School of Pharmacy, University of Otago, Dunedin, New Zealand.
Br J Clin Pharmacol. 2022 Jul;88(7):3474-3482. doi: 10.1111/bcp.15307. Epub 2022 Mar 24.
Dose banding is a method of dose individualisation in which all patients with similar characteristics are allocated to the same dose. Dose banding results in some patients receiving less intensive treatment which risks a reduction in therapeutic benefit (iatrogenic therapeutic failure) because of variability not predicted by dose banding. This study aims to explore the effects of dose banding on therapeutic success and failure.
This was a simulation study. Virtual patients were simulated under a simple pharmacokinetic model where the response of interest is the steady-state average concentration. Clearance was correlated with a covariate used for dose banding. Dose individualisation was based on: one-dose-fits-all, covariate-based dosing, empirical dose banding, dose banding optimised for net therapeutic benefit and optimised for both benefit and minimising iatrogenic therapeutic failure.
The lowest and highest probability of target attainment (PTA) were 44% for one-dose-fits-all and 72% for covariate-based dosing. Neither dosing approach would result in iatrogenic therapeutic failure as lower dose intensities do not occur. Empirical dose banding performed better than one-dose-fits-all with 59% PTA but not as good as either optimised method (64-69% PTA) while carrying a risk of iatrogenic therapeutic failure in 25% of patients. Optimising for benefit (only) improved PTA but carried a risk of iatrogenic therapeutic failure of up to 10%. Optimising for benefit and minimising iatrogenic therapeutic failure provided the best balance.
Future application of dose banding needs to consider both the probability of benefit as well the risk of causing iatrogenic therapeutic failure.
剂量分组是一种剂量个体化方法，其中所有具有相似特征的患者都被分配到相同的剂量。剂量分组导致一些患者接受较少的强化治疗，这可能会降低治疗效果（医源性治疗失败），因为剂量分组无法预测的变异性。本研究旨在探讨剂量分组对治疗成功和失败的影响。
这是一项模拟研究。在简单的药代动力学模型下模拟虚拟患者，其中感兴趣的反应是稳态平均浓度。清除率与用于剂量分组的协变量相关。剂量个体化基于：一刀切、基于协变量的给药、经验剂量分组、为净治疗效益优化的剂量分组和为效益和最小化医源性治疗失败优化的剂量分组。
一刀切的最低和最高目标浓度（PTA）概率分别为 44%和基于协变量的给药的 72%。这两种给药方法都不会导致医源性治疗失败，因为不会出现较低的剂量强度。经验剂量分组的 PTA 优于一刀切，为 59%，但不如任何优化方法（64-69% PTA），同时在 25%的患者中存在医源性治疗失败的风险。仅优化效益提高了 PTA，但存在高达 10%的医源性治疗失败风险。优化效益和最小化医源性治疗失败提供了最佳平衡。
未来剂量分组的应用需要考虑到获益的可能性以及引起医源性治疗失败的风险。
