他克莫司在儿童肾病中的风险预测模型的建立

doi:10.19803/j.1672-8629.2021.06.18

摘要/Abstract

摘要： 目的探究儿童肾病综合征患者中影响他克莫司血药浓度的因素并建立风险预测模型。方法回顾性地收集2017年1月-2019年10月期间确诊为肾病综合征并符合纳入/排除标准的90例儿童信息,包括：人口学信息、实验室检测指标、合并用药以及他克莫司稳态谷浓度及剂量。通过单因素分析筛查影响他克莫司浓度低暴露和高暴露的因素;再通过多因素Logistic回归法建立风险预测模型。结果单因素分析结果显示：剂量、合并阿奇霉素和红细胞容积是影响TAC稳态谷浓度低暴露和高暴露的显著因素（P<0.05）。多因素Logistic回归法建立的低暴露风险模型为Logit（P）=2.521-1.419（剂量）-2.401（合用阿奇霉素）+0.964（血清胱抑素C）-1.936红细胞容积（<35%）,经评估该模型的准确度、特异度及灵敏度较好。结论在儿童肾病综合征患者中应考虑剂量、合并阿奇霉素和红细胞容积对他克莫司稳态谷浓度的影响作用;并可通过低暴露风险模型预先判断肾病综合征患儿发生低暴露的概率;为避免他克莫司不良反应的发生和提高治疗效果提供帮助。

关键词: 儿童, 肾病综合征, 他克莫司, 血药浓度, 影响因素

Abstract: Objective To explore the factors that affecting the blood concentration of tacrolimus in children with nephrotic syndrome and to establish a risk prediction model. Methods Information was collected retrospectively on 90 children diagnosed with NS and meeting inclusion/exclusion criteria from January 2017 to October 2019, including demographic information, laboratory test indicators, combined medication, and tacrolimus steady-state trough concentration and dose. Univariate analysis was used to screen for factors affecting low and high exposure to tacrolimus concentration, Then a risk prediction model was established by multivariate Logistic regression method. Results Univariate analysis result showed that dose, azithromycin and red blood cell volume were the significant factors affecting low and high exposures of tacrolimus steady-state trough concentration (P<0.05). The low exposure risk model established by multivariate Logistic regression was Logit(P)=2.521-1.419(dose)-2.401(with azithromycin)+0.964(serum cystatin C)-1.93 6 erythrocyte volume (<35%) and with a better accuracy, specificity and sensitivity. Conclusion In children with nephrotic syndrome, the effects of dose, combined azithromycin and erythrocyte volume on tacrolimus steady-state trough concentration should be considered. The low exposure risk model can be used to predict the probability of low blood concentration exposure in children to avoid the occurrence of tacrolimus adverse reactions and improve the therapeutic effect.

Key words: children, tacrolimus, nephrotic syndrome, blood concentration, influenceing factors, adverse drug reaction

中图分类号:

R979.5R969

朱丽丽, 耿伟, 袁圆, 安晓婕, 袁双丽, 郦昱琨, 陈渤松, 赵军. 他克莫司在儿童肾病中的风险预测模型的建立[J]. 中国药物警戒, 2021, 18(6): 579-583.

ZHU Lili, GENG Wei, YUAN Yuan, AN Xiaojie, YUAN Shuangli, LI Yukun, CHEN Bosong, ZHAO Jun. A Risk Prediction Model for Tacrolimus in Children with Nephrotic Syndrome[J]. Chinese Journal of Pharmacovigilance, 2021, 18(6): 579-583.

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