Of the patients with drug-resistant epilepsy in the cohort, 54% had status epilepticus during their acute admission, and 2 of 3 patients with NORSE ended up developing drug-resistant epilepsy at 12 months.
In a new retrospective analysis, drug-resistant epilepsy (DRE) was found to be uncommon in patients with autoimmune encephalitis (AE) at 12-month follow-up, but was associated with several risk factors, including the presence of status epilepticus (SE) during acute admission and multiple biomarkers of neuronal dysfunction on electroencephalography (EEG).1
The first objective of the study, identifying the prevalence of DRE, was observed in 16% (n = 11) of the 69-patient cohort who were retrospectively followed up at 12 months. Using EEG data gathered at admission, investigators found the presence of SE (odds ratio [OR], 11.50; 95% CI, 2.81-51.86; P <.001), temporal lobe focality (OR, 9.90; 95% CI, 2.60-50.71; P = .001) and periodic discharges (OR, 19.12; 95% CI, 3.79-191.10; P = .001) were associated with the development of DRE.
Lead investigator Robb Wesselingh, MBBS, neuroimmunologist, Monash University, and colleagues concluded that the "identified biomarkers provide the basis to generate a clinically applicable prediction tool which could be used to inform treatment, prognosis, and patient selection for clinical trials." They also noted that EEG is a noninvasive and accessible tool that can serve as a potentially useful biomarker for disease prognostication.
At 12 months, 33% (n = 23) were seizure-free but still on antiseizure medications (ASMs), 48% (n = 33) were seizure-free while off of ASMs, and 19% (n = 13) had ongoing seizures. SE was reportedly more likely to occur in seronegative patients (63%), while DRE was prevalent across most subtypes aside from LGI-1 (0%).
In addition to SE, clinical variables such as focal seizures (OR, 4.24; 95% CI, 1.7-23.25; P = .04) and new-onset refractory SE at admission (OR, 30.79; 95% CI, 2.28-4379.24; P <.001) were associated with future DRE development. In terms of electrographic variables, focal abnormality (OR, 4.66; 95% CI, 1.19-38.45; P = .045), sharp elements within the abnormality (OR, 8.68; 95% CI, 2.31-43.32; P = .002), an evolving abnormality (OR, 16.68; 95% CI, 4.16-106.87; P <.001), superimposed rhythmic activity (OR, 15.78; 95% CI, 2.28-462.97; P = .02), superimposed spikes (OR, 48.18; 95% CI, 4.16-6701.22; P = .001), high amplitude abnormality (OR, 30.79; 95% CI, 2.28-4379.24; P = .01), and an abnormality with a duration greater than 1 minute (OR, 6.88; 95% CI, 1.87-33.08; P = .005) were all associated with future DRE development.
Associations between EEG biomarkers and DRE development at 12 months were examined using logistic regression modeling and were utilized to create a DRE risk score. After using a backward selection method, the final model included 3 risk factors: temporal focality of EEG abnormality (OR, 63.62; 95% CI, 5.88-3662.86; P <.001), periodic discharges (OR, 13.96; 95% CI, 1.85-196.07; P = .01), and age (OR, 8.93; 95% CI, 1.81-189.14; P = .002).
In the development of the risk score, investigators allocated 0 points to age band 50 years and older, 4 points to age band 31 to 50 years, 8 points to age band 18 to 30 years, 8 points to temporal focality of EGG abnormality, and 5 points for the presence of periodic discharges on EEG. Logistic regression function was used to calculate the probabilities of developing DRE for each point combination from 0 to 21. Probabilities from 0.2% to 18% were classified as low risk, 51% to 61% as moderate risk, and 90% to 99% as high risk.
"Once fully validated, this tool could provide better prognostication of DRE,” Wesselingh et al wrote. "However, it is currently unclear whether alteration in management can alter the clinical course, and therefore how prognostication could change management. Given there is still little known about the pathophysiology of post-encephalitic epilepsy in AIE, it is uncertain whether further antiepileptic therapy or even more aggressive or targeted immunotherapy would provide benefit for prevention of DRE once a patient has been identified as high risk."
They added that, "we believe that our score could be used in routine clinical care as well as informing clinical trials. Patients identified as having a high probability of DRE could, for instance, be randomized to examine the utility of earlier more potent immunosuppressive treatment versus standard care in preventing DRE."