Optimal choice of antiseizure medication: Agreement among experts and validation of a web-based decision support application

Sándor Beniczky, Stefan Rampp, Ali A Asadi-Pooya, Guido Rubboli, Emilio Perucca, Michael R Sperling

Research output: Contribution to journalArticlepeer-review

Abstract

OBJECTIVE: Optimal choice of antiseizure medication (ASM) depends on seizure type, syndrome, age, gender, comorbidities and co-medications. There are no fixed rules on how to weigh these factors; choices are subjective and experience-driven. We investigated agreement among experts in selecting ASM as monotherapy and used their prevailing choices to validate a web-based decision-support application.

METHODS: Twenty-four international experts, blinded to the app, selected the optimal ASM for 25 individual patient-cases covering a wide variation of seizure types and other factors influencing ASM selection. The app ranked ASMs in order of likely appropriateness for each case. In a second step, experts rated anonymously the choices of the app.

RESULTS: Of the 25 patient-cases (age 13-74 years), 13 were female, 18 (72%) had comorbidities, six (24%) were on contraceptives, and 13 (52%) had other co-medications. The median number of experts who selected the same ASM for a given case was 15 (62.5%) and interquartile range (IQR) 13-18 (54%-75%). Gwet's agreement coefficient among experts was 0.38 (95% confidence interval [CI] 0.32-0.44), corresponding to a "fair" agreement. Agreement between the app and the prevailing expert choice for each case was 0.48 (95% CI 0.29-0.67), corresponding to a "moderate" beyond chance agreement. The percent agreement between the highest ranked selections of the app and the expert selections was 73% (95% CI 64%-82%). Ninety-five percent of the experts considered that no incorrect or potentially harmful ASMs were ranked highest by the app, and most experts strongly agreed with the app's selections.

SIGNIFICANCE: This app, now validated by experts, provides an objective, reproducible method for selecting ASM that accounts for relevant clinical features. It is freely available at: https://epipick.org.

Original languageEnglish
JournalEpilepsia
DOIs
Publication statusE-pub ahead of print - Dec 6 2020

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