Adverse antiepileptic drug effects: toward a clinically and neurobiologically relevant taxonomy

Abstract

Background: Adverse effects (AEs) of antiepileptic drugs (AEDs) are a major impediment to optimal dosing for seizure control. Better understanding of clinical properties of AEs is a prerequisite for systematic research of their neurobiological underpinnings. This study aimed to define specific patterns of AE occurrence and determine their clinical relevance based on their association with subjective health status.

Methods: Two hundred subjects with epilepsy completed validated self-report health assessments, including the Adverse Event Profile (AEP) and Quality of Life in Epilepsy Inventory (QOLIE)-89. Factor analysis was performed on the 19 AEP items to identify distinct classes of AEs. Correlations between AE class scores and QOLIE-89 scores were evaluated. Multivariate analysis was used to assess contributions of AE class scores to QOLIE-89 scores after controlling for depression and seizure frequency. Relationships between changes in AE class scores and changes in QOLIE-89 scores were also investigated in a subgroup of 62 subjects enrolled in a randomized trial.

Results: The mean number of AEs per subject was 6.5. AEs were segregated into five classes: Cognition/Coordination, Mood/Emotion, Sleep, Weight/Cephalgia, and Tegument/Mucosa. Higher scores in each AE class were associated with lower QOLIE-89 scores. Cognition/Coordination scores were the strongest predictor of QOLIE-89 scores. Improvements in Cognition/Coordination, Mood/Emotion, and Tegument/Mucosa scores were associated with improvements in QOLIE-89 scores. Improved Cognition/Coordination was the only predictor of improved QOLIE-89.

Conclusion: Adverse effects (AEs) of antiepileptic drugs can be classified in five biologically plausible factors. When specific classes of AEs are identified and attempts are made to reduce them, quality of life is significantly improved.

Figure 1 Distribution of frequency of occurrence of each of the 19 adverse effects listed in the Adverse Event Profile questionnaire

Figure 2 Correlations among the 19 Adverse Event Profile items in the entire cohort The strength of correlation is indicated with a scale of gray (right bar), from white (r = 0.05) to black (r = 0.63, highest correlation). The diagonal running from the upper left to the lower right is intentionally left blank. All correlations are significant, except for those between weight gain and hair loss (p = 0.09), weight gain and trouble with mouth or gums (p = 0.27), and memory problems and problems with skin (p = 0.09).

Figure 3 Radial plot illustrating the strength of segregation of individual adverse effects within each class as identified by factor analysis in the entire cohort In this plot, the 19 spokes that radiate from a central point represent the 19 items of the Adverse Event Profile (AEP) questionnaire. Each item loadings for the five classes identified by factor analysis are plotted on a single spoke, with higher loadings indicating a higher level of segregation. The 19 items loadings on a given class are connected with a line to form a polygon. The highest loading on each spoke (and therefore the most distant intersection between each spoke and the five lines) illustrates to which class the corresponding AEP item is segregated.