Clinical and EEG factors can help identify anti-seizure medication resistance


By Natasha Doyle

2 Nov 2021

A combination of clinical and EEG factors could help identify anti-seizure medication (ASM) resistant and receptive idiopathic generalised epilepsy (IGE) patients, leading to improved prognostic insights and personalised treatments, Australian neurologists say.

It comes after a study of 232 IGE patients showed catamenial epilepsy, certain seizure-type combinations, generalised spike-wave (GSW) discharges in sleep and the presence of generalised polyspike trains (GPTs) helped clinicians distinguish between resistant and receptive patients with 80% accuracy.

Individually, catamenial epilepsy patients were 3.5 times more likely to be resistant to ASMs while those with absence, myoclonic, and generalised tonic-clonic seizures or absence and generalised tonic-clonic seizures were 7.06 and 4.45 times more likely to be resistant, respectively.

EEG-captured GSWs in sleep (frequent and abundant) and GPTs were also associated with resistance, (odds ratios: 3.4, 7.2 and 5.5 respectively).

The combination of clinical and EEG factors is more accurate than clinical variables alone and could support earlier diagnosis, “improve understanding of a patient’s prognosis”, and lead to “better treatment options for patients with ASM-resistant IGE”, study author and Alfred Hospital neurologist Dr Mubeen Janmohamed and his team wrote in Epilepsia.

“This [model’s level of accuracy] represents an improvement of around 7% from our previously published model, suggesting that the addition of EEG variables improves the model’s performance,” they wrote.

Earlier studies demonstrated a 3.5–4 fold increased chance of resistance in patients with catamenial epilepsy, though the relationship between ASM response and the menstrual cycle is poorly understood.

“Herzog et al. showed that cyclic progesterone therapy improved focal seizures in patients with peri-menstrual, but not peri-ovulatory or luteal phase, exacerbations, possibly due to fluctuations of progesterone and other hormone levels during the menstrual cycle,” Dr Janmohamed and colleagues wrote, although their study couldn’t shed any more light on the mechanism.

The combination of seizure types more accurately predicted resistance than IGE syndrome or age of onset, likely due to challenges around “correct” syndrome classification, particularly in childhood absence epilepsy evolving to juvenile myoclonic epilepsy and the transition from paediatric to adult epilepsy care, the authors noted.

“A better understanding of this relationship requires a detailed characterisation of seizure types and their dates of onset,” they wrote.

EEG factors have already been linked to IGE prognosis, with a recent study of 24 hour ambulatory EEGs showing “higher densities and longer paroxysms of generalised epileptiform discharges correlated with a shorter preceding duration of seizure freedom”.

Despite GSW in sleep and GPTs independently predicting resistance, GSW frequency should not be used in isolation as nearly 8% of ASM-responsive patients had frequent-to-abundant discharges in sleep and 16% of resistant cases had no discharges, the authors warned.

“By comparison, GPT was observed in only 21.2% of cases but was highly associated with ASM resistance.”

For better insight into a patient’s prognosis and treatment options “clinicians could consider asking about specific seizure-type combinations and track whether they experience catamenial epilepsy,” the authors suggested.

“Obtaining prolonged EEG studies to record the burden of GSWs in sleep and assessing for the presence of GPTs may provide additional predictive value.”

“Patients ‘want to know more’ [about their disease] and will benefit from meaningful prognostic information that we can provide for this difficult condition”, they concluded.

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