PREVALENCE OF DEVELOPMENTAL AND EPILEPTIC ENCEPHALOPATHIES (DEES) AMONG PATIENTS WITH EPILEPSY: A US CLAIMS ANALYSIS
Author(s)
Mikkel Pedersen, PhD, Gauri Dixit, PhD, Stephane A. Regnier, PhD, MBA.
H. Lundbeck A/S, Copenhagen, Denmark.
H. Lundbeck A/S, Copenhagen, Denmark.
OBJECTIVES: DEEs are associated with treatment-resistant seizures, frequent epileptiform activity, and developmental slowing or regression. ‘DEE’ provides a diagnostic entry point for an etiologically heterogeneous group of disorders, although adoption of the 2024 DEE-specific ICD-10 code, G93.45, in routine US claims coding is low. Patients are currently identified using claims-based proxy definitions. Here, we estimated the proportion of patients with poorly controlled DEEs to determine the corresponding population prevalence using a large US administrative claims database.
METHODS: The IQVIA PharMetrics database was analyzed for patients with continuous enrollment from 2023-2024. Epilepsy was identified by ≥1 ICD-10 G40.xx diagnosis, with DEEs among these patients identified by ≥1 developmental-delay proxy diagnosis code (F54/F59/F7x/F8x). Poorly controlled DEEs were further defined by ≥2 distinct ASMs, with ≥1 ASM being new, defined as an ASM claim in the 6 months before the patient first met all other claims-based criteria, with no claim for the same ASM type in the preceding 6 months. For patients identified with poorly controlled DEEs, crude and age-standardized prevalence per 100,000 patients were calculated.
RESULTS: Among 15,372,421 continuously active patients, we identified 158,722 patients who had ≥1 claim with an ICD-10 G40.xx code—consistent with an epilepsy diagnosis. Of these patients, 22,143 (14.0%) had ≥1 claim with an F diagnosis code. Among patients with both an ICD-10 G40.xx and F code, 5281 met ASM criteria for poorly controlled DEEs—representing 3.3% of all patients with an epilepsy diagnosis per study definition. Crude and age-standardized prevalences for poorly controlled DEEs were 34.4 and 34.7 per 100,000, respectively.
CONCLUSIONS: These findings help estimate the potential eligible population for ASMs indicated for treatment of seizures in all DEEs. A small proportion of patients with epilepsy met a claims-based definition of poorly controlled DEEs incorporating developmental impairment and ASM treatment intensity.
Conducted by H. Lundbeck A/S (Copenhagen, Denmark).
METHODS: The IQVIA PharMetrics database was analyzed for patients with continuous enrollment from 2023-2024. Epilepsy was identified by ≥1 ICD-10 G40.xx diagnosis, with DEEs among these patients identified by ≥1 developmental-delay proxy diagnosis code (F54/F59/F7x/F8x). Poorly controlled DEEs were further defined by ≥2 distinct ASMs, with ≥1 ASM being new, defined as an ASM claim in the 6 months before the patient first met all other claims-based criteria, with no claim for the same ASM type in the preceding 6 months. For patients identified with poorly controlled DEEs, crude and age-standardized prevalence per 100,000 patients were calculated.
RESULTS: Among 15,372,421 continuously active patients, we identified 158,722 patients who had ≥1 claim with an ICD-10 G40.xx code—consistent with an epilepsy diagnosis. Of these patients, 22,143 (14.0%) had ≥1 claim with an F diagnosis code. Among patients with both an ICD-10 G40.xx and F code, 5281 met ASM criteria for poorly controlled DEEs—representing 3.3% of all patients with an epilepsy diagnosis per study definition. Crude and age-standardized prevalences for poorly controlled DEEs were 34.4 and 34.7 per 100,000, respectively.
CONCLUSIONS: These findings help estimate the potential eligible population for ASMs indicated for treatment of seizures in all DEEs. A small proportion of patients with epilepsy met a claims-based definition of poorly controlled DEEs incorporating developmental impairment and ASM treatment intensity.
Conducted by H. Lundbeck A/S (Copenhagen, Denmark).
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EPH234
Topic
Epidemiology & Public Health, Health Policy & Regulatory, Real World Data & Information Systems
Topic Subcategory
Disease Classification & Coding
Disease
Neurological Disorders