Dataset Information

State and metropolitan area-based amyotrophic lateral sclerosis (ALS) surveillance.

ABSTRACT: Our objective was to develop state and metropolitan area-based surveillance projects to describe the characteristics of those with ALS and to assist with evaluating the completeness of the National ALS Registry. Because the literature suggested that ethnic/racial minorities have lower incidence of ALS, three state and eight metropolitan areas were selected to over-represent ethnic/racial minorities to have a sufficient number of minority patients. Project activities relied on reports from medical providers and medical records abstraction. The project areas represented approximately 27% of the U.S.The combined racial and ethnic distribution of these areas is 64.4% white, 16.0% African-American, 6.7% Asian, and 28.3% Hispanic. Most neurologists did not diagnose or provide care for ALS patients. The number of unique patients reported was close to expected (5883 vs. 6673). Age and gender distribution of patients was similar to the literature. The crude average annual incidence rate was 1.52 per 100,000 person-years, CI 1.44-1.61, and the 2009 prevalence rate was 3.84 per 100,000 population, CI 3.70-3.97. In conclusion, this study represents the largest number of clinically diagnosed ALS patients reported by neurologists in the U.S. Comparison of these data with those in the National ALS Registry will help evaluate the completeness of administrative databases.

SUBMITTER: Wagner L

PROVIDER: S-EPMC4732418 | biostudies-other | 2015 Jan-Feb

REPOSITORIES: biostudies-other

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Project description:Thoughtful clinical trial design is critical for efficient therapeutic development, particularly in the field of amyotrophic lateral sclerosis (ALS), where trials often aim to detect modest treatment effects among a population with heterogeneous disease progression. Appropriate outcome measure selection is necessary for trials to provide decisive and informative results. Investigators must consider the outcome measure's reliability, responsiveness to detect change when change has actually occurred, clinical relevance, and psychometric performance. ALS clinical trials can also be performed more efficiently by utilizing statistical enrichment techniques. Innovations in ALS prediction models allow for selection of participants with less heterogeneity in disease progression rates without requiring a lead-in period, or participants can be stratified according to predicted progression. Statistical enrichment can reduce the needed sample size and improve study power, but investigators must find a balance between optimizing statistical efficiency and retaining generalizability of study findings to the broader ALS population. Additional progress is still needed for biomarker development and validation to confirm target engagement in ALS treatment trials. Selection of an appropriate biofluid biomarker depends on the treatment mechanism of interest, and biomarker studies should be incorporated into early phase trials. Inclusion of patients with ALS as advisors and advocates can strengthen clinical trial design and study retention, but more engagement efforts are needed to improve diversity and equity in ALS research studies. Another challenge for ALS therapeutic development is identifying ways to respect patient autonomy and improve access to experimental treatment, something that is strongly desired by many patients with ALS and ALS advocacy organizations. Expanded access programs that run concurrently to well-designed and adequately powered randomized controlled trials may provide an opportunity to broaden access to promising therapeutics without compromising scientific integrity or rushing regulatory approval of therapies without adequate proof of efficacy.

Dataset Information

State and metropolitan area-based amyotrophic lateral sclerosis (ALS) surveillance.

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