Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
Department of Orthopedics, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
Cancer Chemother Pharmacol. 2024 Nov;94(5):733-745. doi: 10.1007/s00280-024-04708-x. Epub 2024 Aug 24.
Osteosarcoma is a rare tumor with an incidence of 4.4 cases per million per year in adolescent. High-dose methotrexate (HD-MTX) is the standard first-line chemotherapeutic agent for osteosarcoma. However, its efficacy can vary significantly among individuals due to wide pharmacokinetic variability. Despite this, only a few population pharmacokinetics (popPK) models based on Chinese patients with osteosarcoma have been reported. Thus, this study aimed to develop a HD-MTX popPK model and an individual model-based dose optimizer for osteosarcoma therapy.
A total of 680 MTX serum concentrations from 57 patients with osteosarcoma were measured at the end of MTX infusion and 10 h, 24 h, 48 h, and 72 h after the start of infusion. Using the first-order conditional estimation method with NONMEM, a popPK model was estimated. Goodness-of-fit plots, visual predictive checks, and bootstrap analysis were generated to evaluate the final model. A dose optimizer tool was developed based on the validated models using R Shiny. Additionally, clinical data from 12 patients with newly diagnosed osteosarcoma were collected and used as the validation set to preliminarily verify the predictive ability of the popPK model and the dose optimizer tool.
Body surface area (BSA) was the most significant covariate for compartment distribution. Creatinine clearance (CrCL) and co-administration of NSAIDs were introduced as predictors for central compartmental and peripheral compartmental clearance, respectively. Co-administration of NSAIDs was associated with significantly higher MTX concentrations at 72 h (p = 0.019). The dose optimizer tool exhibited a high consistency in predicting MTX AUC compared to the actual AUC (r = 0.821, p < 0.001) in the validation set.
The dose optimizer tool could be used to estimate individual PK parameters, and optimize personalized MTX therapy in particular patients.
骨肉瘤是一种罕见的肿瘤，每年每百万人口中有 4.4 例。大剂量甲氨蝶呤（HD-MTX）是骨肉瘤的标准一线化疗药物。然而，由于其药代动力学的广泛变异性，其疗效在个体之间可能有很大差异。尽管如此，仅报道了少数基于中国骨肉瘤患者的群体药代动力学（popPK）模型。因此，本研究旨在建立一个用于骨肉瘤治疗的 HD-MTX popPK 模型和一个基于个体模型的剂量优化器。
共测量了 57 例骨肉瘤患者的 680 个 MTX 血清浓度，在 MTX 输注结束时以及输注开始后 10、24、48 和 72 小时测量。使用 NONMEM 的一阶条件估计法估计 popPK 模型。生成拟合度图、可视化预测检查和 Bootstrap 分析来评估最终模型。使用 R Shiny 基于验证模型开发了一个剂量优化器工具。此外，还收集了 12 例新诊断为骨肉瘤患者的临床数据作为验证集，初步验证了 popPK 模型和剂量优化器工具的预测能力。
体表面积（BSA）是分布容积的最显著协变量。肌酐清除率（CrCL）和 NSAIDs 的联合用药分别被引入为中央室和外周室清除率的预测因子。NSAIDs 的联合用药与 72 小时时 MTX 浓度显著升高有关（p = 0.019）。在验证集中，与实际 AUC 相比，剂量优化器工具在预测 MTX AUC 方面表现出高度一致性（r = 0.821，p < 0.001）。
剂量优化器工具可用于估计个体 PK 参数，并优化特定患者的个性化 MTX 治疗。
