Recurrence of status epilepticus: Prognostic role and outcome predictors.

OBJECTIVE: Predictors of morbidity and mortality after status epilepticus (SE) have been studied extensively in hospital- and population-based cohorts. However, little attention has been directed toward SE recurrence after an incident episode. We investigated clinical and demographic characteristics of patients presenting SE recurrence and its specific prognostic role. METHODS: In this observational cohort study, we screened our prospective registry of consecutive adults with SE between April 2006 and February 2014. Demographic and clinical data were compared between incident and recurrent SE episodes; risk of SE recurrence was assessed through survival analysis, and the prognostic role of SE recurrence with multivariable logistic regressions. RESULTS: Of the incident cohort (509 patients), 68 (13%) experienced recurrent SE. The cumulative recurrence rate over 4 years was 32%. Recurrence risk was significantly reduced after an acute SE etiology (hazard ratio [HR] 0.5, 95% confidence interval [CI] 0.31-0.82; p = 0.005), and was borderline increased in women (HR 1.59, 95% CI 0.97-2.65; p = 0.06). Although recurrent SE episodes showed lower morbidity and mortality, prognosis was independently related to Status Epilepticus Severity Score (STESS) and potentially fatal etiology, but not to SE recurrence. SIGNIFICANCE: This study provides class III evidence that SE recurrence involves a significant proportion of patients, and that recurrence risk is independently associated with chronic etiology and to a lesser extent with female gender. However, contrary to underlying cause and SE severity, SE recurrence per se does not independently correlate with outcome. Early identification of patients at higher risk of SE recurrence may influence their management during follow-up.

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status.

The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.