Towards Efficient Time-to-Event Dose-Escalation Guidance of Multi-Cycle Cancer Therapies.

IF 1.8 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Lukas A Widmer, Sebastian Weber, Yunnan Xu, Hans-Jochen Weber
{"title":"Towards Efficient Time-to-Event Dose-Escalation Guidance of Multi-Cycle Cancer Therapies.","authors":"Lukas A Widmer, Sebastian Weber, Yunnan Xu, Hans-Jochen Weber","doi":"10.1002/sim.70229","DOIUrl":null,"url":null,"abstract":"<p><p>Treatment of cancer has rapidly evolved over time in quite dramatic ways, for example, from chemotherapies, targeted therapies to immunotherapies and chimeric antigen receptor T-cells. Nonetheless, the basic design of early phase I trials in oncology still follows predominantly a dose-escalation design. These trials monitor safety over the first treatment cycle to escalate the dose of the investigated drug. However, over time, studying additional factors such as drug combinations and/or variation in the timing of dosing became important as well. Existing designs were continuously enhanced and expanded to account for increased trial complexity. With toxicities occurring at later stages beyond the first cycle and the need to treat patients over multiple cycles, the focus on the first treatment cycle only is becoming a limitation in nowadays multi-cycle treatment therapies. Here, we introduce a multi-cycle time-to-event model (TITE-CLRM: Time-Interval-To-Event Complementary-Loglog Regression Model), allowing guidance of dose-escalation trials studying multi-cycle therapies. The challenge lies in balancing the need to monitor the safety of longer treatment periods with the need to continuously enroll patients safely. The proposed multi-cycle time-to-event model is formulated as an extension to established concepts like the escalation with overdose control principle. The model is motivated by a current drug development project and evaluated in a simulation study.</p>","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"44 20-22","pages":"e70229"},"PeriodicalIF":1.8000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics in Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/sim.70229","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Treatment of cancer has rapidly evolved over time in quite dramatic ways, for example, from chemotherapies, targeted therapies to immunotherapies and chimeric antigen receptor T-cells. Nonetheless, the basic design of early phase I trials in oncology still follows predominantly a dose-escalation design. These trials monitor safety over the first treatment cycle to escalate the dose of the investigated drug. However, over time, studying additional factors such as drug combinations and/or variation in the timing of dosing became important as well. Existing designs were continuously enhanced and expanded to account for increased trial complexity. With toxicities occurring at later stages beyond the first cycle and the need to treat patients over multiple cycles, the focus on the first treatment cycle only is becoming a limitation in nowadays multi-cycle treatment therapies. Here, we introduce a multi-cycle time-to-event model (TITE-CLRM: Time-Interval-To-Event Complementary-Loglog Regression Model), allowing guidance of dose-escalation trials studying multi-cycle therapies. The challenge lies in balancing the need to monitor the safety of longer treatment periods with the need to continuously enroll patients safely. The proposed multi-cycle time-to-event model is formulated as an extension to established concepts like the escalation with overdose control principle. The model is motivated by a current drug development project and evaluated in a simulation study.

多周期癌症治疗的有效时间-事件剂量递增指导。
随着时间的推移,癌症的治疗已经以相当戏剧性的方式迅速发展,例如,从化疗、靶向治疗到免疫治疗和嵌合抗原受体t细胞。尽管如此,肿瘤早期I期试验的基本设计仍然主要遵循剂量递增设计。这些试验监测第一个治疗周期的安全性,以增加所研究药物的剂量。然而,随着时间的推移,研究其他因素,如药物组合和/或给药时间的变化也变得很重要。现有的设计不断增强和扩展,以解释增加的试验复杂性。由于毒性发生在第一个周期之后的后期阶段,并且需要在多个周期内对患者进行治疗,因此仅关注第一个治疗周期正在成为当今多周期治疗疗法的局限性。在这里,我们引入了一个多周期时间-事件模型(TITE-CLRM:时间-间隔-事件互补-对数回归模型),可以指导研究多周期治疗的剂量递增试验。挑战在于平衡监测较长治疗期安全性的需要与持续安全地招募患者的需要。提出的多周期时间到事件模型是对已建立的概念的扩展,如过量控制原则的升级。该模型是由当前的药物开发项目驱动的,并在模拟研究中进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Statistics in Medicine
Statistics in Medicine 医学-公共卫生、环境卫生与职业卫生
CiteScore
3.40
自引率
10.00%
发文量
334
审稿时长
2-4 weeks
期刊介绍: The journal aims to influence practice in medicine and its associated sciences through the publication of papers on statistical and other quantitative methods. Papers will explain new methods and demonstrate their application, preferably through a substantive, real, motivating example or a comprehensive evaluation based on an illustrative example. Alternatively, papers will report on case-studies where creative use or technical generalizations of established methodology is directed towards a substantive application. Reviews of, and tutorials on, general topics relevant to the application of statistics to medicine will also be published. The main criteria for publication are appropriateness of the statistical methods to a particular medical problem and clarity of exposition. Papers with primarily mathematical content will be excluded. The journal aims to enhance communication between statisticians, clinicians and medical researchers.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信