The School of Medicine, The University of Notre Dame Australia, Sydney, NSW, Australia.
Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, NSW, Australia.
Br J Clin Pharmacol. 2021 Mar;87(3):1422-1431. doi: 10.1111/bcp.14542. Epub 2020 Sep 21.
Bayesian forecasting software can assist in guiding therapeutic drug monitoring (TDM)-based dose adjustments for amikacin to achieve therapeutic targets. This study aimed to evaluate amikacin prescribing and TDM practices, and to determine the suitability of the amikacin model incorporated into the DoseMeRx® software as a replacement for the previously available software (Abbottbase®).
Patient demographics, pathology, amikacin dosing history, amikacin concentrations and Abbottbase® predicted TDM targets (area under the curve up to 24 hours, maximum concentration and trough concentration) were collected for adults receiving intravenous amikacin (2012-2017). Concordance with the Australian Therapeutic Guidelines was assessed. Observed and predicted amikacin concentrations were compared to determine the predictive performance (bias and precision) of DoseMeRx®. Amikacin TDM targets were predicted by DoseMeRx® and compared to those predicted by Abbottbase®.
Overall, guideline compliance for 63 courses of amikacin in 47 patients was suboptimal. Doses were often lower than recommended. For therapy >48 h, TDM sample collection timing was commonly discordant with recommendations, therapeutic target attainment low and 34% of dose adjustments inappropriate. DoseMeRx® under-predicted amikacin concentrations by 0.9 mg/L (95% confidence interval [CI] -1.4 to -0.5) compared with observed concentrations. However, maximum concentration values (n = 19) were unbiased (-1.7 mg/L 95%CI -5.8 to 0.8) and precise (8.6% 95%CI 5.4-18.1). Predicted trough concentration values (n = 7) were, at most, 1 mg/L higher than observed. Amikacin area under the curve values estimated using Abbottbase® (181 mg h/L 95%CI 161-202) and DoseMeRx® (176 mg h/L 95%CI 152-199) were similar (P = .59).
Amikacin dosing and TDM practice was suboptimal compared with guidelines. The model implemented by DoseMeRx® is satisfactory to guide amikacin dosing.
贝叶斯预测软件可协助指导阿米卡星的治疗药物监测（TDM）剂量调整，以实现治疗目标。本研究旨在评估阿米卡星的处方和 TDM 实践，并确定纳入 DoseMeRx®软件的阿米卡星模型作为替代先前可用软件（Abbottbase®）的适用性。
收集接受静脉内阿米卡星治疗的成人患者的人口统计学、病理学、阿米卡星剂量史、阿米卡星浓度和 Abbottbase®预测的 TDM 目标（24 小时内的 AUC、最大浓度和谷浓度）（2012-2017 年）。评估与澳大利亚治疗指南的一致性。比较观察到的和预测的阿米卡星浓度，以确定 DoseMeRx®的预测性能（偏差和精度）。通过 DoseMeRx®预测阿米卡星 TDM 目标，并与 Abbottbase®预测的目标进行比较。
总体而言，47 例患者 63 个疗程的指南遵循情况并不理想。剂量通常低于推荐剂量。对于治疗时间>48 小时，TDM 样本采集时间通常与建议不一致，治疗目标达成率低，34%的剂量调整不适当。与观察到的浓度相比，DoseMeRx®低估了 0.9mg/L（95%置信区间 [CI] -1.4 至 -0.5）的阿米卡星浓度。然而，最大浓度值（n=19）无偏差（-1.7mg/L 95%CI -5.8 至 0.8）且精确（8.6%95%CI 5.4-18.1）。预测的谷浓度值（n=7）最多比观察到的值高 1mg/L。使用 Abbottbase®（181mg h/L 95%CI 161-202）和 DoseMeRx®（176mg h/L 95%CI 152-199）估计的阿米卡星 AUC 值相似（P=0.59）。
与指南相比，阿米卡星的给药和 TDM 实践并不理想。DoseMeRx®实施的模型足以指导阿米卡星的给药。
