Better drugs are needed for common epilepsies. Drug repurposing offers the potential of significant savings in the time and cost of developing new treatments. In order to select the best candidate drug(s) to repurpose for a disease, it is desirable to predict the relative clinical efficacy that drugs will have against the disease. Common epilepsy can be divided into different types and syndromes. Different antiseizure medications are most effective for different types and syndromes of common epilepsy. For predictions of antiepileptic efficacy to be clinically translatable, it is essential that the predictions are specific to each form of common epilepsy, and reflect the patterns of drug efficacy observed in clinical studies and practice. These requirements are not fulfilled by previously published drug predictions for epilepsy. We developed a novel method for predicting the relative efficacy of drugs against any common epilepsy, by using its Genome Wide Association Study summary statistics and drugs’ activity data. The methodological advancement in our technique is that the drug predictions for a disease are based upon drugs’ effects on the function and abundance of proteins, and the magnitude and direction of those effects, relative to the importance, degree and direction of the proteins’ dysregulation in the disease. We used this method to predict the relative efficacy of all drugs, licensed for any condition, against each of the major types and syndromes of common epilepsy. Our predictions are concordant with findings from real-world experience and randomised clinical trials. Our method predicts the efficacy of existing antiseizure medications against common epilepsies; in this prediction, our method outperforms the best alternative existing method: area under receiver operating characteristic curve (mean ± standard deviation) 0.83 ± 0.03 and 0.63 ± 0.04, respectively. Importantly, our method predicts which antiseizure medications are amongst the more efficacious in clinical practice, and which antiseizure medications are amongst the less efficacious in clinical practice, for each of the main syndromes of common epilepsy, and it predicts the distinct order of efficacy of individual antiseizure medications in clinical trials of different common epilepsies. We identify promising candidate drugs for each of the major syndromes of common epilepsy. We screen five promising predicted drugs in an animal model: each exerts a significant dose-dependent effect upon seizures. Our predictions are a novel resource for selecting suitable candidate drugs that could potentially be repurposed for each of the major syndromes of common epilepsy. Our method is potentially generalizable to other complex diseases.
Introduction Radiation induced meningioma (RIM) incidence is increasing in line with improved childhood cancer survival. No optimal management strategy consensus exists. This study aimed to delineate meningioma growth rates from tumor discovery and correlate with clinical outcomes. Methods Retrospective study of patients with a RIM, managed at a specialist tertiary neuroscience center (2007–2019). Tumor volume was measured from diagnosis and at subsequent interval scans. Meningioma growth rate was determined using a linear mixed-effects model. Clinical outcomes were correlated with growth rates accounting for imaging and clinical prognostic factors. Results Fifty-four patients (110 meningiomas) were included. Median duration of follow-up was 74 months (interquartile range [IQR], 41–102 months). Mean radiation dose was 41 Gy (standard deviation [SD] = 14.9) with a latency period of 34.4 years (SD = 13.7). Median absolute growth rate was 0.62 cm3/year and the median relative growth rate was 72%/year. Forty meningiomas (between 27 patients) underwent surgical intervention after a median follow-up duration of 4 months (IQR 2–35). Operated RIMs were clinically aggressive, likely to be WHO grade 2 at first resection (43.6%) and to progress after surgery (41%). Median time to progression was 28 months (IQR 13–60.5). A larger meningioma at discovery was associated with growth (HR 1.2 [95% CI 1.0–1.5], P = 0.039) but not progression after surgery (HR 2.2 [95% CI 0.7–6.6], P = 0.181). Twenty-seven (50%) patients had multiple meningiomas by the end of the study. Conclusion RIMs exhibit high absolute and relative growth rates after discovery. Surgery is recommended for symptomatic or rapidly growing meningiomas only. Recurrence risk after surgery is high.
The outcomes following re-operation for meningioma are poorly described. The aim of this study was to identify risk factors for a performance status outcome following a second operation for a recurrent meningioma. A retrospective, comparative cohort study was conducted. The primary outcome measure was World Health Organization performance. Secondary outcomes were complications, and overall and progression free survival (OS and PFS respectively). Baseline clinical characteristics, tumor details, and operation details were collected. Multivariable binary logistic regression was used to identify risk factors for performance status outcome following a second operation. Between 1988 and 2018, 712 patients had surgery for intracranial meningiomas, 56 (7.9%) of which underwent a second operation for recurrence. Fifteen patients (26.8%) had worsened performance status after the second operation compared to three (5.4%) after the primary procedure (p = 0.002). An increased number of post-operative complications following the second operation was associated with a poorer performance status following that procedure (odds ratio 2.2 [95% CI 1.1–4.6]). The second operation complication rates were higher than after the first surgery (46.4%, n = 26 versus 32.1%, n = 18, p = 0.069). The median OS was 312.0 months (95% CI 257.8–366.2). The median PFS following the first operation was 35.0 months (95% CI 28.9–41.1). Following the second operation, the median PFS was 68.0 months (95% CI 49.1–86.9). The patients undergoing a second operation for meningioma had higher rates of post-operative complications, which is associated with poorer clinical outcomes. The decisions surrounding second operations must be balanced against the surgical risks and should take patient goals into consideration.
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