Evaluating fenfluramine hydrochloride as an oral solution for the treatment of seizures associated with Lennox-Gastaut syndrome

IntroductionLennox-Gastaut syndrome (LGS) is a severe childhood-onset developmental and epileptic encephalopathy characterised by treatment-refractory seizures, including tonic/atonic "drop" seizures, and intellectual impairment and slow spike-wave discharges on the electroencephalogram. Fenfluramine, previously prescribed as a weight-loss drug but then withdrawn, has recently been approved in the US, EU and UK for the adjunct treatment of seizures associated with LGS.Areas coveredEfficacy and safety findings from clinical trials of fenfluramine in LGS are reviewed. The evidence for adverse effects that may be of particular concern with fenfluramine, namely cardiac abnormalities and weight loss, are discussed in the context of the use of fenfluramine for the treatment of the refractory seizures in LGS.Expert opinionFenfluramine has demonstrated efficacy in reducing the frequency of seizures in LGS, notably drop seizures, in short-term and long-term clinical trials. Valvular heart disease and pulmonary hypertension have not been reported at the low doses (≤ 26 mg/day) used in these studies, however, data are limited. Due to its novel mechanism of action, fenfluramine may be of benefit in LGS which has not responded adequately to other antiseizure medications. However, none of these medications, including fenfluramine, achieves the ultimate goal of seizure freedom in most cases.<br/

Critical success index or F measure to validate the accuracy of administrative healthcare data identifying epilepsy in deceased adults in Scotland

Background: Methods to undertake diagnostic accuracy studies of administrative epilepsy data are challenged bylack of a way to reliably rank case-ascertainment algorithms in order of their accuracy. This is because it isdifficult to know how to prioritise positive predictive value (PPV) and sensitivity (Sens). Large numbers of truenegative (TN) instances frequently found in epilepsy studies make it difficult to discriminate algorithm accuracyon the basis of negative predictive value (NPV) and specificity (Spec) as these become inflated (usually &gt;90%).This study demonstrates the complementary value of using weather forecasting or machine learning metricscritical success index (CSI) or F measure, respectively, as unitary metrics combining PPV and sensitivity. Wereanalyse data published in a diagnostic accuracy study of administrative epilepsy mortality data in Scotland.Method: CSI was calculated as 1/[(1/PPV) + (1/Sens) – 1]. F measure was calculated as 2.PPV.Sens/(PPV +Sens). CSI and F values range from 0 to 1, interpreted as 0 = inaccurate prediction and 1 = perfect accuracy. Thepublished algorithms were reanalysed using these and their accuracy re-ranked according to CSI in order to allowcomparison to the original rankings.Results: CSI scores were conservative (range 0.02–0.826), always less than or equal to the lower of the correspondingPPV (range 39–100%) and sensitivity (range 2–93%). F values were less conservative (range0.039–0.905), sometimes higher than either PPV or sensitivity, but were always higher than CSI. Low CSI and Fvalues occurred when there was a large difference between PPV and sensitivity, e.g. CSI was 0.02 and F was0.039 in an instance when PPV was 100% and sensitivity was 2%. Algorithms with both high PPV and sensitivityperformed best in terms of CSI and F measure, e.g. CSI was 0.826 and F was 0.905 in an instance when PPV was90% and sensitivity was 91%.Conclusion: CSI or F measure can combine PPV and sensitivity values into a convenient single metric that is easierto interpret and rank in terms of diagnostic accuracy than trying to rank diagnostic accuracy according to the twomeasures themselves. CSI or F prioritise instances where both PPV and sensitivity are high over instances wherethere are large differences between PPV and sensitivity (even if one of these is very high), allowing diagnosticaccuracy thresholds based on combined PPV and sensitivity to be determined. Therefore, CSI or F measures maybe helpful complementary metrics to report alongside PPV and sensitivity in diagnostic accuracy studies ofadministrative epilepsy data

Comparison of neurodevelopmental, educational and adult socioeconomic outcomes in offspring of women with and without epilepsy : A systematic review and meta-analysis

Peer reviewe

Efficient organisation of the contralateral hemisphere connectome is associated with improvement in intelligence quotient after paediatric epilepsy surgery

Objective: Aims of epilepsy surgery in childhood include optimising seizure control and facilitating cognitive development. Predicting which children will improve cognitively is challenging. We investigated the association of the pre-operative structural connectome of the contralateral non-operated hemisphere with improvement in intelligence quotient (IQ) post-operatively. Methods: Consecutive children who had undergone unilateral resective procedures for epilepsy at a single centre were retrospectively identified. We included those with pre-operative volume T1-weighted non-contrast brain magnetic resonance imaging (MRI), no visible contralateral MRI abnormalities, and both pre-operative and two years post-operative IQ assessment. The MRI of the hemisphere contralateral to the side of resection was anatomically parcellated into 34 cortical regions and the covariance of cortical thickness between regions was used to create binary and weighted group connectomes. Results: Eleven patients with a post-operative IQ increase of at least 10 points at two years were compared with twenty-four patients with no change in IQ score. Children who gained at least 10 IQ points post-operatively had a more efficiently structured contralateral hemisphere connectome with higher global efficiency (0.74) compared to those whose IQ did not change at two years (0.58, p = 0.014). This was consistent across thresholds and both binary and weighted networks. There were no statistically significant group differences in age, sex, age at onset of epilepsy, pre-operative IQ, mean cortical thickness, side or site of procedure, two year post-operative Engel scores or use of anti-seizure medications between the two groups. Conclusions: Surgical procedures to reduce or stop seizures may allow children with an efficiently structured contralateral hemisphere to achieve their cognitive potential

The association of structural connectome efficiency with cognition in children with epilepsy

Objective: Cognitive impairment is common in children with epilepsy (CWE), but understanding the underlying pathological processes is challenging. We aimed to investigate the association of structural brain network organisation with cognition. Methods: This was a retrospective cohort study of CWE without structural brain abnormalities, comparing whole brain network characteristics between those with cognitive impairment and those with intact cognition. We created structural whole-brain connectomes from anatomical and diffusion tensor magnetic resonance imaging using the number of streamlines and tract-averaged fractional anisotropy. We assessed the differences in average path length and global network efficiency between children with cognitive impairment and those without,using multivariable analyses to account for possible clinical group differences. Results: Twenty-eight CWE and cognitive impairment had lower whole brain network global efficiency compared with 34 children with intact cognition (0.54, standard deviation (SD):0.003 vs. 0.56, SD:0.002, p < 0.001), which is equivalent to longer normalized network average path lengths (1.14, SD:0.05 vs. 1.10, SD:0.02, p = 0.003). In multivariable logistic regression cognitive impairment was not significantly associated with age of onset, duration of epilepsy, or number of antiseizure medications, but was independently associated with daily seizures (p = 0.04) and normalized average path length (p = 0.007). Conclusions: Higher structural network average path length and lower global network efficiency may be imaging biomarkers of cognitive impairment in epilepsy. Understanding what leads to changes in structural connectivity could aid identification of modifiable risk factors for cognitive impairment. These findings are only applicable to the specific cohort studied, and further confirmation in other cohorts is required