当前位置: X-MOL 学术Biometrics › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Bayesian dose regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics
Biometrics ( IF 1.9 ) Pub Date : 2021-02-02 , DOI: 10.1111/biom.13433
Emma Gerard 1, 2, 3 , Sarah Zohar 1 , Hoai-Thu Thai 4 , Christelle Lorenzato 2 , Marie-Karelle Riviere 3 , Moreno Ursino 1, 5
Affiliation  

Phase I dose-finding trials in oncology seek to find the maximum tolerated dose of a drug under a specific schedule. Evaluating drug schedules aims at improving treatment safety while maintaining efficacy. However, while we can reasonably assume that toxicity increases with the dose for cytotoxic drugs, the relationship between toxicity and multiple schedules remains elusive. We proposed a Bayesian dose regimen assessment method (DRtox) using pharmacokinetics/pharmacodynamics (PK/PD) to estimate the maximum tolerated dose regimen (MTD-regimen) at the end of the dose-escalation stage of a trial. We modeled the binary toxicity via a PD endpoint and estimated the dose regimen toxicity relationship through the integration of a dose regimen PD model and a PD toxicity model. For the first model, we considered nonlinear mixed-effects models, and for the second one, we proposed the following two Bayesian approaches: a logistic model and a hierarchical model. In an extensive simulation study, the DRtox outperformed traditional designs in terms of proportion of correctly selecting the MTD-regimen. Moreover, the inclusion of PK/PD information helped provide more precise estimates for the entire dose regimen toxicity curve; therefore the DRtox may recommend alternative untested regimens for expansion cohorts. The DRtox was developed to be applied at the end of the dose-escalation stage of an ongoing trial for patients with relapsed or refractory acute myeloid leukemia (NCT03594955) once all toxicity and PK/PD data are collected.

中文翻译:

结合药代动力学和药效学的早期肿瘤学贝叶斯剂量方案评估

肿瘤学中的 I 期剂量寻找试验旨在找到特定时间表下药物的最大耐受剂量。评估药物时间表旨在提高治疗安全性,同时保持疗效。然而,虽然我们可以合理地假设毒性随着细胞毒性药物剂量的增加而增加,但毒性与多种方案之间的关系仍然难以捉摸。我们提出了一种贝叶斯剂量方案评估方法 (DRtox),使用药代动力学/药效学 (PK/PD) 来估计试验剂量递增阶段结束时的最大耐受剂量方案 (MTD 方案)。我们通过 PD 终点对二元毒性进行建模,并通过剂量方案 PD 模型和 PD 毒性模型的整合来估计剂量方案毒性关系。对于第一个模型,我们考虑了非线性混合效应模型,对于第二种方法,我们提出了以下两种贝叶斯方法:逻辑模型和层次模型。在一项广泛的模拟研究中,DRtox 在正确选择 MTD 方案的比例方面优于传统设计。此外,包含 PK/PD 信息有助于为整个剂量方案毒性曲线提供更精确的估计;因此,DRtox 可能会为扩展队列推荐替代的未经测试的方案。一旦收集了所有毒性和 PK/PD 数据,DRtox 被开发用于在正在进行的针对复发或难治性急性髓性白血病 (NCT03594955) 患者的试验的剂量递增阶段结束时应用。DRtox 在正确选择 MTD 方案的比例方面优于传统设计。此外,包含 PK/PD 信息有助于为整个剂量方案毒性曲线提供更精确的估计;因此,DRtox 可能会为扩展队列推荐替代的未经测试的方案。一旦收集了所有毒性和 PK/PD 数据,DRtox 被开发用于在正在进行的针对复发或难治性急性髓性白血病 (NCT03594955) 患者的试验的剂量递增阶段结束时应用。DRtox 在正确选择 MTD 方案的比例方面优于传统设计。此外,包含 PK/PD 信息有助于为整个剂量方案毒性曲线提供更精确的估计;因此,DRtox 可能会为扩展队列推荐替代的未经测试的方案。一旦收集了所有毒性和 PK/PD 数据,DRtox 被开发用于在正在进行的针对复发或难治性急性髓性白血病 (NCT03594955) 患者的试验的剂量递增阶段结束时应用。
更新日期:2021-02-02
down
wechat
bug