Epilepsy Risk Prediction Model for Patients with Tuberous Sclerosis Complex

Background Individuals with tuberous sclerosis complex (TSC) are at increased risk of epilepsy. Early seizure control improves developmental outcomes, making identifying at-risk patients critically important. Despite several identified risk factors, it remains difficult to predict. The purpose of the study was to confirm previously identified risk factors for epilepsy in patients with TSC and evaluate the combined risk prediction of these factors. Methods The study group (N=333) were participants with TSC enrolled in the TSC Autism Center of Excellence Research Network and UT TSC Biobank. The outcome was defined as having an epilepsy diagnosis. Potential risk factors included sex, TSC genotype, and tuber presence. Logistic regression was used to calculate the odds ratio, 95% confidence interval (CI), and p-value for the association between each variable and epilepsy. A clinical risk prediction model incorporating all risk factors was built. Area under the curve (AUC) was calculated to characterize the full model’s ability to discriminate individuals with TSC with and without epilepsy. Results The strongest risk for epilepsy was presence of tubers (95% CI: 2.39-10.89). Individuals with pathogenic TSC2 variants were 3-times more likely (95% CI: 1.55-6.36) to develop seizures compared to those with TSC from other causes. The combination of risk factors resulted in an AUC of 0.73. Conclusions Simple characteristics of TSC patients can be combined to successfully predict epilepsy risk. A risk assessment model that incorporates sex, TSC genotype, protective TSC2 missense variant, and tuber presence correctly predicts epilepsy in 73% of TSC patients.