4.7 Article

Web-based decision support system for patient-tailored selection of antiseizure medication in adolescents and adults: An external validation study

Journal

EUROPEAN JOURNAL OF NEUROLOGY
Volume 29, Issue 2, Pages 382-389

Publisher

WILEY
DOI: 10.1111/ene.15168

Keywords

adolescent; adult; adverse effects; antiepileptic drugs; epilepsy; neuropharmacology

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The study validated that the use of the algorithm recommending ASMs based on individual characteristics is associated with better outcomes compared to using less desirable ASMs, including higher retention rates, higher seizure freedom rates, and fewer discontinuations due to adverse effects. The freely available decision support system proved to be beneficial for healthcare professionals in prescribing medication for individuals with epilepsy.
Background and purpose Antiseizure medications (ASMs) should be tailored to individual characteristics, including seizure type, age, sex, comorbidities, comedications, drug allergies, and childbearing potential. We previously developed a web-based algorithm for patient-tailored ASM selection to assist health care professionals in prescribing medication using a decision support application (). In this validation study, we used an independent dataset to assess whether ASMs recommended by the algorithm are associated with better outcomes than ASMs considered less desirable by the algorithm. Methods Four hundred twenty-five consecutive patients with newly diagnosed epilepsy were followed for at least 1 year after starting an ASM chosen by their physician. Patient characteristics were fed into the algorithm, blinded to the physician's ASM choices and outcome. The algorithm recommended ASMs, ranked in hierarchical groups, with Group 1 ASMs labeled as the best option for that patient. We evaluated retention rates, seizure freedom rates, and adverse effects leading to treatment discontinuation. Survival analysis contrasted outcomes between patients who received favored drugs and those who received lower ranked drugs. Propensity score matching corrected for possible imbalances between the groups. Results Antiseizure medications classified by the algorithm as best options had a higher retention rate (79.4% vs. 67.2%, p = 0.005), higher seizure freedom rate (76.0% vs. 61.6%, p = 0.002), and lower rate of discontinuation due to adverse effects (12.0% vs. 29.2%, p < 0.001) than ASMs ranked as less desirable by the algorithm. Conclusions Use of the freely available decision support system is associated with improved outcomes. This drug selection application can provide valuable assistance to health care professionals prescribing medication for individuals with epilepsy.

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