Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Br J Clin Pharmacol. 2013 Oct;76(4):603-15. doi: 10.1111/bcp.12121.
Ciclosporin A (CsA) dosing in immunosuppression after paediatric kidney transplantation remains challenging, and appropriate target CsA exposures (AUCs) are controversial. This study aimed to develop a time-to-first-acute rejection (AR) model and to explore predictive factors for therapy outcome.
Patient records at the Children's Hospital in Helsinki, Finland, were analysed. A parametric survival model in NONMEM was used to describe the time to first AR. The influences of AUC and other covariates were explored using stepwise covariate modelling, bootstrap-stepwise covariate modelling and cross-validated stepwise covariate modelling. The clinical relevance of the effects was assessed with the time at which 90% of the patients were AR free (t90).
Data from 87 patients (0.7-19.8 years old, 54 experiencing an AR) were analysed. The baseline hazard was described with a function changing in steps over time. No statistically significant covariate effects were identified, a finding substantiated by all methods used. Thus, within the observed AUC range (90% interval 1.13-8.40 h mg l⁻¹), a rise in AUC was not found to increase protection from AR. Dialysis time, sex and baseline weight were potential covariates, but the predicted clinical relevance of their effects was low. For the strongest covariate, dialysis time, median t90 was 5.8 days (90% confidence interval 5.1-6.8) for long dialysis times (90th percentile) and 7.4 days (6.4-11.7) for short dialysis times (10th percentile).
A survival model with discrete time-varying hazards described the data. Within the observed range, AUC was not identified as a covariate. This feedback on clinical practice may help to avoid unnecessarily high CsA dosing in children.
小儿肾移植后免疫抑制中环孢素 A(CsA)的剂量仍然具有挑战性,合适的目标 CsA 暴露量(AUC)存在争议。本研究旨在建立首次急性排斥(AR)的时间模型,并探讨治疗结果的预测因素。
对芬兰赫尔辛基儿童医院的患者记录进行分析。NONMEM 中的参数生存模型用于描述首次 AR 的时间。使用逐步协变量建模、Bootstrap 逐步协变量建模和交叉验证逐步协变量建模来探索 AUC 和其他协变量的影响。使用 90%的患者无 AR 的时间(t90)评估效应的临床相关性。
分析了 87 例患者(0.7-19.8 岁,54 例发生 AR)的数据。基础风险由随时间变化的阶跃函数描述。未发现具有统计学意义的协变量效应,所有使用的方法均证实了这一发现。因此,在所观察到的 AUC 范围内(90%区间为 1.13-8.40 h·mg·l⁻¹),AUC 的升高并未发现可增加对 AR 的保护作用。透析时间、性别和基线体重是潜在的协变量,但它们的影响预测临床相关性较低。对于最强的协变量透析时间,长透析时间(第 90 百分位数)的中位 t90 为 5.8 天(90%置信区间为 5.1-6.8),短透析时间(第 10 百分位数)为 7.4 天(6.4-11.7)。
使用具有离散时变风险的生存模型描述了数据。在观察到的范围内,AUC 未被确定为协变量。这一反馈可能有助于避免儿童不必要地高剂量 CsA 治疗。