Many factors potentially contribute to survival in ALS, making the prediction of survival for individuals challenging. Although prior studies have identified potential variables that predict survival, many of these studies are of small sample size and the findings are often not replicated in subsequent studies. Multivariate analysis of clinical, demographic, and genetic data on large cohorts is necessary to better model survival in ALS. We report the baseline clinical, demographic, and genetic data collected in our ongoing clinical registry and their influence on survival.
Objective: To determine factors that are important in survival in patients with amyotrophic lateral sclerosis.
Age at diagnosis, gender, race, site of onset, time to diagnosis, FVC, and BMI were collected from 1,986 patients seen at Mayo Clinic Florida Center between 1998 and 2019. A subgroup of 948 consented for analysis of C9orf72 repeat expansion. 1,450 patients were confirmed to be deceased at the time of analysis. Survival was determined from reported symptom onset and query of national death databases. Kaplan-Meier survival analysis and Cox regression modeling were used for univariate and multivariate analyses.
The median survival was 30.7 months from reported onset and 17.6 months from first diagnosis. While nearly all baseline features were associated with survival in univariate analysis, age, FVC, BMI, C9orf72 status, and time to diagnosis were independent predictors of survival in multivariate analysis.
The median survival of our cohort is consistent with prior series. Contrary to prior studies, bulbar site of onset and gender were not found to be predictors of survival in multivariate analysis. This illustrates the need for multivariate analyses of large cohorts of patients to study the effect of individual factors on survival in ALS.