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具有较窄治疗指数药物的有吸引力的伦理学剂量发现设计。

Ethically attractive dose-finding designs for drugs with a narrow therapeutic index.

机构信息

Division of Pharmacokinetics and Drug Therapy, Department of Pharmaceutical Biosciences, Uppsala University, Box 591, SE 751 24 Uppsala, Sweden.

出版信息

J Clin Pharmacol. 2012 Jan;52(1):29-38. doi: 10.1177/0091270010390041. Epub 2011 Jan 12.

Abstract

A simulation-based comparison study on the relative merits of dose-control trials (DCTs) with exposure-response analysis versus concentration-control trials (CCTs) for drugs with narrow therapeutic index showed that DCT designs are more informative about the exposure-response relationship. The authors revisit the question employing optimal design methodology and propose strategies for designing ethically attractive trials for these drugs, balancing between individual-collective risk and informativeness. An optimal study was performed considering a hypothetical immunosuppressant agent with 2 clinical end points. Different scenarios were optimized applying cost-based designs (unwanted events vs number of subjects/trial or maximal individual risk). Dose/exposure targets and number of subjects per trial/arm were optimized. Prior information inclusion on baseline risks was evaluated. DCTs were more informative, needing smaller studies to provide the same information as CCTs. Using the number of unwanted events-rather than subjects-as cost resulted in ethically more attractive designs. Including prior baseline risk information reduced the number of subject/events and allowed the use of targets closer to the optimal. Designing dose-finding trials for some narrow therapeutic index drugs may be improved by using DCTs with exposure-response analysis, cost-based designs, prior information, and optimal design analysis providing information on the ethical trade-off between individual risk and information gain.

摘要

一项基于模拟的比较研究表明,对于治疗指数较窄的药物,与暴露反应分析相比,剂量控制试验(DCT)与浓度控制试验(CCT)在评估相对优势方面更具信息量。本文采用最优设计方法重新探讨了这个问题,并提出了设计这些药物具有伦理吸引力的试验策略,在个体-群体风险和信息量之间取得平衡。在考虑到一个具有 2 个临床终点的假设性免疫抑制剂药物的情况下,进行了最优研究。应用基于成本的设计(不良事件与受试者数量/试验或最大个体风险)对不同场景进行了优化。优化了剂量/暴露目标和每个试验/臂的受试者数量。评估了纳入基线风险的先验信息。DCT 更具信息量,需要更小的研究就能提供与 CCT 相同的信息。使用不良事件数量而不是受试者数量作为成本会导致更具伦理吸引力的设计。纳入先验基线风险信息可以减少受试者/事件的数量,并允许使用更接近最佳的目标。通过使用具有暴露反应分析、基于成本的设计、先验信息和最优设计分析的 DCT,为一些治疗指数较窄的药物设计剂量探索试验,可能会得到改善,从而在个体风险和信息增益之间的伦理权衡中提供信息。

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