Altered structural connectome in non-lesional newly diagnosed focal epilepsy: Relation to pharmacoresistance

Kreilkamp, Barbara A.K.; McKavanagh, Andrea; Alonazi, Batil; Bryant, Lorna; Das, Kumar; Wieshmann, Udo; Marson, Anthony G; Taylor, Peter Neal; Keller, Simon S.

doi:10.1016/j.nicl.2021.102564

Cited by 20 publications

(21 citation statements)

References 64 publications

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“…The remaining 128 reports were sought for retrieval, of which 126 were obtained. The retrieved reports were then assessed for eligibility, during which 77 were excluded due to univariable modelling (44), unsuitable cohorts (20), unsuitable outcomes (12), or absence of primary analysis (1). The remaining reports underwent data extraction, during which 17 were deemed ineligible.…”

Section: Study Selectionmentioning

confidence: 99%

“…10,11 Studying epilepsy at its earliest time point avoids the confounds inherent in long- standing epilepsy, including the chronic effects of seizure activity and ASM use: seizure activity in chronic epilepsy can cause injuries that encourage the development of pharmacoresistance in PWE, and successive ASM regimens are associated with a reduction in the chance of attaining seizure freedom. 12–15 Predictive models for chronic epilepsy consequently include the confounding variability of seizure and ASM profiles, whereas models developed specifically for use in NDE (which can reliably prognosticate disease trajectories) do not. Models based on NDE cohorts can therefore inform treatment approaches that ameliorate the consequences of epilepsy chronicity.…”

Section: Introductionmentioning

confidence: 99%

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Clinical Prediction Models for Treatment Outcomes in Newly-diagnosed Epilepsy

Ratcliffe,

Pradeep,

Marson

et al. 2024

Preprint

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Background: Up to 35% of individuals diagnosed with epilepsy proceed to develop pharmacoresistant epilepsy, leading to persistent uncontrolled seizure activity that can directly, or indirectly, significantly degrade an individual's quality of life. The factors underlying pharmacoresistance are unclear, but it has been hypothesised that repeated ictogenic activity is conducive to the development of a more robust epileptogenic network. To ensure that the most effective treatment choices are made and ictogenic activity is minimised, accurate outcome modelling at the point of diagnosis is key. Objectives: This review therefore aims to identify demographic, clinical, physiological (e.g. EEG), and imaging (e.g. MRI) factors that may be predictive of treatment outcomes in patients with newly diagnosed epilepsy (NDE). Data sources, study eligibility criteria, participants, and interventions: MEDLINE and EMBASE were searched for prediction models of treatment outcomes in patients with newly diagnosed epilepsy and any non-surgical treatment plan. Study appraisal and synthesis methods: Study characteristics were extracted and subjected to assessment of risk of bias (and applicability concerns) using the PROBAST tool. Prognostic factors associated with treatment outcomes are reported. Results: After screening, 48 models were identified in 32 studies, which generally scored low for concerns of applicability, but universally high for susceptibility to bias. Outcomes reported were heterogenous, but fit broadly into four categories: pharmacoresistance, short-term treatment response, seizure remission, and mortality. Prognostic factors were also heterogenous, but the predictors that were commonly significantly associated with outcomes were those related to seizure characteristics (semiology), epilepsy history, and age at onset. ASM response was often included as a prognostic factor, potentially obscuring factor relationships at baseline. Conclusions: Currently, outcome prediction models for NDE demonstrate a high risk of bias. Model development could be improved with a stronger adherence to recommended TRIPOD practices, and by avoiding including response to treatment as a prognostic factor. Implications of key findings: This review identified semiology, epilepsy history, and age at onset as factors associated with treatment outcome prognosis, suggesting that future prediction model studies should focus on these factors in their models. Furthermore, we outline actionable changes to common practices that are intended to improve the overall quality of prediction model development in NDE. Keywords: newly diagnosed epilepsy, seizures, prognosis, intractability, outcomes, treatment

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Section: Study Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Clinical Prediction Models for Treatment Outcomes in Newly-diagnosed Epilepsy

Ratcliffe,

Pradeep,

Marson

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

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“…Evidence for the network hypothesis comes from the possible clinical success of surgical interventions that can result in seizure control or convert a DRE into a drug‐sensitive epilepsy 69–71 . Moreover, a clinical association between drug responsiveness and the connectome has been suggested by neuropathological studies, structural imaging studies, and electroencephalographic functional network topology analysis 68,72–75 . Despite this evidence, it seems crucial to expand our knowledge and further explore the influence of aberrant connectivity on areas and brain circuits involved in ictogenesis and how ASMs may or may not work to prevent ictal activity in critical brain regions.…”

Section: Potential Mechanisms Of Drementioning

confidence: 99%

Revisiting the concept of drug‐resistant epilepsy: A TASK1 report of the ILAE/AES Joint Translational Task Force

Auvin,

Galanopoulou,

Moshé

et al. 2023

Epilepsia

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Despite progress in the development of anti‐seizure medications (ASMs), one third of people with epilepsy have drug‐resistant epilepsy (DRE). The working definition of DRE, proposed by the International League Against Epilepsy (ILAE) in 2010, helped identify individuals who might benefit from presurgical evaluation early on. As the incidence of DRE remains high, the TASK1 workgroup on DRE of the ILAE/American Epilepsy Society (AES) Joint Translational Task Force discussed the heterogeneity and complexity of its presentation and mechanisms, the confounders in drawing mechanistic insights when testing treatment responses, and barriers in modeling DRE across the lifespan and translating across species. We propose that it is necessary to revisit the current definition of DRE, in order to transform the preclinical and clinical research of mechanisms and biomarkers, to identify novel, effective, precise, pharmacologic treatments, allowing for earlier recognition of drug resistance and individualized therapies.

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“… 12 , 13 Even in non-lesional newly diagnosed focal epilepsy patients, those with persistent seizures have bilateral structural network impairment compared to patients who were seizure-free with ASMs at 24-months since diagnosis in 1 investigation. 14 In another study examining idiopathic/genetic generalized epilepsy (IGE), drug-responsive patients had reduced diffusion network alterations than drug-resistant IGE patients with bi-hemispheric structural network alterations. 15 These studies indicate that epileptic networks might be more altered in drug-resistant epilepsy patients and measuring these alterations can be a marker for the prognosis of drug resistance in the early stages of epilepsy treatment.…”

Section: Progressmentioning

confidence: 99%

Integrating Network Neuroscience Into Epilepsy Care: Progress, Barriers, and Next Steps

et al. 2022

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Drug resistant epilepsy is a disorder involving widespread brain network alterations. Recently, many groups have reported neuroimaging and electrophysiology network analysis techniques to aid medical management, support presurgical planning, and understand postsurgical seizure persistence. While these approaches may supplement standard tests to improve care, they are not yet used clinically or influencing medical or surgical decisions. When will this change? Which approaches have shown the most promise? What are the barriers to translating them into clinical use? How do we facilitate this transition? In this review, we will discuss progress, barriers, and next steps regarding the integration of brain network analysis into the medical and presurgical pipeline.

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Altered structural connectome in non-lesional newly diagnosed focal epilepsy: Relation to pharmacoresistance

Cited by 20 publications

References 64 publications

Clinical Prediction Models for Treatment Outcomes in Newly-diagnosed Epilepsy

Clinical Prediction Models for Treatment Outcomes in Newly-diagnosed Epilepsy

Revisiting the concept of drug‐resistant epilepsy: A TASK1 report of the ILAE/AES Joint Translational Task Force

Integrating Network Neuroscience Into Epilepsy Care: Progress, Barriers, and Next Steps

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