Big data analysis of ASM retention rates and expert ASM algorithm: A comparative study.

ABSTRACT:

Objective

Only 50% of patients with new-onset epilepsy achieve seizure freedom with their first antiseizure medication (ASM). A growing body of data illustrates the complexity of predicting ASM response and tolerability, which is influenced by age, sex, and comorbidities. Randomized data with sufficient resolution for personalized medicine are unlikely to emerge. Two potential facilitators of ASM selection are big data using real-world retention rates or algorithms based on expert opinion. We asked how these methods compare in adult-onset focal epilepsy.

Methods

ASM retention rates were determined by cross-referencing data from comprehensive Swedish registers for 37 643 individuals, with identified comorbidities. Eight fictive cases were created and expert advice was collect

SUBMITTER: Hakansson S 

PROVIDER: S-EPMC9321965 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature