Background

Individuals with tuberous sclerosis complex 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 evaluate the combined risk prediction of previously identified risk factors for epilepsy in individuals with tuberous sclerosis complex.

Methods

The study group (n = 333) consisted of individuals with tuberous sclerosis complex who were enrolled in the Tuberous Sclerosis Complex 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 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 was calculated to characterize the full model's ability to discriminate individuals with tuberous sclerosis complex with and without epilepsy.

Results

The strongest risk for epilepsy was presence of tubers (95% confidence interval: 2.39 to 10.89). Individuals with pathogenic TSC2 variants were three times more likely (95% confidence interval: 1.55 to 6.36) to develop seizures compared with those with tuberous sclerosis complex from other causes. The combination of risk factors resulted in an area under the curve 0.73.

Conclusions

Simple characteristics of patients with tuberous sclerosis complex 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 patients with tuberous sclerosis complex.

中文翻译：

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结节性硬化症患者的癫痫风险预测模型

背景

患有结节性硬化症的人患癫痫的风险增加。早期癫痫控制可以改善发育结果，因此识别高危患者至关重要。尽管有几个已确定的风险因素，但仍然难以预测。该研究的目的是评估先前确定的结节性硬化症患者癫痫危险因素的综合风险预测。

方法

研究小组 (n = 333) 由结节性硬化症患者组成，他们加入了结节性硬化症自闭症卓越研究中心网络和 UT TSC 生物库。结果被定义为癫痫诊断。潜在的危险因素包括性别、TSC基因型和块茎存在。使用逻辑回归来计算每个变量与癫痫之间关联的比值比和P值。建立了包含所有风险因素的临床风险预测模型。计算曲线下面积来表征完整模型区分患有或不患有癫痫的结节性硬化症患者的能力。

结果

癫痫的最大风险是块茎的存在（95% 置信区间：2.39 至 10.89）。与其他原因导致的结节性硬化症患者相比，具有致病性TSC2变异的个体发生癫痫发作的可能性是其三倍（95% 置信区间：1.55 至 6.36）。风险因素的组合导致曲线下面积为 0.73。

结论

结节性硬化症患者的简单特征可以结合起来成功预测癫痫风险。结合了性别、TSC 基因型、保护性TSC2错义变异和结节存在的风险评估模型可以正确预测 73% 的结节性硬化症患者是否患有癫痫。