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

Antiseizure medications (ASMs) should be tailored to individual characteristics, including seizure type, age, sex, comorbidities, co-medications, drug allergies, and child-bearing potential. We previously developed a web-based algorithm for patient-tailored ASM selection to assist healthcare professionals in prescribing medication using a decision support application (https://epipick.org). 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. Four hundred and twenty-five consecutive patients with newly diagnosed epilepsy were followed for at least one 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 labelled as 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. ASMs classified by the algorithm as best options had 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 less desirable by the algorithm. Use of the freely available decision-support system is associated with improved outcomes. This drug-selection application can provide valuable assistance to healthcare professionals prescribing medication for individuals with epilepsy.