Lishi Lin, Vincent van der Noort, Neeltje Steeghs, Gerrina Ruiter, Jos H Beijnen, Alwin D R Huitema
{"title":"研究暴露-反应关系的纵向药代动力学和时间-事件数据联合模型:阿来替尼的概念验证研究。","authors":"Lishi Lin, Vincent van der Noort, Neeltje Steeghs, Gerrina Ruiter, Jos H Beijnen, Alwin D R Huitema","doi":"10.1007/s00280-024-04698-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>In exposure-response analyses of oral targeted anticancer agents, longitudinal plasma trough concentrations are often aggregated into a single value even though plasma trough concentrations can vary over time due to dose adaptations, for example. The aim of this study was to compare joint models to conventional exposure-response analyses methods with the application of alectinib as proof-of-concept.</p><p><strong>Methods: </strong>Joint models combine longitudinal pharmacokinetic data and progression-free survival data to infer the dependency and association between the two datatypes. The results from the best joint model and the standard and time-dependent cox proportional hazards models were compared. To normalize the data, alectinib trough concentrations were normalized using a sigmoidal transformation to transformed trough concentrations (TTC) before entering the models.</p><p><strong>Results: </strong>No statistically significant exposure-response relationship was observed in the different Cox models. In contrast, the joint model with the current value of TTC in combination with the average TTC over time did show an exposure-response relationship for alectinib. A one unit increase in the average TTC corresponded to an 11% reduction in progression (HR, 0.891; 95% confidence interval, 0.805-0.988).</p><p><strong>Conclusion: </strong>Joint models are able to give insights in the association structure between plasma trough concentrations and survival outcomes that would otherwise not be possible using Cox models. Therefore, joint models should be used more often in exposure-response analyses of oral targeted anticancer agents.</p>","PeriodicalId":9556,"journal":{"name":"Cancer Chemotherapy and Pharmacology","volume":" ","pages":"453-459"},"PeriodicalIF":2.7000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11420381/pdf/","citationCount":"0","resultStr":"{\"title\":\"A joint model of longitudinal pharmacokinetic and time-to-event data to study exposure-response relationships: a proof-of-concept study with alectinib.\",\"authors\":\"Lishi Lin, Vincent van der Noort, Neeltje Steeghs, Gerrina Ruiter, Jos H Beijnen, Alwin D R Huitema\",\"doi\":\"10.1007/s00280-024-04698-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>In exposure-response analyses of oral targeted anticancer agents, longitudinal plasma trough concentrations are often aggregated into a single value even though plasma trough concentrations can vary over time due to dose adaptations, for example. The aim of this study was to compare joint models to conventional exposure-response analyses methods with the application of alectinib as proof-of-concept.</p><p><strong>Methods: </strong>Joint models combine longitudinal pharmacokinetic data and progression-free survival data to infer the dependency and association between the two datatypes. The results from the best joint model and the standard and time-dependent cox proportional hazards models were compared. To normalize the data, alectinib trough concentrations were normalized using a sigmoidal transformation to transformed trough concentrations (TTC) before entering the models.</p><p><strong>Results: </strong>No statistically significant exposure-response relationship was observed in the different Cox models. In contrast, the joint model with the current value of TTC in combination with the average TTC over time did show an exposure-response relationship for alectinib. A one unit increase in the average TTC corresponded to an 11% reduction in progression (HR, 0.891; 95% confidence interval, 0.805-0.988).</p><p><strong>Conclusion: </strong>Joint models are able to give insights in the association structure between plasma trough concentrations and survival outcomes that would otherwise not be possible using Cox models. Therefore, joint models should be used more often in exposure-response analyses of oral targeted anticancer agents.</p>\",\"PeriodicalId\":9556,\"journal\":{\"name\":\"Cancer Chemotherapy and Pharmacology\",\"volume\":\" \",\"pages\":\"453-459\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11420381/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Chemotherapy and Pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00280-024-04698-w\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Chemotherapy and Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00280-024-04698-w","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/11 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
A joint model of longitudinal pharmacokinetic and time-to-event data to study exposure-response relationships: a proof-of-concept study with alectinib.
Purpose: In exposure-response analyses of oral targeted anticancer agents, longitudinal plasma trough concentrations are often aggregated into a single value even though plasma trough concentrations can vary over time due to dose adaptations, for example. The aim of this study was to compare joint models to conventional exposure-response analyses methods with the application of alectinib as proof-of-concept.
Methods: Joint models combine longitudinal pharmacokinetic data and progression-free survival data to infer the dependency and association between the two datatypes. The results from the best joint model and the standard and time-dependent cox proportional hazards models were compared. To normalize the data, alectinib trough concentrations were normalized using a sigmoidal transformation to transformed trough concentrations (TTC) before entering the models.
Results: No statistically significant exposure-response relationship was observed in the different Cox models. In contrast, the joint model with the current value of TTC in combination with the average TTC over time did show an exposure-response relationship for alectinib. A one unit increase in the average TTC corresponded to an 11% reduction in progression (HR, 0.891; 95% confidence interval, 0.805-0.988).
Conclusion: Joint models are able to give insights in the association structure between plasma trough concentrations and survival outcomes that would otherwise not be possible using Cox models. Therefore, joint models should be used more often in exposure-response analyses of oral targeted anticancer agents.
期刊介绍:
Addressing a wide range of pharmacologic and oncologic concerns on both experimental and clinical levels, Cancer Chemotherapy and Pharmacology is an eminent journal in the field. The primary focus in this rapid publication medium is on new anticancer agents, their experimental screening, preclinical toxicology and pharmacology, single and combined drug administration modalities, and clinical phase I, II and III trials. It is essential reading for pharmacologists and oncologists giving results recorded in the following areas: clinical toxicology, pharmacokinetics, pharmacodynamics, drug interactions, and indications for chemotherapy in cancer treatment strategy.