Exploring generic brittleness and the demographic factors for its susceptibility in patients with epilepsy.

PURPOSE: The purpose of this study was to provide an algorithm for generic brittleness and to elucidate the demographic factors that anticipate generic brittleness for patients with epilepsy.

METHODS

This exploratory, observational, and nontherapeutic study was conducted in patients with epilepsy who were routinely followed at the University of Maryland epilepsy outpatient clinic in Baltimore, Maryland. Patients were taking at least one antiepileptic drug (AED) for treatment of epilepsy. Based on patient interview and medical history, 12 demographic factors were collected. Each patient was assessed to be either generic brittle (GB) or not GB. Demographic factors were subjected to binary logistical regression and other statistical tests, to elucidate determinants of GB status.

RESULTS

N = 148 patients completed the study. An algorithm to define whether a patient was GB or not GB was devised. The two elements that defined GB status are as follows: patient opinion about generics and (if needed) whether patients were currently taking brand or generic of their most problematic AED. About 40% of patients were GB. From binary logistical regression, two demographic factors that contributed to patients being GB were whether a patient was currently taking a problem AED and total number of current medications for a patient, with odds ratios of 4.06 (95% confidence interval [CI] from 1.53 to 10.81) and 1.10 (95% CI from 1.003 to 1.21), respectively. Of the patients on a problem AED, 46.9% were GB, while only 18.2% of patients not currently on a problem AED were GB. The total number of current medications ranged from 1 to 22, with mode of four medications. From regression, for each additional medication that a patient took, the odds of being GB increased 1.10-fold. Although patient seizure and adverse event history was not employed to define GB status, being GB was associated with less seizure control and greater adverse events.

CONCLUSIONS

An algorithm for generic brittleness was derived, and about 40% of patients were GB, usually due to prior history of a switch problem. Two demographic factors favored patients being GB: whether the patient was currently taking a problem AED and the total number of current medications.