Epilepsy, characterised by a predisposition towards unprovoked seizures, is one of the most common neurological disorders globally. Whilst 60-70% of individuals diagnosed with epilepsy will gain seizure control through anti-seizure medication, the mechanisms underlying seizure persistence are unclear. Intractability can significantly degrade a patient’s quality of life amongst other things; the use of predictive modelling of epilepsy outcomes in deciding on treatment therefore offers a tangible benefit to the patient. Early indicators of pharmacoresistance may discourage certain treatment options, and save time in what has been indicated to be a critical stage for newly-diagnosed epilepsy. Primarily, this paper aims to evaluate existing predictive models to identify demographic, clinical, physiological (e.g. EEG), and neuroimaging (e.g. MRI) factors that may be predictive of treatment outcomes in newly-diagnosed epilepsy. Two electronic databases, MEDLINE and EMBASE, will be searched with terms related to prognosis in newly-diagnosed epilepsy, and identified studies will be included for review if they have combined at least two demographic, clinical, neuroimaging, and/or physiological factors to predict treatment outcome in people with newly-diagnosed epilepsy. Papers will be screened by two independent reviewers via titles, abstracts and then full text against the inclusion criteria for eligibility. Data will be extracted by reviewers using standardised forms, assessed for risk of bias using the PROBAST tool and synthesised narratively. If considered appropriate the authors will carry out a meta-analysis on the available data.
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