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.
