Protocol for a prospective observational study of adverse drug reactions of anti-epileptic drugs in children in the UK

A computational clinical decision-supporting system to suggest effective anti-epileptic drugs for pediatric epilepsy patients based on deep learning models using patient's medical history

BACKGROUND

Epilepsy, a chronic brain disorder characterized by abnormal brain activity that causes seizures and other symptoms, is typically treated using anti-epileptic drugs (AEDs) as the first-line therapy. However, due to the variations in their modes of action, identification of effective AEDs often relies on ad hoc trials, which is particularly challenging for pediatric patients. Thus, there is significant value in computational methods capable of assisting in the selection of AEDs, aiming to minimize unnecessary medication and improve treatment efficacy.

RESULTS

In this study, we collected 7,507 medical records from 1,000 pediatric epilepsy patients and developed a computational clinical decision-supporting system for AED selection. This system leverages three multi-channel convolutional neural network (CNN) models tailored to three specific AEDs (vigabatrin, prednisolone, and clobazam). Each CNN model predicts whether a respective AED is effective on a given patient or not. The CNN models showed AUROCs of 0.90, 0.80, and 0.92 in 10-fold cross-validation, respectively. Evaluation on a hold-out test dataset further revealed positive predictive values (PPVs) of 0.92, 0.97, and 0.91 for the three respective CNN models, representing that suggested AEDs by our models would be effective in controlling epilepsy with a high accuracy and thereby reducing unnecessary medications for pediatric patients.

CONCLUSION

Our CNN models in the system demonstrated high PPVs for the three AEDs, which signifies the potential of our approach to support the clinical decision-making by assisting doctors in recommending effective AEDs within the three AEDs for patients based on their medical history. This would result in a reduction in the number of unnecessary ad hoc attempts to find an effective AED for pediatric epilepsy patients.

Anti-Epileptic Drug Toxicity in Children

Anti-epileptic drugs (AEDs) have had a major impact on children, improving their quality of life and significantly reducing both morbidity and mortality. They are, however, associated with significant toxicity. Behavioural problems and somnolence are the most frequent adverse drug reactions for many AEDs. Unfortunately, the comparative risk of drug toxicity for different AEDs has been inadequately studied. Drug toxicity is poorly reported in randomised controlled trials. Prospective cohort studies are the best way to study drug toxicity. There have been a few prospective cohort studies of children with epilepsy, but the numbers of children have been small. Systemic reviews of the toxicity of individual AEDs have been helpful in identifying the risk of drug toxicity. Parents of children with epilepsy and the children and young people who are due to receive AED treatment have the right to know the likelihood of them experiencing drug toxicity. Unfortunately, the evidence base on which health professionals can provide such information is limited.