significant risk factors (P<0.005). Multiva riate analysis resulted in a 3-variable model (chi-square=75.3, P<0.00001) in which estimated rates of decline of FD strength and of FVC%, and bulbar onset were independently significant (P<0.0001, P<0.0007 and P<0.05, respec tively). We conclude that linear estimates of the rate of disease progressi on till enrollment into a clinical trial may be better predictors of patien t survival than demographic data or discrete biologic measures. (C) 1998 El sevier Science B.V. All rights reserved.