Identifying patients who will not reachieve remission after breakthrough seizures

Treatment Outcome and Risk Factors of Adult Newly Diagnosed Epilepsy: A Prospective Hospital-Based Study in Northeast China

Objective: The study was conducted to summarize the treatment outcomes of newly diagnosed epilepsy (NDE) and analyse the risk factors for refractory epilepsy (RE) in Northeast China.

Methods: A total of 466 adult patients with NDE were consecutively enrolled in this programme. Clinical data were collected at baseline and each follow-up. Several scales concerning recognition and mood were also completed at the first visit.

Results: Seizure-free status was achieved by 52% (n = 244) of the patients; however, 15% (n = 68) manifested RE. A total of 286 (61%) patients continued with the first ASM as monotherapy, among which 186 (40%) patients became seizure-free. Fifteen (22%) patients with RE became seizure-free following ASM adjustment and 34 patients (14%) had breakthrough seizures after being classified as seizure-free. One patient developed RE after attaining seizure-free status. Breakthrough seizures during the first expected interictal interval [Odds ratio (OR) = 5.81, 95% CI: 2.70–12.50], high seizure frequency at baseline (OR = 1.24, 95% CI: 1.04–1.49), younger age of onset (OR = 1.42, 95% CI: 1.12–1.79), and male sex (OR = 2.64, 95% CI: 1.26–5.53) were risk factors for RE.

Significance: Treatment outcomes of the majority of NDE cases are good. New risk factors could help physicians more promptly and accurately identify patients who are likely to develop RE. Seizure-free state is not long enough to commence the withdrawal of ASMs. RE is not permanent and seizure-free may be achieved subsequently by appropriate drug adjustment.

Course and prognosis of adult-onset epilepsy in Brazil: A cohort study

BACKGROUND

Most of the epilepsy longitudinal studies have analyzed children. However, in endemic regions, such as Brazil, neurocysticercosis accounts for many adult-onset epilepsy cases. So, the main objective of this study was to identify the clinical predictors associated with drug-resistant adult-onset epilepsy in Brazil during a long-term follow-up.

METHODS

We followed 302 individuals with adult-onset epilepsy for 9.8 years in our University Hospital. Structured questionnaires about drug-resistant epilepsy were applied. The presence of drug-resistant epilepsy was the primary outcome. We used multilevel linear modeling in our data analysis.

RESULTS

Overall 47 (15.6%) individuals presented drug-resistant epilepsy and the etiology was structural in 70.2% of them, while infectious etiology was present in 8.5% of this group. Infectious etiology occurred in 25.9% (n = 66) of the patients from the nondrug-resistant group. Those with developmental delay were two times more likely to present seizures. Structural epilepsy etiology was associated with an increased chance of relapsing. Poor school performance and abnormal electroencephalogram were also associated with an increased chance of seizures.

CONCLUSION

The course of epilepsy was favorable in the majority of our patients, and drug-resistant epilepsy rates were similar to those found in other studies, although we evaluated older individuals with higher levels of infectious etiology. Also, we found that neurocysticercosis was associated with well-controlled epilepsy, while structural epilepsy was directly related to the occurrence of seizures. We also hypothesized that the smaller size of lesions found in neurocysticercosis could contribute to better treatment response.

Identifying patients who will not reachieve remission after breakthrough seizures

Objective

We aim to identify people with epilepsy who are unlikely to reachieve a 12‐month remission within 2 years after experiencing a breakthrough seizure following an initial 12‐month remission.

Methods

We apply a novel longitudinal discriminant approach to data from the Standard and New Antiepileptic Drugs study to dynamically predict the risk of a patient not achieving a second remission after a breakthrough seizure by combining both baseline covariates (collected at the time of breakthrough seizure) and follow‐up data.

Results

The model classifies 83% of patients. Of these, 73% of patients (95% confidence interval [CI] = 58%‐88%) who did not achieve a second remission were correctly identified (sensitivity), and 84% of patients (95% CI = 69%‐96%) who achieved a second remission were correctly identified (specificity). The area under the curve from our model was 87% (95% CI = 80%‐94%). Patients who did not achieve a second remission were correctly identified on average after 10 months of observation postbreakthrough. Occurrence of seizures after breakthrough and the number of seizures experienced were the most informative longitudinal variables. These longitudinal profiles were influenced by the following baseline covariates: age at breakthrough seizure, presence of neurological insult, and number of antiepileptic drugs required to achieve first remission.

Significance

Using longitudinal data gathered during patient follow‐up allows more accurate predictions than using baseline covariates in a standard Cox model. The model developed in this paper is a useful first step in developing a tool for identifying patients who develop drug resistance after an initial remission.