It is now possible to slow the disease progression of amyotrophic lateral sclerosis (ALS), but documented improvement in the quality of life of ALS patients has been difficult to quantitate. Putative mechanisms involved in motor neuron degeneration in ALS include oxidative damage, mitochondrial dysf
Linear estimates of disease progression predict survival in patients with amyotrophic lateral sclerosis
✍ Scribed by Carmel Armon; Michael C. Graves; Dharmaseli Moses; Delano K. Forté; Linda Sepulveda; Stephanie M. Darby; Richard A. Smith
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 165 KB
- Volume
- 23
- Category
- Article
- ISSN
- 0148-639X
No coin nor oath required. For personal study only.
✦ Synopsis
We have shown that linear estimates of rates of disease progression (LEP), derived from isometric myometry [grip or foot dorsiflexion (FD) strength] and forced vital capacity (FVC%), are clinically and statistically significant predictors of survival of patients with amyotrophic lateral sclerosis (ALS) from date of disease onset and, except those based on grip strength, of survival from the date of measurement. We tested these results in 2 additional groups of patients: 1) those who participated in a previously reported Protropin (GH) study; and 2) those enrolled in two other clinical trials (group 2). The LEP were derived and tested as predictors of survival. In a Cox proportional hazards model, LEP based on all measures predicted survival from disease onset in both groups of patients. Using cutoff points determined within the original group to stratify patients in the validation groups into faster and slower progressing subgroups resulted in statistically significant separation of survival curves from disease onset in group 2 for all LEP and in group 1 (the GH group) for LEP derived from FD strength; and, for survival from date of measurement in group 2, when stratified by LEP based on FD strength or FVC%. LEP based on data generated by myometry or pulmonary function studies have now been shown to predict survival in 3 unrelated groups of patients with ALS entering clinical trials. Their precise use in clinical trial design needs to be explored further.
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