为适应疗法推导最佳治疗时间:将模型与瘤动态相匹配
Kit Gallagher1,2, Maximilian A R Strobl3, Alexander R A Anderson4
1Wolfson Centre for Mathematical Biology, Mathematical Institute, Oxford, UK. gallagher@maths.ox.ac.uk.
Bulletin of mathematical biology
|September 8, 2025
概括
适应疗法 (AT) 优化了癌症治疗,包括从最大耐受剂量化疗中休息. 这种方法旨在通过管理瘤负担和耐药性来改善结果,提供潜在的延长时间到进展.
科学领域:
- 在瘤学瘤学.
- 数学生物学 数学生物学
- 药理学 药理学是指药理学的学科.
背景情况:
- 适应疗法 (AT) 是一种新兴的癌症治疗策略,涉及间歇性药物管理.
- 通过利用瘤负担动态和敏感和耐药细胞群之间的竞争性抑制,AT旨在克服耐药性.
- 当前的AT协议往往缺乏个性化,并且没有充分考虑临床约束,例如离散的监测间隔.
研究的目的:
- 为优化适应性治疗方案制定一个总体框架,考虑到临床预约时间表.
- 为了获得适应性治疗的模型独立的最佳治疗计划.
- 研究监测频率对治疗结果的影响,并提出新的AT策略.
主要方法:
- 在离散的时间限制下,开发适应性治疗优化的数学框架.
- 为各种瘤生长和反应的数学模型推导最佳治疗计划.
- 分析患者监测频率和进展时间之间的权衡.
- 确定需要不同的适应性治疗方法的患者子集.
主要成果:
- 为优化适应性治疗方案建立了一个可概括的框架,考虑到离散的临床时间间隔.
- 获得了最佳的时间表,证明了监测频率和进展时间之间的权衡.
- 为特定的患者子组提出了一种基于患者特异性,时间变化的临界值的新型适应性治疗方案.
- 该研究强调了固定值的AT协议的局限性以及需要动态,个性化的方法.
结论:
- 优化适应性治疗方案可以通过考虑临床现实来改善癌症治疗结果.
- 患者监测频率是影响自适应治疗有效性的关键因素.
- 个性化适应性治疗,可能涉及动态值,对于管理异质瘤动态和改善患者结果至关重要.
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