已核实 DOI PubMed 相关产品: 0

LC-MS/MS method for quantification of 23 TKIs in Plasma: Assessing the relationship between anlotinib trough concentration and toxicities

Journal 2024 · IF 3.2 · 发表于 2024 年 11 月 14 日
作者: Chen Bu,Liansheng Jiang,Lili Cui,Mao Tang,Xinhua Song,Yingkui Zhao,Zhengyan Liang,Liya Ye,Jiayao Nian,Shouhong Gao,Xia Tao,Zhipeng Wang,Wansheng Chen
阅读全文 在 PubMed 查看

摘要

Objective To develop a simple, rapid, and sensitive LC-MS/MS method for quantifying 23 tyrosine kinase inhibitors (TKIs) in plasma samples, and evaluate the relationship between the trough concentration of anlotinib(ANL) and its toxicities. Methods The method was developed in Agilent 1290–6460 UHPLC-MS/MS system. This study prospectively enrolled 55 cancer patients undergoing ANL treatment. Plasma samples were collected at steady-state trough concentration and subsequently analyzed using the method. Patients were recorded for the occurrence of toxicities. Statistical analysis was performed to assess the association of the toxicities with ANL exposure level and patients’ characteristics. Results The LC-MS/MS method was developed and validated for all items required by pharmacopoeia. The results revealed a positive association between the trough concentration of ANL and the incidence of toxicities. The exposure level 17.655 ng/mL (AUC 0.82, p = 0.010) was identified as a predictive threshold value for grade ≥ 3 overall toxicities. In addition, lower platelet count (PLT count < 179 × 10 9 g/L) was significantly associated with higher occurrence of grade ≥ 3 toxicities (AUC 0.75, p = 0.049). A logistic model incorporating these two factors demonstrated improved diagnostic capacity for predicting ≥ 3 overall toxicities (AUC = 0.90, p = 0.001). Conclusion This study successfully developed and validated a simple, rapid, and sensitive LC-MS/MS method for quantifying 23 TKIs in plasma samples. Besides, this study found that both C trough of ANL and PLT count as independent predictors for ANL-induced ≥ 3 overall toxicities. Moreover, a logistic model including these two factors presents better prediction capacity for ≥ 3 overall toxicities.