Department of Pharmacy, Uppsala University, Box 580, 75123, Uppsala, Sweden.
Pharm Res. 2021 Apr;38(4):593-605. doi: 10.1007/s11095-021-03024-w. Epub 2021 Mar 17.
Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity.
Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CL: -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m (-30%)). Study power was assessed given diverse scenarios (n = 50-400 patients/arm, parallel/crossover, varying magnitude of CL, exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing.
The magnitude of CL reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (<0.5·10 cells/L) after PGx-based versus standard dosing. To achieve >80% power with traditional statistical analysis (χ/McNemar's test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (n = 100/15 given parallel/crossover design) to obtain the same statistical power.
The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies.
药代动力学模型为辅助临床试验的合理设计提供了有用的工具。本研究评估了研究设计、药物和患者相关特征以及分析方法对基于药物基因组学(PGx)剂量的骨髓毒性获益的验证能力的影响。
组装了两个药代动力学模型和一个骨髓抑制模型,以预测不同 UGT1A1 基因型(弱代谢者:CL:-36%)和传统剂量与基于 PGx 剂量(350 与 245 mg/m 2 (-30%))下的伊立替康及其代谢物 SN-38 的浓度。考虑了不同的方案(每组 50-400 名患者,平行/交叉,CL 变化幅度,暴露-反应关系,个体间变异性),并使用基于模型的数据分析与传统统计检验评估了研究的效能。
弱代谢者 CL 降低的幅度和 SN-38 的骨髓抑制效力对基于 PGx 剂量与标准剂量相比发生 4 级中性粒细胞减少(<0.5·10 个细胞/L)的差异显示能力有显著影响。为了达到传统统计学分析(χ/McNemar 检验,α=0.05)>80%的效能,每个治疗组/序列(平行/交叉研究)需要 220/100 名患者。基于模型的分析导致总样本量显著减少(n=100/15,平行/交叉设计),以获得相同的统计学效能。
本研究结果有助于避免不可行的试验,并合理化药物基因组学研究的设计。