Evaluation of long-term antiepileptic drug use in patients with temporal lobe epilepsy: Assessment of risk factors for drug resistance and polypharmacy

Bjørke, Agnes Balint; Nome, Cecilie G.; Falk, Ragnhild Sørum; Gjerstad, Leif; Taubøll, Erik

doi:10.1016/j.seizure.2018.07.011

Cited by 21 publications

(10 citation statements)

References 61 publications

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“…The AUC of predictive model is as high as 0.96, which suggests that this model is promising to be applicable in clinical practice. In the previous research, some seizure-related characteristics, including the prior number of seizures and disease course, were reported to be related with the risk of drug resistance 4,9. Another factor strongly linked to the increased risk of intractable epilepsy is HS, which is consistent with the findings in our study.…”

supporting

confidence: 92%

“…2,3 Moreover, cognitive impairment and psychiatric comorbidities including depression and anxiety disorders, together with the longterm actual seizures and accompanying drug usage, often result in severe effects on the quality of life and individual health. 4,5 At present, the diagnosis of epilepsy mainly depends on clinical manifestation, neuroimaging, and electroencephalogram (EEG).…”

Section: Introductionmentioning

confidence: 99%

“…6,7 Furthermore, drug-response prediction is mainly based on subjective clinical features by experience and has not come to a conclude. 4,8,9 Earlier identification of drug-resistant patients makes it possible to benefit from epilepsy surgery. Thus, biomarkers for assisting the current diagnosis and predicting the treatment outcome are in urgent need.…”

Section: Introductionmentioning

confidence: 99%

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CpG methylation signature defines human temporal lobe epilepsy and predicts drug‐resistant

et al. 2020

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Aims Temporal lobe epilepsy (TLE) is the most common focal epilepsy syndrome in adults and frequently develops drug resistance. Studies have investigated the value of peripheral DNA methylation signature as molecular biomarker for diagnosis or prognosis. We aimed to explore methylation biomarkers for TLE diagnosis and pharmacoresistance prediction. Methods We initially conducted genome‐wide DNA methylation profiling in TLE patients, and then selected candidate CpGs in training cohort and validated in another independent cohort by employing machine learning algorithms. Furthermore, nomogram comprising DNA methylation and clinicopathological data was generated to predict the drug response in the entire patient cohort. Lastly, bioinformatics analysis for CpG‐associated genes was performed using Ingenuity Pathway Analysis. Results After screening and validation, eight CpGs were identified for diagnostic biomarker with an area under the curve (AUC) of 0.81 and six CpGs for drug‐resistant prediction biomarker with an AUC of 0.79. The nomogram for drug‐resistant prediction comprised methylation risk score, disease course, seizure frequency, and hippocampal sclerosis, with AUC as high as 0.96. Bioinformatics analysis indicated drug response–related CpGs corresponding genes closely related to DNA methylation. Conclusions This study demonstrates the ability to use peripheral DNA methylation signature as molecular biomarker for epilepsy diagnosis and drug‐resistant prediction.

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confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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CpG methylation signature defines human temporal lobe epilepsy and predicts drug‐resistant

et al. 2020

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“…There are many theories and hypotheses about the causes of drug resistance in TLE (9) . There have also been many studies to predict whether TLE can evolve into drug resistance through the effect of initial drug treatment (10) and seizure frequency (11) . Furthermore, several studies have speculated about the possible mechanism of drug resistance in TLE by detecting levels of some target proteins, genes, and molecules (12)(13)(14).…”

Section: The Interictal Discharge Neural Network Of Refractory Tle Mamentioning

confidence: 99%

Factors affecting interictal unilateral and bilateral discharges and ictal diffusion patterns of scalp electroencephalogram in temporal lobe epilepsy

Chen

et al. 2019

Preprint

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Purpose To evaluate preoperative factors influencing unilateral and bilateral interictal discharges in TLE, and ictal diffusion patterns in scalp EEG during onset of the seizure.Methods This was a retrospective analysis of 129 patients with TLE who had undergone surgery; cases were classified into two groups of unilateral and bilateral discharge groups according to interictal discharge patterns in the EEG. In this study, unilateral interictal discharges meaned that the discharge was confined to one hemisphere, while bilateral interictal discharges meaned that the discharge involved both hemispheres. Differences between the two groups in age, gender, duration of disease, frequency of seizures, MRI findings, origin of TLE, antiepileptic drug administration, and ictal diffusion patterns during seizures were statistically analyzed. In addition, the differences in ictal diffusion patterns between left and right TLE were statistically analyzed.Results There were a total of 74 cases of unilateral discharges, including unilateral discharges in the temporal region, anterior head including both temporal and frontal regions, and unilateral hemispheric discharges, and there were another 55 cases of bilateral discharges, including bilateral temporal area, bilateral anterior heads, and bilateral hemispheric multi-brain areas. There were 60 cases of left TLE and 69 cases of right TLE. There were no statistically significant differences in gender, duration of disease, frequency of seizures, MRI manifestations, administration of antiepileptic drugs, and ictal diffusion patterns between interictal unilateral and bilateral discharge groups, but, there were statistically significant differences in age and side of origin of the TLE. Scalp EEG recorded 11 different ictal diffusion pattern types, and the difference in terms of whether the EEG recorded the diffusion pattern to be confined to the same hemisphere or spread to both hemispheres was statistically significant between the left and right temporal lobes.Conclusion Age and side of origin of TLE affects the TLE interictal discharge patterns. Older patients are more prone to bilateral discharges. Bilateral discharges are more common in right TLE, and the onset of EEG more likely to bilateral diffusion in right TLE.

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“…As the duration of the disease increases, there is a risk of drug resistance and polypharmacy. Worse, second-generation antiepileptic drugs provide no additional effect for poor responders to first-generation drugs [117]. Studies have proposed using randomness in such cases to partially overcome tolerance to therapies and to improve the efficacy of therapies [118–120].…”

Section: Introductionmentioning

confidence: 99%

Generating randomness: making the most out of disordering a false order into a real one

Ilan

2019

J Transl Med

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Randomness is far from a disturbing disorder in nature. Rather, it underlies many processes and functions. Randomness can be used to improve the efficacy of development and of systems under certain conditions. Moreover, valid unpredictable random-number generators are needed for secure communication, rendering predictable pseudorandom strings unsuitable. This paper reviews methods of generating randomness in various fields. The potential use of these methods is also discussed. It is suggested that by disordering a “false order,” an effective disorder can be generated to improve the function of systems.

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Evaluation of long-term antiepileptic drug use in patients with temporal lobe epilepsy: Assessment of risk factors for drug resistance and polypharmacy

Cited by 21 publications

References 61 publications

CpG methylation signature defines human temporal lobe epilepsy and predicts drug‐resistant

CpG methylation signature defines human temporal lobe epilepsy and predicts drug‐resistant

Factors affecting interictal unilateral and bilateral discharges and ictal diffusion patterns of scalp electroencephalogram in temporal lobe epilepsy

Generating randomness: making the most out of disordering a false order into a real one

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