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头颈部癌症加速再增殖的剂量依赖性:支持证据和临床意义。

Dose dependence of accelerated repopulation in head and neck cancer: Supporting evidence and clinical implications.

机构信息

Center for Radiological Research, Columbia University Medical Center, New York, USA.

Center for Radiological Research, Columbia University Medical Center, New York, USA.

出版信息

Radiother Oncol. 2018 Apr;127(1):20-26. doi: 10.1016/j.radonc.2018.02.015. Epub 2018 Mar 10.

Abstract

BACKGROUND AND PURPOSE

Accelerated repopulation (AR) can compromise tumor control after conventional radiotherapy for fast-growing tumors. Standard AR models assume it begins at a fixed time, with repopulation rates independent of the number of clonogens killed. We investigate the validity and significance of an alternative model where onset-time and rate of AR depend on the number of clonogens killed, and thus on dose and dose-fractionation.

MATERIALS AND METHODS

We analyzed tumor control (TCP) from randomized trials for head and neck cancer (HNC, 7283 patients), featuring wide ranges of doses, times, and fractionation-schemes. We used the linear-quadratic model with the standard dose-independent AR model, or with an alternative dose-dependent model, where AR onset and rate depend on clonogen killing.

RESULTS

The alternative dose-dependent model of AR provides significantly-improved descriptions of a wide range of randomized clinical data, relative to the standard dose-independent model. This preferred model predicts that, for currently-used HNC fractionation schemes, the last 5 fractions do not increase TCP, but simply compensate for increased accelerated repopulation.

CONCLUSIONS

The preferred dose-dependent AR model predicts that, for standard fractionation schemes currently used to treat HNC, the final week (5 fractions) could be eliminated without compromising TCP, but resulting in significantly decreased late sequelae due to the lower overall dose.

摘要

背景与目的

对于生长迅速的肿瘤,常规放疗后的加速再增殖(AR)会影响肿瘤控制。标准 AR 模型假设它在固定时间开始,再增殖率与杀死的克隆源数量无关。我们研究了一种替代模型的有效性和意义,其中 AR 的起始时间和速率取决于杀死的克隆源数量,从而取决于剂量和剂量分割方案。

材料和方法

我们分析了头颈部癌症(HNC)的随机试验中的肿瘤控制(TCP),这些试验具有广泛的剂量、时间和分割方案。我们使用线性二次模型,采用标准的不依赖剂量的 AR 模型,或采用替代的依赖剂量的模型,其中 AR 的起始和速率取决于克隆源的杀伤。

结果

与标准的不依赖剂量的模型相比,AR 的替代的依赖剂量的模型为广泛的随机临床数据提供了显著改进的描述。该首选模型预测,对于目前用于 HNC 的分割方案,最后 5 个分割不会增加 TCP,而只是补偿了增加的加速再增殖。

结论

首选的依赖剂量的 AR 模型预测,对于目前用于治疗 HNC 的标准分割方案,最后一周(5 个分割)可以消除而不会影响 TCP,但由于总剂量降低,会导致显著减少的晚期后遗症。

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