Faculty Bibliography

Rationale: Resective surgical treatment can be curative in a large subset of patients with treatment resistant epilepsy. Despite the potential for seizure freedom following surgery, many patients do not progress to epilepsy surgery. It is presumed that the reasons for this are multifactorial and often stem from poor prognostic factors within the presurgical workup. This study was designed to explore potential barriers (both medical and social) to resective epilepsy surgery in a population of patients with a high likelihood of seizure freedom based upon initial MRI, EEG, and semiology data. Methods: Chart review of patients admitted to the New York University Langone Medical Center epilepsy monitoring unit from 1/1/2007 to 7/31/2008 identified 1,105 unique patients. Of these, 455 met inclusion criteria: age >=18, focal epilepsy diagnosis>=2 years, failed >=1 medication, and >=1 seizure three months prior to admission. Utilizing the Epilepsy Surgery Grading Scale (ESGS; Table 1), a score was calculated from MRI, EEG, semiology, and IQ data. Patients with scores categorizing them as Grade 1 (best likelihood of seizure freedom) were included for analysis. Patients with follow-up periods less than 6 months and those with previous resective surgeries were excluded (32 patients). Outcomes were assessed based upon last available follow-up up through June 1, 2011. Patients were classified as either seizure free or not seizure free. For patients not undergoing surgery, medical and surgical outpatient notes were reviewed to ascertain the reason(s) for not pursuing surgery. Results: Of the 423 patients, a total of 110 were Grade 1. Of all Grade 1 patients, 43 (39.1%) underwent resective epilepsy surgery. Two patients had less than one year of follow-up; 35/41 (85.4%) were seizure free. An additional 11 (10%) patients underwent intracranial EEG monitoring without resection. Of the 56 (50.9%) patients that did not undergo invasive monitoring or resective surgery within the period of follow-up, 15 (26.8%) were reported as seizure free at the time of last follow-up. For the remaining patients, multiple reasons were identified for not pursuing surgery. These findings are presented in Table 2. In brief, 2% are presently awaiting surgery, 21% the patient declined surgery, 7% reported adequate seizure control and declined surgery, 16% had no identifiable reason (unknown), 25% were lost to follow up, and 2% had insurance denials precluding surgery. Conclusions: These results indicate that multiple factors can contribute to patients failing to pursue epilepsy surgery, with over 1/2 of patients declining surgery due to seizure freedom, "adequate" seizure control or no desire to further pursue surgery despite continued seizures. In addition, 25% of patients were lost to follow-up, which does not preclude them having had resective surgery at another institution

Rationale: Resective surgical treatment can be curative in a large subset of patients with treatment resistant epilepsy. There is a need for a simple surgical grading scale that can be used by the referring neurologist using information obtained prior to diagnostic hospitalization. Such a tool would provide a simple, systematic method for identifying a patient's likelihood of positive outcome following surgical treatment and would offer a uniform means to improve epidemiology and tracking. Our hypothesis was that a model using interictal EEG, brain MRI, seizure semiology and IQ could stratify patients with treatment resistant epilepsy based upon their likelihood of achieving seizure freedom following assessment for resective epilepsy surgery. Methods: Chart review of patients admitted to the New York University Langone Medical Center epilepsy monitoring unit from 1/1/2007 to 7/31/2008 identified 1,105 unique patients. Of these, 455 met inclusion criteria: age >=18, focal epilepsy diagnosis >=2 years, failed >=1 medication, and >=1 seizure three months prior to admission. Calculation of the Epilepsy Surgery Grading Scale (ESGS) score was based upon MRI, EEG, semiology, IQ (Table 1). Patients with follow-up periods <6 months and those with prior resective surgeries were excluded (32 patients). Outcomes were assessed at the study's conclusion (3/31/2010); patients were classified as either seizure free following resective surgery or not seizure free following surgery/no resection. Three cohorts were used in this study: 1) the full cohort, 2) only patients undergoing surgical multidisciplinary case (MDC) conference evaluation, 3) only patients who underwent resective surgery. Results: Our data demonstrate that of 423 patients initially identified as presurgical admissions to the EMU, only 193 (45.6%) were ultimately considered for surgical management and presented in surgical MDC. Eighty-four (19.9%) then underwent resective surgery. Analysis of the MDC cohort reveals that 53.2% of ESGS Grade 1 patients, 34.1% of Grade 2 patients, and 17.2 % of Grade 3 patients became seizure free from resective surgery. For this cohort, significant differences between Grades 1 and 3 (p=0.0001), and between Grades 2 and 3 (p=0.0463) were seen, and a trend was seen between Grades 1 and 2 (p=0.0743). Analysis of the resection only cohort showed that 89.2% of ESGS Grade 1 patients, 83.3% of Grade 2 patients, and 44.8% of Grade 3 patients became seizure free from resective surgery (Table 2). Significant differences between Grades 1 and 3 (p=0.0009), and between Grades 2 and 3 (p=0.0343) were seen; the difference between Grades 1 and 2 was not statistically significant (p=0.6713). Conclusions: These results indicate that, using basic information obtainable in a doctor's office, patients with treatment resistant epilepsy may be stratified into clinically meaningful groups based upon their likelihood of achieving seizure freedom as a result of resective surgery

Rationale: Resective surgical treatment can be curative in a large subset of patients with treatment resistant epilepsy. There is a need for a simple surgical grading tool which can be employed by the referring neurologist, ideally utilizing information obtained prior to diagnostic hospitalization. Our hypothesis was that a model using interictal EEG, brain MRI, seizure semiology and IQ could stratify patients with treatment resistant epilepsy with respect to their likelihood of achieving seizure freedom following assessment for resective epilepsy surgery. Methods: A prospectively identified cohort of 211 patients from the University of Alabama was combined with a retrospectively identified cohort of 193 consecutive patients at New York University presented in surgical multidisciplinary conference and either proceeded to surgery or were excluded as surgical candidates. All met inclusion criteria: age e18, focal epilepsy diagnosis e2 years, failed e1 medication, e1 seizure 3 months prior to admission, follow-up>6 months. Patients were classified as seizure free following resective surgery or not seizure free following resective surgery/no surgery. Pre-operative EEG, MRI, seizure semiology and IQ data were reviewed, systematically categorized (Table 1) and were utilized in a decision tree algorithm to predict seizure freedom. When p<0.05 was utilized, a simplistic dichotomous algorithm resulted. Therefore, to further explore, a relaxed, exploratory statistical significance level of p<0.25 was used. Nodes resulting in >50% of patients becoming seizure free were considered predictive of seizure freedom. Results: The overall seizure freedom rate was 46.8%. The exploratory decision tree analysis (Figure 1) resulted in two EEG groups: F, G, H (bilateral temporal, bilateral extra-temporal, bisynchronous; node 2; N=97) versus all others (node 3; N=307). For node 3, MRI was employed for further stratification: b (unilateral mesial temporal sclerosis (MTS); node 4; N=75) versus all others (node 7; N=232). Node 4 was further stratified based upon IQ: below 70 (node 5; N=11), above 70 (node 6; N=64). Semiology had no statistically significant impact. The model correctly predicts outcome in 62% of patients, yielding a positive predictive value of 55%, and a negative predictive value of 71%, with sensitivity of 74% and specificity of 51%. Conclusions: The relatively low overall seizure freedom rate is due to the fact that patients considered for, but ultimately not undergoing, surgery were included in the analysis, which better reflects the actual decision process for patients and neurologists. Of interest, the model fails to identify the commonly considered "best surgical" group of unilateral MTS with concordant interictal activity as a unique node. Notably, the main predictive factor was interictal EEG; other factors were only statistically viable with a more exploratory statistical approach. The positive and negative predictive values in this model are probably not sufficient for clinical use