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Keywords:

  • Outcome;
  • Temporal lobectomy;
  • Levetiracetam;
  • Epilepsy surgery

Summary

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusion
  8. Disclosure
  9. References

Purpose:  To study the prognostic implications of antiepileptic drug (AED) use on seizure freedom following temporal lobe resections for intractable epilepsy.

Methods:  Seizure outcome implications of epilepsy characteristics and AED use were studied in patients who underwent temporal lobectomy patients at the Cleveland Clinic between September 1995 and December 2006. Survival analysis and multivariate regression with Cox proportional hazard modeling were used. Complete seizure freedom was defined as a favorable outcome.

Key Findings:  Records of 312 patients were analyzed (mean ± standard deviation follow-up 3.5 ± 1.7 years). The estimated probability of complete seizure freedom was 69% at 12 months (95% confidence interval [CI] 66–72%), and 48% at 36 months (95% CI 45–52%). The mean number of AEDs used per patient at the time of surgery was 1.78 (range 1–4), dropping to 1.02 at last follow-up (range 0–4). Following multivariate analysis, a lower preoperative seizure frequency and perioperative use of levetiracetam predicted a favorable outcome (risk ratio [RR] 0.62, 95% CI 0.43–0.89, and RR = 0.57, 95% CI 0.39–0.83, respectively), whereas nonspecific pathology (RR 1.71, 95% CI 1.15–2.47) and a higher number of AEDs used at the time of surgery correlated with higher rates of seizure recurrence (whole-model log-rank test p-value < 0.0001). Better outcomes within the levetiracetam group were seen despite a higher proportion of several poor prognostic indicators within this patient group, and started as early as 4 months after surgery, gradually increasing to a 15–20% survival advantage by 5 years. No similar outcome correlations were identified with another AED.

Significance:  AED use may be a potential new modifiable seizure-outcome predictor after temporal lobectomy. This possible prognostic indicator is discussed in light of proposed seizure recurrence mechanisms.

Much is known about clinical and radiologic predictors of seizure freedom following resective surgery for intractable temporal lobe epilepsy (TLE). A unilateral magnetic resonance imaging (MRI) lesion, tumor etiology, absence of secondary generalization, electroencephalography (EEG)/MRI concordance, and extensive resection all predict favorable surgical outcomes (McIntosh et al., 2004; Tonini et al., 2004; Spencer et al., 2005; Jeha et al., 2006). Although helpful in selecting surgical candidates, none of these factors are modifiable. Conversely, only scarce information is available on how antiepileptic drug (AED) use, one of the most modifiable aspects of intractable epilepsy patient care, affects surgical outcome. A recent retrospective study of surgical patients with hippocampal sclerosis showed no advantage to use of any individual class of AEDs regarding postoperative seizure control (Asadi-Pooya et al., 2008); however, previous reports suggested that levetiracetam (LEV) may control recurrent postoperative seizures better than other AEDs (Motamedi et al., 2003; Janszky et al., 2005). These studies were limited by small sample sizes (Asadi-Pooya et al., 2008), variable designs (Janszky et al., 2005), or both (Motamedi et al., 2003).Yet, clarifying any potential effect of AED use on postoperative seizure outcome is of particular interest, as it would introduce a modifiable factor into a complicated equation of epilepsy surgery. The concept that certain medications may favorably affect postsurgical outcomes becomes more relevant given recent evidence about possible neuroprotective effects of multiple AEDs (Yang et al., 2000; Schubert et al., 2005; Yang & Rothman, 2009; Asanuma et al., 2010; Pitkanen & Lukasiuk, 2011).This article examines the hypothesis that potentially neuroprotective or antiepileptogenic AEDs may favorably affect seizure outcomes following temporal lobe resections.

Methods

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusion
  8. Disclosure
  9. References

Patient selection

Following approval from the Cleveland Clinic Institutional Review Board, investigators (A.I. and H.K.) reviewed patients of all ages with intractable TLE who underwent a temporal lobe resection at our center between September 1995 and December 2006. These patients had failed to respond to adequate trials of at least two AEDs and were carefully selected for surgery during a multidisciplinary weekly patient management conference.

One neurosurgeon (W.B.) performed all surgeries, including standard anterior temporal lobectomy (ATL), selective amygdalohippocampectomy (SAH), and tailored cortical temporal lobe resections [described elsewhere (Jehi et al., 2010a)]. Patients with malignant brain tumors or with <1 year of postoperative follow-up were excluded.

Anatomic and functional imaging features were classified into unilateral abnormalities, normal or “other abnormal” category, which included bilateral lesions or unrelated anatomic abnormalities (such as small vessel disease). Disease etiology was determined from imaging and surgical pathology.

AED data collection

The AEDs used at the time of surgery, at seizure recurrence, and at last available follow-up were recorded. The date of start and stop of each AED was determined through chart review. When an AED was started or stopped between two clinic visits, but the exact date of start or stop was not found in the medical record, it was approximated to the halfway point between these two clinic encounters. If the start date of an AED taken at the time of surgery was not available and could not be calculated as above, we approximated it to January 1st of the year when the patient was originally seen in our institution. Overall, these approximations were made for 23% of the dates. For every patient, we determined the number and type of AEDs used perioperatively and postoperatively, whether any AED was used in monotherapy or polytherapy, the treatment duration, and the timing of certain events of interest such as starting or stopping an AED on one hand and seizure recurrence on the other.

Primary outcome

The primary outcome was time to seizure recurrence. Information regarding seizure recurrence was obtained from electronically documented follow-up visits or telephone calls. As per our center’s protocol, follow-up visits occurred at 3 and 6 months and then annually following surgery for seizure-free patients, with more frequent follow-up for patients with recurrent seizures. A favorable outcome was defined as complete seizure freedom after surgery. Triggers of seizure recurrence were classified into AED reduction/discontinuation, physiologic stress such as sleep deprivation or fever, and unprovoked recurrences. The Engel class at last follow-up was recorded.

Statistical methods

Prior to modeling, data were summarized with descriptive statistics. An initial univariate analysis was performed using Wilcoxon rank-sum, chi-square, and Fisher’s exact tests to compare seizure-free patients to those with seizure recurrence, regardless of follow-up time. This allowed identification of potential prognostic indicators. Variables with a significance level of 10% on univariate analysis were tested in a multivariate Cox proportional hazards regression model controlling for year and type of surgery to avoid any confounding effects related to temporal variations in diagnostic and surgical approaches during the study period. Results were then considered statistically significant at the 5% level. Kaplan-Meier survival analysis was first used to calculate the probability of seizure freedom in the overall group, and then by considering each of the significant outcome predictors. For the most commonly used AEDs, survival plots were made to compare seizure freedom between patients using that AED (monotherapy or in combination therapy) with patients not taking it.

Results

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusion
  8. Disclosure
  9. References

Patient characteristics and AEDs used

A total of 312 patients fulfilled our study criteria and were analyzed. Tables 1 and 2 summarize clinical and imaging patient characteristics.

Table 1.   Clinical characteristics of the overall cohort
 Overall group (N = 312)
  1. No., number of patients; GTC, generalized tonic–clonic.

  2. aOthers category included two patients with stroke, eight with a vascular malformation, and one with encephalitis.

Clinical characteristics 
 Male, no. (%)149 (48)
 Left-sided surgery, No. (%)176 (56)
 Mean age at onset, years (range)15.1 (0–57)
 Mean age at surgery, years (range)35.5 (2.5–74)
 Mean epilepsy duration at time of surgery, years (range)20.5 (1–64)
 Preoperative GTC present, no. (%)229 (74)
 Mean preoperative seizure frequency/month (range)22 (0.3–600)
Type of surgery 
 Selective amygdalohippocampectomy (%)7 (2)
 Standard anterior temporal lobectomy (%)289 (92)
 Tailored resection (%)15 (6)
Etiology 
 Hippocampal sclerosis (%)178 (57)
 Tumors (%)43 (14)
 Malformation of cortical development (%)30 (10)
 Gliosis (%)50 (16)
 Othersa (%)11 (10)
Table 2.   Imaging characteristics of the overall cohort
 Overall group (N = 312)Recurred (N = 165)
  1. aThis category includes bilateral as well as unrelated anatomical abnormalities seen on MRI.

  2. PET, positron emission tomography.

MRI (p = 0.098)  
 Normal (%)33 (11)23 (70)
 Abnormal unilateral (%)238 (76)120 (51)
 othera (%)41 (13)22 (54)
PET (p = 0.5)  
 Normal (%)16 (5)9 (56)
 Abnormal (%)231 (76)113 (49)

Our patients were taking a total of 15 different AEDs, with the number of AEDs per patient ranging from 1–4 (mean 1.78, median 2, standard deviation [SD] 0.67) at the time of surgery, and from 04/patient (mean 1.02, median 1, SD 0.85) at last follow-up. Of 312 patients, 107 (34%) discontinued their medications completely by the last follow-up. Figure 1 summarizes the distribution of AED use.

image

Figure 1.   The number of patients taking each AED at the time of surgery and then at last follow-up.

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Overall recurrence

One hundred sixty-five patients had at least one seizure recurrence, but 70 of these regained remission, resulting in a total of 208 patients (69%) who maintained Engel class I at their last follow up, whereas 13% were classified as Engel class II, 14% Engel III, and 4% were Engel IV. Kaplan-Meier survival plot for the entire population estimated a 69% rate of complete seizure freedom at 12 months (95% confidence interval [CI] 66–72%), 59% at 24 months (95% CI 56–62%), and 48% at 36 months (95% CI 45–52%). Most seizure recurrences were unprovoked (45%), followed by breakthrough seizures in the setting of AED withdrawal (39%), physiologic stress (15%), or tumor recurrence in two patients (1%).

Univariate analysis

The main findings of the univariate analysis are shown in Table 3. There was no correlation between the number of AEDs to which the patient failed to respond prior to surgery and seizure outcome, and no AEDs other than phenytoin (PHT) and levetiracetam (LEV) showed any significant correlations with use of univariate analysis (Table 4).

Table 3.   Main variables correlating with postoperative seizure freedom on univariate analysis
 NSeizure- freeRecurredp-Value
  1. Data are No. (%) unless otherwise indicated.

Preoperative GTC    
 Present22998 (43)131 (57)0.02
 Absent7946 (58)33 (42)
Levetiracetam use    
 Used12471 (57)53 (43)0.003
 Not used18876 (40)112 (60)
Phenytoin use    
 Used7326 (36)47 (64)0.02
 Not used239121 (51)118 (49)
Gliosis    
 Present5015 (30)35 (70)0.007
 Absent262132 (50)130 (50)
Mean preoperative seizure frequency/month (range)22 (0.3–600)13 (0.1–32)31 (0.1–600)0.003
Table 4.   Longitudinal rates of seizure freedom (% seizure-free ± survival standard error) in our cohort as related to various AEDs
 4 month (%)12 month (%)24 month (%)36 month (%)60 month (%)
  1. Rates were derived through Kaplan-Meyer survival analyses with p-value for log-rank test reported.

  2. LEV, levetiracetam; CBZ, carbamazepine; LTG, lamotrigine; OXC, oxcarbazepine; PHT, phenytoin; TOP, topiramate.

LEV (p = 0.04)     
 LEV86% (±3)76% (±4)66% (±4)53% (±5)47% (±6)
 No LEV79% (±3)65% (±3)57% (±4)47% (±4)28% (±5)
CBZ (p = 0.41)     
 CBZ82% (±4)74% (±5)67% (±5)55% (±6)28% (±5)
 No CBZ83% (±2)68% (±3)58% (±3)48% (±4)39% (±5)
LTG (p = 0.54)     
 LTG82% (±5)65% (±6)55% (±6)53% (±6)38% (±7)
 No LTG83% (±2)71% (±3)61% (±3)49% (±4)36% (±5)
OXC (p = 0.39)     
 OXC75% (±7)64% (±8)55% (±8)50% (±8)31% (±10)
 No OXC84% (±2)70% (±3)61% (±3)50% (±3)35% (±5)
PHT (p = 0.02)     
 PHT81% (±5)56% (±6)48% (±6)37% (±6)32% (±6)
 No PHT83% (±2)74% (±3)64% (±3)54% (±4)35% (±5)
TOP (p = 0.23)     
 TOP75% (±6)62% (±6)50% (±7)41% (±7)38% (±7)
 No TOP84% (±2)72% (±3)62% (±3)51% (±5)34% (±5 )

In addition, unilateral MRI lesions correlated with improved seizure outcomes, but this did not reach statistical significance (p = 0.1). There was also a trend correlating higher numbers of AEDs used at the time of surgery with higher rates of seizure recurrence (Fig. 2; p = 0.07).

image

Figure 2.   The worsening seizure outcomes with higher numbers of perioperative AEDs. The numbers 1, 2, or 3 on the graph refer to the number of AEDs taken by the patient at the time of surgery.

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Multivariate analysis

Following Cox proportional hazard modeling, four variables remained independently associated with complete seizure freedom, including baseline seizure frequency, number of AEDs at the time of surgery, pathology, and use of LEV (Table 5, Fig. 3).

Table 5.   Variables correlating with complete postoperative seizure freedom after applying multivariate proportional hazard modeling (whole-model log-rank p-test < 0.0001)
VariableRisk ratio95% CIAdjusted p-value
  1. Other variables that were included in the model but lost their significance were generalized tonic–clonic seizure (adjusted p-value = 0.054) and year of surgery (adjusted p-value = 0.61).

Levetiracetam use0.570.39–0.830.004
Gliosis on pathology1.711.15–2.470.009
Preoperative seizure frequency <200.620.43–0.890.012
Number of AEDs at the time of surgery   
 3 vs. 12.361.36–3.950.003
 2 vs. 11.501.05–2.150.024
image

Figure 3.   The survival curves illustrate the effect of three independent outcome predictors identified after multivariate Cox proportional hazard modeling (whole model log-rank p-test < 0.0001).

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By last follow-up, 53 of 124 patients who were taking LEV had recurrent seizures (43%) as opposed to 112 (60%) of 188 patients who were taking other AEDs (p = 0.003). As detailed in Fig. 3 and Table 5, survival analysis accounting for varying follow-up durations, and interaction among different outcome predictors further documented higher rates of seizure freedom with the perioperative use of LEV when compared with other AEDs. This advantage started as early as 4 months (86% seizure-free in patients on LEV as opposed to 79% in patients on other AEDs), with a gap of 10–15% later favoring the LEV group, and persisting until last follow-up (adjusted p-value = 0.003). The negative correlation between PHT use and outcome lost its significance after multivariate analysis. In fact, patients taking PHT had more frequent seizures at baseline (31% of patients on PHT had >20 seizures/month compared to 20% otherwise; p = 0.10), more frequent generalized tonic–clonic seizures (26% if on PHT vs. 16% otherwise; p = 0.08), and were more likely to be receiving polytherapy (mean number of AEDs if taking PHT was 2.00 compared with 1.70 otherwise; p = 0.002). Therefore, the worse outcomes observed in the PHT group were likely a reflection of a sicker patient group, rather than an effect of the medication itself, whereas the observation of better outcomes with LEV persisted despite controlling for potentially confounding variables.

Cox proportional hazard modeling using an Engel class of I (rather than complete seizure freedom) as the favorable outcome definition reproduced the same outcome determinants (log likelihood-ratio test p-value < 0.0001) except for gliosis, which became marginally significant (p-value 0.09).

Characteristics of patients taking LEV as compared with other AEDs

Of the 124 patients in our cohort taking LEV at the time of surgery, 20 (17%) were receiving monotherapy. The mean duration of LEV treatment at the time of resection was 20.1 months (range 1.6–69.8 months). The mean duration of LEV use after surgery was 15.8 months (range 0.6–65 months), with 47 (38%) of 124 discontinuing LEV by last follow-up. Seizures recurred in close to half the patients who stopped LEV (48%) after a median time of a week (maximum 1.3 months). Seizure outcomes were similar whether LEV was used as monotherapy or in combination with other AEDs. There was no correlation between duration of LEV treatment either before or after surgery with seizure outcomes.

We then compared the clinical and imaging characteristics of patients taking LEV to those taking other AEDs, particularly in relation to the independent outcome predictors identified after multivariate regression in our cohort. First, patients taking LEV had higher presurgical seizure frequency: 27% of patients taking LEV had >20 seizures/month, compared with 17% of patients taking other AEDs (p = 0.04). Second, there was no difference between the LEV group and the rest of the cohort regarding generalized tonic–clonic seizure history, pathology, or other classically reported seizure outcome predictors such as epilepsy duration, type of surgery, or imaging findings. In addition, the mean total number of AEDs used at the time of surgery was higher in patients taking LEV (mean 2.1 AEDs in patients taking LEV vs. 1.6 AEDs otherwise; p < 0.0001), and patients taking LEV had failed to respond to more AEDs prior to surgery (mean number of AEDs failed at the time of surgery was 4.8 for LEV group vs. 3.8 for the rest of the cohort, p = 0.0003). Taken together, these findings suggest that the LEV group actually had more negative surgical outcome predictors than the rest of the group, and should have actually had worse seizure outcomes after surgery. Surgeries were more recent in the LEV group (mean year of surgery 2004 for LEV group vs. 2001 for rest of cohort, p < 0.0001), justifying our inclusion of the year and type of surgery in the multivariate analysis model.

Discussion

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusion
  8. Disclosure
  9. References

Overall seizure recurrence

Our cohort’s seizure outcomes fall within the previously reported rates of seizure freedom following temporal lobe resections (Sperling et al., 1996; Foldvary et al., 2000; McIntosh et al., 2001; Salanova et al., 2002; McIntosh et al., 2004; Paglioli et al., 2004; Spencer et al., 2005; Jeha et al., 2006). In addition, as expected with TLE surgery (Fong et al., 2011), a significant proportion of our patients with breakthrough seizures regained seizure control and achieving an Engel I classification by last follow-up. This study also reproduces the traditional outcome predictors identified in prior TLE surgery reports, including higher rates of seizure freedom with unilateral MRI lesions and clear epileptic pathology (Yoon et al., 2003; McIntosh et al., 2004; Tonini et al., 2004; Tellez-Zenteno et al., 2005; Jeha et al., 2006), and worse seizure outcomes in patients with a history of generalized tonic–clonic seizures (Hennessy et al., 2001; McIntosh et al., 2004; Jeong et al., 2005; Spencer et al., 2005; Jeha et al., 2006) or frequent preoperative seizures (Foldvary et al., 2000; Jeha et al., 2006). Patients taking a higher number of AEDs at the time of surgery may have a more “severe” or “refractory” epilepsy, less amenable to a surgical cure. All these confirmatory findings do not augment the current literature, but emphasize that our cohort is indeed representative of a “typical” TLE surgery population.

Levetiracetam use

Our main and novel finding is the improvement in seizure freedom following TLE surgery with the perioperative use of LEV. This favorable effect was unique to LEV in our cohort, similar whether LEV was used in monotherapy or polytherapy, and was in fact observed despite a higher proportion of several poor outcome determinants in the LEV cohort. The robust favorable LEV effect (adjusted p-value = 0.003) persisted after multivariate analysis controlling for currently known clinical and radiologic outcome predictors, prior and concomitant AED use, and year and type of resection suggesting that it is difficult to attribute it to improved diagnostic or surgical methods used in the LEV cohort. In fact, we evaluated the available data as best as possible within the limitations of a retrospective cohort to look for and adjust for possible confounders. As such, the possibility of a true physiologic basis for improved seizure outcomes with LEV deserves careful consideration.

One hypothesis might be that LEV is a better “antiepileptic” medication in postsurgical patients. In fact, one report has already suggested better control of recurrent postoperative seizures using LEV (Janszky et al., 2005). Although such an assumption is plausible, it would be difficult to speculate how surgery will selectively convert the LEV group in our intractable TLE cohort to pharmacoresponsiveness. Furthermore, although all AEDs were equally effective soon after surgery, with 75–86% of our patients being seizure free at four postoperative months (Table 4), the seizure freedom advantage for patients taking increased over time to reach up to a 20% difference for example compared with the carbamazepine (CBZ) group at 60 months. Discontinuation rates of the various AEDs were similar in our cohort (Fig. 1), so it is reasonable to speculate that adherence to AED treatment was also similar across groups. As such, a growing gap in the rates of seizure freedom for patients taking LEV introduces a postoperative time-dependency element to the LEV effect, which is difficult to explain through “anticonvulsant” properties alone.

An alternative hypothesis is that better seizure outcomes with LEV use might be related to an “antiepileptogenic” effect. Assuming that surgery removed the current focus of intractable epilepsy, improved effectiveness of LEV in the same patient population suggests that LEV may be acting mainly as an “antiepileptogenic” medication after surgery as opposed to its more typical “antiepileptic” role before the resection. A recent study of rats with genetic predisposition to epilepsy showed that LEV treatment starting prior to epilepsy onset decreased subsequent seizure frequency and duration (Yan et al., 2005). Proposed mechanisms of this antiepileptogenic effect in animals range from inhibition of interleukin-1β inflammatory markers in the hippocampus and piriform cortex or transforming growth factor β in astroglia, to modulation of presynaptic P/Q-type voltage-dependent calcium channels in granule cells of dentate gyrus (Lee et al., 2009; Kim et al., 2010; Stienen et al., 2011). Human brain tissue studies have also shown alteration of synaptic vesicle release within neurons and stabilization of epileptic γ-aminobutyric acid (GABA)A receptors (Palma et al., 2007; Yang & Rothman, 2009). However, direct evidence translating these experimental data into clear beneficial clinical effects has been lacking. One study found that adjunctive therapy with LEV is more effective when used early in patients who failed to respond to TLE surgery, than in refractory patients who had no prior surgery (Motamedi et al., 2003), but a subsequent retrospective analysis of temporal lobectomy patients did not show any superiority of potentially neuroprotective AEDs when compared with PHT or CBZ in preventing postoperative seizure recurrence (Asadi-Pooya et al., 2008). However, the study by AsadiPooya et al. was underpowered as it included a smaller group of patients taking “neuroprotective” AEDs (a total of 53 patients taking LEV, TOP, ZNS, and TGB combined), whereas our study includes 124 patients taking LEV alone. By the same token, smaller numbers of patients in our cohort taking the remaining potentially neuroprotective drugs (topiramate [TOP], zonisamide [ZNS], tiagabine [TGB]) may account for the lack of any favorable effects.

An underlying concept behind attributing better seizure outcomes to an antiepileptogenic effect of any medication though is the assumption that postoperative seizure recurrence is at least partly due to epileptogenesis. Our previous work on longitudinal postoperative seizure outcome supports this notion. Following resective surgery for temporal (Jeha et al., 2006), frontal (Jeha et al., 2007), or posterior quadrant (Jehi et al., 2009) intractable epilepsy, 50–80% of all seizure recurrence occurs within the first two to six postoperative months, followed by a much slower 3–5% subsequent yearly decrease in seizure-freedom rates. This variation in the rate of seizure recurrence likely reflects shifts in the mechanisms of recurrence. In fact, whenever the predictors of these two phases of recurrence (early vs. late) were analyzed independently for TLE surgery (Jeha et al., 2006), the strongest predictors of early recurrence were markers of an inaccurate localization of the epileptogenic zone or its incomplete resection such as residual spiking on postoperative EEG, bitemporal MRI abnormalities, and the need to use invasive EEG recordings. In contrast, late seizure recurrences were highest in patients whose pathology was restricted to nonspecific gliosis (Jeha et al., 2006). Furthermore, when compared with early surgical failures, those later recurrences manifested with less frequent seizures (Jeha et al., 2006, 2007) that were more readily controlled with medical therapy alone (McIntosh et al., 2005; Jehi et al., 2010a,b), behaving then more like a “new onset epilepsy” rather than a persistent focus of intractable seizures that was incompletely resected. This suggests that the mechanism of late recurrence may extend to include the maturational process of epileptogenesis required for seizures to develop again years after an initial period of postoperative seizure freedom. Within this framework, our current finding that a potentially antiepileptogenic medication may improve seizure outcomes, particularly late after surgery, is not surprising.

Limitations

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusion
  8. Disclosure
  9. References

There are several limitations to our study, mainly its retrospective uncontrolled design, which invariably raises concerns about the validity of the findings. Our large sample size and our use of multivariate modeling reduce that risk, but do not eliminate it.

Albeit obtained from intensive follow-up information, start and stop dates of AEDs required some approximation. In addition, our sample included multiple patients who were receiving polytherapy, allowing for speculation regarding potential synergistic effects between various AED combinations. Given all these limitations, our results will need to be reproduced, and validated through adequately designed prospective studies before clearly defining their significance.

Conclusion

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusion
  8. Disclosure
  9. References

In addition to traditional nonmodifiable seizure outcome predictors, our study provides preliminary data suggesting a potential benefit for a modifiable variable: the type of AED treatment. Carefully designed prospective trials are needed to confirm this finding in patients who are undergoing temporal and extratemporal resections, and to explore its full implications on patient management. If confirmed in the future, this finding will open the door to “antiepileptogenic” interventions that can actually alter a patient’s course after surgery rather than simply predict it.

Disclosure

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusion
  8. Disclosure
  9. References

None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

References

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusion
  8. Disclosure
  9. References