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Review

Identification of common predictors of surgical outcomes for epilepsy surgery

, , , , , , & show all
Pages 1673-1682 | Published online: 06 Nov 2013

Abstract

Although epilepsy surgery is an effective treatment for patients with drug-resistant epilepsy, surgical outcomes vary across patient groups and studies. Identification of reliable prognostic factors for surgical outcome is important for outcome research. In this study, recent systematic reviews and meta-analyses on prediction of seizure outcome have been analyzed, and common predictors of seizure outcome or unrelated factors for temporal lobe epilepsy (TLE), lesional extratemporal lobe epilepsy (ETLE), and tuberous sclerosis complex have been identified. Clinical factors such as lesional epilepsy, abnormal magnetic resonance imaging, partial seizures, and complete resection were found to be common positive predictors, and factors such as nonlesional epilepsy, poorly defined and localized epileptic focus, generalized seizures, and incomplete resection are common negative predictors, while factors such as age at surgery and side of surgery are unrelated to seizure outcome for TLE and lesional ETLE. In addition, diagnostic neuroimaging and resection are among the most important predictors of seizure outcome. However, common predictors of seizure outcome could not be identified in nonlesional ETLE because no predictors were found to be significant in adult patients (by meta-analysis), and outcome prediction is difficult in this case. Meta-analysis of other outcomes, such as neuropsychologic outcomes, is rare due to lack of evaluation standards. Further studies on identification of reliable predictors of surgical outcomes are needed.

Introduction

Around one third of patients with focal seizures are resistant to antiepileptic drugs. For these patients, epilepsy surgery brings the hope of a seizure-free outcome and improved quality of life. Epilepsy surgery can achieve a 60%–90% likelihood of seizure-free outcome in patients with temporal lobe epilepsy (TLE) and 40%–60% in extratemporal lobe epilepsy (ETLE).Citation1 However, there are still uncertainties in surgical candidates, and it is important to estimate possible risks, identify factors related or unrelated to outcomes, and predict postoperative outcomes prior to surgery.

The predictive value of neuroimaging for epilepsy surgical outcome has been reported by a number of studies. For example, Lerner et al,Citation2 Cossu et al,Citation3 Widdess-Walsh et al,Citation4 and Jeha et alCitation5 have shown that complete resection of the abnormality detected by preoperative magnetic resonance imaging (MRI) is the most important predictor of a favorable postoperative outcome. Functional neuroimaging modalities, such as magnetoencephalography (MEG)/magnetic source imaging (MSI), positron emission tomography (PET), and ictal single-photon emission computed tomography (SPECT) also have clinical value in predicting seizure-free outcome.Citation6 In addition, Kuzniecky et al,Citation7 Eberhardt et al,Citation8 and Stefan et alCitation9 have demonstrated that bilateral magnetic resonance spectroscopy (MRS) metabolite alterations in TLE with hippocampal sclerosis (HS) have a predictive value for surgical outcome.

In addition to neuroimaging, other predictors and risk factors for seizure outcome have also been identified. The presence of radiographic mesial temporal sclerosis (MTS) is considered to be a factor predictive of a favorable seizure outcome after surgical intervention.Citation10 The surgical option of localized frontal resection versus more extensive lobectomy with/without an extrafrontal component has been found to be predictive of outcome after frontal lobectomy,Citation11 while bilateral temporal onset,Citation12 frequent secondary generalized seizures,Citation13,Citation14 and head traumaCitation15 have been identified as poor predictors of seizure control.

In general, reasons for failure of epilepsy surgery are multifactorial,Citation16,Citation17 and outcome predictors are hard to identify, especially in nonlesional TLE or ETLE cases.Citation18Citation20 On the other hand, patients with unilateral radiographic mesial temporal sclerosis are considered to be the “ideal” candidates for epilepsy surgery. Recently, Feis et alCitation21 studied patients with left TLE (n=49, 89.8% or 44/49 with hippocampal sclerosis) who underwent selective amygdalohippocampectomy, and found that surgical outcome could be predicted in males (94% balanced accuracy) and in females (96% balanced accuracy) using presurgical structural MRI.

However, the above study findings triggered the following questions. How applicable is such high-accuracy outcome prediction? In addition to predicting outcome in unilateral lesional TLE, what about outcome prediction in bilateral TLE, nonlesional TLE, or ETLE cases? What is the full and real picture of surgical outcome prediction? Is seizure outcome in general predictable? How are the presurgical findings related to surgical outcomes? Is it possible to use presurgical neuroimaging and/or other factors to predict surgical outcomes? How reliable are the predictors? Since the findings vary among studies, is it possible to identify common predictors based on the findings of systematic reviews and meta-analyses? Further, what is the role of presurgical neuroimaging in predicting seizure outcome? Moreover, in addition to seizure outcome, how good is the prediction of other outcomes? To address the above questions, recent systematic reviews and meta-analyses on epilepsy surgical outcome prediction were reviewed and their findings were analyzed.

Methods

Paper selection and classification

A Medline query was performed via PubMed using the keywords “epilepsy”, “surgical outcome”, and “predictor” for papers published since 2000. The articles were filtered for reviews and meta-analyses. Ten meta-analyses and three comprehensive reviews on seizure outcome prediction were indentified. The articles were classified according to epilepsy substrates as lesional or nonlesional TLE, ETLE, or tuberous sclerosis complex (TSC). In addition, to understand predictors of other outcomes and the role of other factors (such as type of surgery), further Medline queries were undertaken. Four related articles (two reviews and two meta-analyses) on other outcomes and four meta-analyses on surgical options or other interventions were identified.

gives an overview of the literature studied in this paper. The literature was classified as lesional or nonlesional TLE or ETLE subgroups. Lesion in this paper refers to mesial temporal sclerosis or hippocampal sclerosis, gliotic tissue, tumors, and other circumscribed anomalies, including malformations of cortical development and focal cortical dysplasia.Citation22 In addition, tubers in tuberous sclerosis complex were considered to be special lesions, and meta-analyses on outcome prediction in tuberous sclerosis complex were classified as a separate subgroup. Further, given that the majority of epilepsy cases in Tonini et alCitation23 and Téllez-Zenteno et alCitation1 were TLE, these two articles were counted as those addressing seizure outcome in TLE. Moreover, since the majority of epilepsy cases in Téllez-Zenteno et alCitation22 were lesional, this paper was classified into lesional epilepsy subgroups.

Table 1 Overview of literature on predictors of seizure outcome after surgery for epilepsy

Extraction of findings

To summarize the findings of the meta-analyses and reviews, outcome predictors (both positive and negative) and unrelated factors were extracted from the results of the papers. To overcome the variations between studies, common predictors of seizure outcome were extracted from the findings of the meta-analyses and reviews.

Common predictors or factors unrelated to surgical outcome in the literature were identified by counting the frequency of appearance of a predictor/unrelated factor in every literature subgroup (such as lesional or nonlesional TLE). If the papers in a literature subgroup had overlap (eg, for adults with lesional TLE), and the frequency of a predictor/unrelated factor was ≥2, the predictor/unrelated factor was considered to be as a common predictor/unrelated factor. On the other hand, if the papers in a literature subgroup had no overlap (eg, one for children and the other for adult patients), then the predictors/factors found by meta-analysis were still considered.

Results

Prediction of seizure outcome

The outcome predictors and factors unrelated to seizure outcome in patients with lesional or nonlesional TLE extracted from the literature are listed in . For patients with lesional or nonlesional ETLE, predictors and unrelated factors are listed in (lesional ETLE) and (non-lesional ETLE). Predictors and unrelated factors in patients with tuberous sclerosis complex are shown in .

Table 2 Predictors of seizure outcome for lesional and nonlesional TLE

Table 3 Predictors of seizure outcome for lesional ETLE

Table 4 Predictors of seizure outcome for nonlesional ETLE

Table 5 Predictors of seizure outcome for TSC

The predictors and factors unrelated to seizure outcome identified by the reviews and meta-analyses varied between patient groups and studies. In patients who underwent temporal lobectomy, seizure outcome was associated with a number of predictors, including diagnostic neuroimaging, lesional versus nonlesional epilepsy, and complete versus incomplete resection. However, in challenging epilepsy cases such as nonlesional ETLE, surgical outcome predictors were hard to identify, especially in adult patients. A meta-analysis by Ansari et al found that none of the factors (age at surgery, age at seizure onset, duration of epilepsy, seizure semiology, abnormality on MRI, lateralization of seizures) were significantly associated with seizure outcome, indicating that shortening the duration of epilepsy or pursuing surgery early does not improve outcomes in this case.Citation20

Common predictors and factors unrelated to seizure outcome in the findings of the meta-analyses for lesional and nonlesional TLE, lesional ETLE, and tuberous sclerosis complex were identified and the results are shown in . Because no predictors of seizure outcome for adult nonlesional ETLE patients were found by the meta-analysis of Ansari et al,Citation20 common predictors could not be extracted from the findings of the reviews or meta-analysis in nonlesional ETLE.

Table 6 Common predictors of seizure outcome for lesional or nonlesional TLE, lesional ETLE, and TSC

Other outcomes and interventions

The main findings of reviews or meta-analyses on other outcomes such as discontinuation of antiepileptic drugs (AEDs) and neuropsychologic outcomes are summarized in . Further, the main findings of the meta-analyses on epilepsy surgical options or other interventions are summarized in .

Table 7 Main literature findings on other outcomes including discontinuation of AEDs and neuropsychologic outcomes

Table 8 Main literature findings on surgical options or other interventions

Discussion

Identification of reliable prognostic factors or predictors of outcomes of epilepsy surgery is critical to reduce uncertainties for both surgical candidates and surgical teams. This study gathered together recent reviews and meta-analyses in this area, classified them into lesional or nonlesional TLE, ETLE, or tuberous sclerosis complex subgroups, summarized the findings, and made an effort to identify common predictors in order to obtain more reliable prognostic factors.

Common predictors of seizure outcome

Early research found that predictors of early recurrence include diffuse and poorly localized epilepsy, need for invasive electroencephalographic (EEG) recordings, and presence of interictal epileptiform abnormalities on postoperative EEG,Citation24 while more recent research found that a predictor of late failure was pathology consistent with focal cortical dysplasia type 1.Citation25 On the other hand, clinical factors, such as seizure frequency, duration of epilepsy, sex, age of onset, and laterality of seizure focus have not been shown to be risk factors for seizure recurrence.Citation18,Citation19 The results of this study indicate that lesional epilepsy (with a focal and identifiable lesion), an abnormal MRI, partial seizures, and complete resection are common positive predictors of seizure outcome in patients who undergo surgery for lesional or nonlesional TLE or lesional ETLE. On the other hand, indicators such as nonlesional epilepsy, a poorly defined and localized epileptic focus (with normal MRI, bilateral/multifocal lesion on MRI, or nonlocalizing EEG), generalized seizures, and incomplete resection are common negative predictors, while clinical factors such as age at surgery and side of surgery are consistently unrelated to surgical outcome following surgery for patients with TLE or lesional ETLE.

The common predictors/unrelated factors provide a very rough picture on what clinical factors are associated/unassociated with seizure outcome and how they are related or unrelated to outcome. For example, abnormal preoperative MRI has been frequently identified as a strong positive predictor of postoperative outcome (with a wide odds ratio of 0.44–1.67), while a normal MRI and a nonlocalizing EEG have been frequently regarded as strong negative predictors, whereas duration of epilepsy and seizure frequency have been frequently identified as factors unrelated to seizure outcome. However, because no predictors were found for adult patients with nonlesional ETLECitation20 and there is no other meta-analysis on seizure outcome prediction in this case, common prognostic factors/predictors could not be identified for nonlesional ETLE in adults. More studies are needed to identify possible predictors/risk factors of seizure outcome in challenging cases such as nonlesional ETLE.

Neuroimaging as an outcome predictor

Mild lesions, such as mild hippocampal sclerosis and focal cortical dysplasia, are hard to identify on regular MRI. They may be missed by MRI, misinterpreted as nonlesional, and even excluded from presurgical evaluation. Therefore, there are controversies regarding the utility of neuroimaging in predicting surgical outcome.Citation26 Given that neuroimaging modalities such as PET, SPECT, and MEG are less frequently used than MRI in presurgical evaluation,Citation27 and usually do not reach the significance threshold in multivariate analysis as does MRI,Citation11 they are less frequently identified as predictors of surgical outcome by meta-analyses. In addition, meta-analyses such as the one reported by Téllez-Zenteno et alCitation22 tend to emphasize the presence of a lesion as a predictor regardless of what neuroimaging is used to identify the lesion. However, advances in neuroimaging have increased the diagnostic yield by revealing dysplastic lesions that previously eluded visual inspection,Citation28 and the predictive value of neuroimaging with regard to outcome has been increasingly identified.Citation2Citation5,Citation7Citation9 In addition to MRI, MEG/MSI, PET, and ictal SPECT also have a positive predictive value in predicting seizure outcome.Citation6 Further, it was found that focal unilateral MRS metabolite alterations that are in agreement with the EEG focus are associated with a good outcome, while contralateral or bilateral metabolite abnormalities are associated with a poor outcome.Citation29 Therefore, diagnostic imaging and resection have been regarded as the most important factors in prediction of seizure outcome following surgery for focal cortical dysplasia.Citation26 The results of this study tend to support this, in that diagnostic imaging and resection were the most important factors in seizure outcome prediction, not only for focal cortical dysplasia, but also for other lesional or nonlesional TLE and ETLE.Citation16,Citation23

Further, the utility of neuroimaging predictors of seizure outcome has been explored. Because patients with unilateral radiographic mesial temporal sclerosis are considered “ideal” candidates for epilepsy surgery, research on outcome prediction has been done in this group of patients as a priority, and high prediction/classification accuracy has been obtained. Using a multivariable analysis model, Berg et al found that mesial temporal sclerosis (relative risk 1.47–1.49) coupled with documented etiology (1.32) and partial seizures (1.17–1.24) could identify patients (n=133 and n=81, respectively) with a nearly 100% seizure-free outcome.Citation30 Focke et al applied automatic support vector machine classification to MRI and diffusion tensor images for left or right hippocampal sclerosis in TLE, and achieved a 90%–100% classification accuracy.Citation31 In addition, Feis et al found that surgical outcome could be predicted in male (94% balanced accuracy) and female (96% balanced accuracy) patients using presurgical structural MRI.Citation21 These results are encouraging, but are not applicable to other cases. For example, in patients with nonlesional or bilateral/multifocal TLE, because the odds ratios of the predictors (eg, abnormal MRI for focal cortical dysplasia with an odds ratio of 1.67 or probability of 0.63Citation26) are relatively low, the predictive power of these common predictors is limited, and the prediction accuracy is low. Thus, the overall prediction accuracy for surgical outcome is not high, especially in challenging epilepsy cases such as nonlesional ETLE, and more research is needed to improve it.

Other outcome prediction

Discontinuation of AEDs is an important outcome of surgical treatment for epilepsy, and a surgical cure for drug-resistant epilepsy is regarded as both seizure freedom and discontinuation of AEDs.Citation32 Téllez-Zenteno et al reported that children achieved better AED discontinuation than adults and longer follow-up was associated with less AED discontinuation.Citation33 Schmidt et al found that better cure rates were achieved in children with hippocampal sclerosis and those with typical Ammon’s horn sclerosis or tumors.Citation32 These findings indicate that young age is associated with a better chance of AED discontinuation.

Meta-analysis of neuropsychologic outcomes is difficult and rare due to a lack of standardized testing and reporting between studies.Citation34 For example, Vaz found that the current research cannot provide consistent evidence regarding nonverbal memory outcome following right anterior temporal lobectomy,Citation35 and the improved long-term psychosocial outcomes consistently reported by uncontrolled studies were less clear in controlled studies.Citation33 However, a meta-analysis covering 35 papers (from 1991 to 2005) found that memory decline occurred in patients after left temporal resections but that intelligence was not significantly changed by surgery.Citation33 Further, presurgical functional MRI is useful in predicting verbal memory decline following left anterior temporal lobectomy,Citation36 but neuroimaging is not regarded as a predictor of cognitive outcomes by meta-analysis.Citation33 Other factors seemed to be more significant. For example, long-term memory outcomes were associated with seizure freedom and side of temporal lobe resection,Citation33 while decline in naming was associated with the absence of structural hippocampal pathology and late-onset epilepsy.Citation37 In general, poor cognitive outcome is associated with early onset, long duration of epilepsy, and poor seizure control.Citation33

Impact of interventional options on outcomes

Finally, treatment options and types of surgery play a critical role in determining surgical outcomes. Schmidt and Stavem reported that surgery and medical treatment is four times as likely as medical treatment alone to achieve seizure freedom.Citation38 In epilepsy surgery, anterior temporal lobectomy is more likely to achieve seizure freedom than selective amygdalohippocampectomy, while selective amygdalohippocampectomy may have improved neuropsychologic outcomes.Citation34 As adjunctive therapies, multiple subpial transection and vagus nerve stimulation could reduce (but not cure) seizures, and preserve some neuropsychologic functions.Citation39,Citation40

Limitations

This study is limited by the available reviews and meta-analyses identified in the literature. In addition, the simple method used in this study to identify common predictors might be biased due to the few meta-analyses available and the variable findings of the meta-analyses in each subgroup (lesional, nonlesional TLE, or ETLE). Therefore, the common predictors extracted might not reflect true outcome predictors. Ideally, a comprehensive meta-analysis could include and analyze all the related studies in the literature in each subgroup of children or adult patients, thereby providing a clearer picture of the truly reliable predictors of seizure outcome, and largely reduce the variations in the findings of different meta-analyses in each subgroup. Better methods for exploring outcome prediction and identifying reliable predictors of seizure outcome after epilepsy surgery are needed.

Conclusion

In summary, common predictors/factors for TLE, lesional ETLE, and tuberous sclerosis complex were identified in this study. Clinical factors such as lesional epilepsy, abnormal MRI, partial seizures, and complete resection are common positive predictors, and indicators such as nonlesional epilepsy, poorly defined and localized epileptic focus (with normal MRI or bilateral/multifocal lesion on MRI, or nonlocalizing EEG), generalized seizures, and incomplete resection are common negative predictors, while factors such as age at surgery and side of surgery are unrelated to seizure outcome after surgery for TLE and lesional ETLE. Diagnostic neuroimaging and resection are among the most important predictors of seizure outcome in TLE and lesional ETLE. However, no common predictors of seizure outcome were identified in nonlesional ETLE. In addition, meta-analysis of other outcomes, such as neuropsychologic outcomes, has been rare due to lack of evaluation standards. Further studies on the identification of reliable prognostic factors for surgical outcomes are needed.

Acknowledgments

This work was partially supported by the National Natural Science Foundation of China (81071211).

Disclosure

The authors report no conflicts of interest in this work.

References

  • Téllez-ZentenoJFDharRWiebeSLong-term seizure outcomes following epilepsy surgery: a systematic review and meta-analysisBrain2005128Pt 51188119815758038
  • LernerJTSalamonNHauptmanJSAssessment and surgical outcomes for mild type I and severe type II cortical dysplasia: a critical review and the UCLA experienceEpilepsia2009501310133519175385
  • CossuMLo RussoGFrancioneSEpilepsy surgery in children: results and predictors of outcome on seizuresEpilepsia200849657217645538
  • Widdess-WalshPJehaLNairDKotagalPBingamanWNajmISubdural electrode analysis in focal cortical dysplasia: predictors of surgical outcomeNeurology20076966066717698787
  • JehaLENajmIBingamanWDinnerDWiddess-WalshPLüdersHSurgical outcome and prognostic factors of frontal lobe epilepsy surgeryBrain200713057458417209228
  • KnowltonRCElgavishRABartolucciAFunctional imaging: II. Prediction of epilepsy surgery outcomeAnn Neurol200864354118570291
  • KuznieckyRHuggJHetheringtonHPredictive value of 1 H MRSI for outcome in temporal lobectomyNeurology19995369469810489028
  • EberhardtKEStefanHBuchfelderMThe significance of bilateral CSI changes for the postoperative outcome in temporal lobe epilepsyJ Comput Assist Tomogr20002491992611105713
  • StefanHPauliEEberhardtKEMRI spectroscopy, T2 relaxometry, and postoperative prognosis in cryptogenic temporal lobe epilepsyNervenarzt200071282287 German10795095
  • ValeFLPollockGBenbadisSRFailed epilepsy surgery for mesial temporal lobe sclerosis: a review of the pathophysiologyNeurosurg Focus2012323E922380863
  • EnglotDJWangDDRolstonJDShihTTChangEFRates and predictors of long-term seizure freedom after frontal lobe epilepsy surgery: a systematic review and meta-analysisJ Neurosurg20121161042104822304450
  • AboschABernasconiNBolingWFactors predictive of suboptimal seizure control following selective amygdalohippocampectomyJ Neurosurg2002971142115112450037
  • HennessyMJElwesRDRabe-HeskethSBinnieCDPolkeyCEPrognostic factors in the surgical treatment of medically intractable epilepsy associated with mesial temporal sclerosisActa Neurol Scand200110334435011421846
  • JanszkyJPannekHWJanszkyIFailed surgery for temporal lobe epilepsy: predictors of long-term seizure-free courseEpilepsy Res200564354415894459
  • TezerFIAkalanNOguzKKPredictive factors for postoperative outcome in temporal lobe epilepsy according to two different classificationsSeizure20081754956018403220
  • BeghiEToniniCSurgery for epilepsy: assessing evidence from observational studiesEpilepsy Res2006709710216713183
  • HarroudABouthillierAWeilAGNguyenDKTemporal lobe epilepsy surgery failures: a reviewEpilepsy Res Treat2012201220165122934162
  • KilpatrickCCookMMatkovicZO’BrienTKayeAMurphyMSeizure frequency and duration of epilepsy are not risk factors for postoperative seizure outcome in patients with hippocampal sclerosisEpilepsia19994089990310403213
  • RamosEBenbadisSValeFLFailure of temporal lobe resection for epilepsy in patients with mesial temporal sclerosis: results and treatment optionsJ Neurosurg20091101127113419249930
  • AnsariSFTubbsRSTerryCLCohen-GadolAASurgery for extratemporal nonlesional epilepsy in adults: an outcome meta-analysisActa Neurochir (Wien)20101521299130520524016
  • FeisDLSchoene-BakeJCElgerCWagnerJTittgemeyerMWeberBPrediction of post-surgical seizure outcome in left mesial temporal lobe epilepsyNeuroImage Clinical2013290391124179841
  • Téllez-ZentenoJFHernández RonquilloLMoien-AfshariFWiebeSSurgical outcomes in lesional and nonlesional epilepsy: a systematic review and meta-analysisEpilepsy Res20108931031820227852
  • ToniniCBeghiEBergATPredictors of epilepsy surgery outcome: a meta-analysisEpilepsy Res200462758715519134
  • JehaLENajmIMBingamanWEPredictors of outcome after temporal lobectomy for the treatment of intractable epilepsyNeurology2006661938194016801667
  • NajmIJehiLPalminiAGonzalez-MartinezJPaglioliEBingamanWTemporal patterns and mechanisms of epilepsy surgery failureEpilepsia20135477278223586531
  • RowlandNCEnglotDJCageTASughrueMEBarbaroNMChangEFA meta-analysis of predictors of seizure freedom in the surgical management of focal cortical dysplasiaJ Neurosurg20121161035104122324422
  • JansenFEvan HuffelenACAlgraAvan NieuwenhuizenOEpilepsy surgery in tuberous sclerosis: a systematic reviewEpilepsia2007481477148417484753
  • BernasconiABernasconiNBernhardtBCSchraderDAdvances in MRI for ‘cryptogenic’ epilepsiesNat Rev Neurol201179910821243016
  • HammenTKuznieckyRMagnetic resonance spectroscopy in epilepsyStefanHTheodoreWHHandbook of Clinical Neurology. Epilepsy, Part INew York, NYElsevier Science2012107
  • BergATWalczakTHirschLJSpencerSSMultivariable prediction of seizure outcome one year after resective epilepsy surgery: development of a model with independent validationEpilepsy Res1998291851949551780
  • FockeNKYogarajahMSymmsMRGruberOPaulusWDuncanJSAutomated MR image classification in temporal lobe epilepsyNeuroimage20125935636221835245
  • SchmidtDBaumgartnerCLoscherWThe chance of cure following surgery for drug-resistant temporal lobe epilepsy. What do we know and do we need to revise our expectations?Epilepsy Res20046018720115380563
  • Téllez-ZentenoJFDharRHernandez-RonquilloLWiebeSLong-term outcomes in epilepsy surgery: antiepileptic drugs, mortality, cognitive and psychosocial aspectsBrain2007130Pt 233434517124190
  • JosephsonCBDykemanJFiestKMSystematic review and meta-analysis of standard vs selective temporal lobe epilepsy surgeryNeurology2013801669167623553475
  • VazSANonverbal memory functioning following right anterior temporal lobectomy: a meta-analytic reviewSeizure20041344645215324819
  • BinderJRSabsevitzDSSwansonSJHammekeTARaghavanMMuellerWMUse of preoperative functional MRI to predict verbal memory decline after temporal lobe epilepsy surgeryEpilepsia2008491377139418435753
  • Ives-DeliperiVLButlerJTNaming outcomes of anterior temporal lobectomy in epilepsy patients: a systematic review of the literatureEpilepsy Behav20122419419822569529
  • SchmidtDStavemKLong-term seizure outcome of surgery versus no surgery for drug-resistant partial epilepsy: a review of controlled studiesEpilepsia2009501301130919243421
  • SpencerSSSchrammJWylerAMultiple subpial transection for intractable partial epilepsy: an international meta-analysisEpilepsia20024314114511903459
  • EnglotDJChangEFAugusteKIVagus nerve stimulation for epilepsy: a meta-analysis of efficacy and predictors of responseJ Neurosurg20111151248125521838505
  • McIntoshAMWilsonSJBerkovicSFSeizure outcome after temporal lobectomy: current research practice and findingsEpilepsia2001421288130711737164
  • EnglotDJRolstonJDWangDDSunPPChangEFAugusteKISeizure outcomes after temporal lobectomy in pediatric patientsJ Neurosurg Pediatr20131213414123768202
  • EnglotDJBreshearsJDSunPPChangEFAugusteKISeizure outcomes after resective surgery for extra-temporal lobe epilepsy in pediatric patientsJ Neurosurg Pediatr20131212613323768201
  • AnsariSFMaherCOTubbsRSTerryCLCohen-GadolAASurgery for extratemporal nonlesional epilepsy in children: a meta-analysisChilds Nerv Syst20102694595120013124
  • ZhangKHuWHZhangCMengFGChenNZhangJGPredictors of seizure freedom after surgical management of tuberous sclerosis complex: a systematic review and meta-analysisEpilepsy Res201312134141
  • FallahAGuyattGHSneadOC3rdPredictors of seizure outcomes in children with tuberous sclerosis complex and intractable epilepsy undergoing resective epilepsy surgery: an individual participant data meta-analysisPLoS One20138e5356523405072