LAP&P Consultants BV, Leiden, The Netherlands.
Takeda Development Centre Europe Ltd, London, UK.
Br J Clin Pharmacol. 2019 Jun;85(6):1247-1259. doi: 10.1111/bcp.13891. Epub 2019 Apr 3.
This investigation aimed to quantitatively characterize the relationship between the gonadotropin-releasing hormone agonist leuprorelin, testosterone (T) and prostate specific antigen (PSA) concentrations over time, to aid identification of a target T concentration that optimises the balance of the benefits of T suppression whilst reducing the risk of side effects related to futile over-suppression.
Data from a single dose study to investigate the effect of leuprorelin in a 6-month depot formulation on T and PSA in prostate cancer patients were analysed using a population pharmacokinetic-pharmacodynamic modelling approach. The developed model was qualified using external data from 3 studies, in which the effect of different formulations of leuprorelin on T and PSA was evaluated in prostate cancer patients.
The effect of leuprorelin on the relationship between T and PSA was adequately characterized by the Romero model with minor modifications, combined with a turnover model to describe the delay in response between T and PSA. The data were significantly better described when assuming a minimum PSA level that is independent on the treatment-related reduction in T, as compared to a model with a proportional reduction in PSA and T.
The model-based analysis suggests that on a population level, reducing T concentrations below 35 ng/dL does not result in a further decrease in PSA levels (>95% of the minimal PSA level is reached). More data are required to support this relationship in the lower T and PSA range.
本研究旨在定量描述促性腺激素释放激素激动剂亮丙瑞林、睾酮(T)和前列腺特异性抗原(PSA)浓度随时间的变化关系,以帮助确定一个目标 T 浓度,该浓度既能优化 T 抑制的获益平衡,又能降低与无效过度抑制相关的副作用风险。
使用群体药代动力学-药效学建模方法,对一项旨在研究 6 个月长效制剂亮丙瑞林对前列腺癌患者 T 和 PSA 影响的单剂量研究数据进行分析。通过 3 项研究的外部数据对开发的模型进行了验证,这些研究评估了不同制剂的亮丙瑞林对前列腺癌患者 T 和 PSA 的影响。
对亮丙瑞林对 T 和 PSA 之间关系的影响进行了适当的描述,采用了 Romero 模型,并进行了一些修改,结合了一个转换模型来描述 T 和 PSA 之间反应的延迟。与假设 PSA 和 T 呈比例下降的模型相比,当假设 PSA 水平存在一个与 T 下降无关的最小值时,数据得到了更好的描述。
基于模型的分析表明,在人群水平上,将 T 浓度降低至 35ng/dL 以下不会导致 PSA 水平进一步下降(达到 PSA 最低水平的>95%)。需要更多的数据来支持在较低的 T 和 PSA 范围内的这种关系。