Objective:

To describe data on demographics, clinical characteristics, pre-index disease progression milestones and healthcare resource utilization (HCRU), and referral patterns of patients with amyotrophic lateral sclerosis (ALS) enrolled in a real-world, US-based administrative claims database. 

Background:

ALS is a rare and progressive neurodegenerative disease that is difficult to diagnose. Diagnosis of ALS often involves referrals and time to diagnosis is influenced by the referring physician/specialty area. Diagnostic delays are common, yet timely diagnosis is critical for initiating effective treatment, emphasizing the need to understand referral patterns and their impact on ALS diagnosis. There are currently 3 US Food and Drug Administration-approved treatments for patients with ALS: riluzole, edaravone (Radicava® IV [intravenous] and Radicava ORS® oral suspension; Mitsubishi Tanabe Pharma America [MTPA]), and tofersen (for patients with a superoxide dismutase 1 mutation).

Design/Methods:

Patients with ALS continuously enrolled in Optum’s de-identified Clinformatics® Data Mart (CDM) from January 2007 to December 2023 were included and grouped based on ALS treatment pattern (ie, untreated, riluzole-only, MTPA edaravone±riluzole). Index date was the ALS diagnosis date.

Results:

Patients with ALS with a ≥2-year history prior to index ALS diagnosis (n=8120) enrolled in Optum’s CDM were a mean (SD) age of 68.5 (12.9) years, 54.8% male, and 65.5% were covered by Medicare (vs commercial insurance). Pre-index disease progression milestones and HCRU were measured. Overall, the top 3 specialty areas that diagnosed patients with ALS were psychiatry and neurology (37.6%), internal medicine (15.5%), and general acute care hospital (9.5%). Overall, the top 3 specialty areas that diagnosed patients referred to them were psychiatry and neurology (50.8%), internal medicine (17.8%), and family medicine (15.9%).

Conclusions:

These real-world data may help clinicians and payers better understand the referral patterns of patients with ALS, which may aid in reducing delays in diagnosis and treatment.