癫痫患儿唑尼沙胺血药浓度不达标风险预测模型的建立与验证 点击下载
| 论文标题： | 癫痫患儿唑尼沙胺血药浓度不达标风险预测模型的建立与验证 |
| 英文标题： | |
| 中文摘要： | 目的 构建癫痫患儿唑尼沙胺血药浓度不达标的风险预测模型，为个体化给药提供依据。方法回顾性选取昆明市儿童医院接受口服唑尼沙胺规范治疗的癫痫患儿为研究对象，其中2022年5月至2024年5月接受治疗的患儿纳入建模队列，2024年6月至2025年1月接受治疗的患儿纳入外部验证队列。根据血药浓度将患儿分为达标组和未达标组。通过共线性诊断、单因素分析、Lasso回归和随机森林筛选唑尼沙胺血药浓度不达标的独立影响因素，据此构建列线图风险预测模型，并进行验证。最后，应用沙普利加性解释（SHAP）法对列线图风险预测模型特征进行解释。结果本研究共纳入945例癫痫患儿，建模队列（531例）与外部验证队列（414例）患儿基线资料差异无统计学意义（P＞0.05），具有可比性。通过多阶段特征筛选，最终纳入性别、年龄、给药剂量、天冬氨酸氨基转移酶、总胆红素、尿酸、维生素D7个影响因素构建预测模型。该模型建模队列的校正曲线下面积为0.799，外部验证队列的校正曲线下面积为0.762，校准度和临床适用性良好。SHAP法分析显示，性别、给药剂量、总胆红素、年龄和天冬氨酸氨基转移酶为影响模型预测的前5个重要变量。结论本研究构建的唑尼沙胺血药浓度不达标的列线图风险预测模型具有稳定的预测效能，临床可结合患儿的性别、年龄、给药剂量、肝肾功能、维生素D，快速评估唑尼沙胺血药浓度不达标的风险，并及时调整给药方案。 |
| 英文摘要： | OBJECTIVE To construct a risk prediction model for nonattainment plasma concentration of zonisamide in children with epilepsy， and to provide evidence for individualized dosing.METHODS Children with epilepsy who received standardized zonisamide treatment orally in Kunming Children’s Hospital were retrospectively selected as research subjects. Those treated from May 2022 to May 2024 were included in the modeling cohort， and those treated from June 2024 to January 2025 were included in the external validation cohort. According to plasma concentration， children were divided into therapeutic group and nonattainment group. Independent influencing factors for nonattainment plasma concentration of zonisamide were screened by collinearity diagnosis， univariate analysis， Lasso regression and random forest， based on which a nomogram risk prediction model was constructed and validated. Finally， the Shapley additive explanations （SHAP） method was used to interpret the features of the nomogram risk prediction model.RESULTS A total of 945 children with epilepsy were included in this study. There was no statistically significant difference in baseline data between the modeling cohort （531 cases） and the external validation cohort （414 cases） （ P ＞0.05）， indicating comparability. Through multi-stage feature screening， seven influencing factors were finally included to construct the prediction model， namely gender， age， dosage， aspartate transferase， total bilirubin， uric acid and vitamin D. The corrected area under the curve of the model was 0.799 in the modeling cohort and 0.762 in the external validation cohort， showing good calibration and clinical applicability. SHAP analysis showed that gender， dosage， total bilirubin， age and aspartate transferase were the top five important variables affecting model prediction.CONCLUSIONS The nomogram risk prediction model for nonattainment plasma concentration of zonisamide constructed in this study has stable predictive performance. Clinically， the risk of nonattainment plasma concentration can be quickly assessed by combining the child’s gender， age， dosage， liver and kidney function， and vitamin D， and the dosing regimen can be adjusted in time. |
| 期刊： | 2026年第37卷第16期 |
| 作者： | 李惠英；张艳；李发双；黎林波；张力麟；任丹阳；涂彩霞；徐润东 |
| 英文作者： | LI Huiying，ZHANG Yan，LI Fashuang，LI Linbo，ZHANG Lilin，REN Danyang，TU Caixia，XU Rundong |
| 关键字： | 唑尼沙胺；癫痫；儿童；血药浓度；列线图风险预测模型；影响因素 |
| KEYWORDS： | zonisamide;Epilepsy;Children;Plasma concentration;nomogram risk prediction model;Influencing factors |
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