School of Cancer Studies, University of Liverpool, Liverpool L69 3GA, United Kingdom.
Int J Radiat Oncol Biol Phys. 2012 Feb 1;82(2):1021-30. doi: 10.1016/j.ijrobp.2010.12.048. Epub 2011 Mar 4.
To determine how modelled maximum tumor control rates, achievable without exceeding mucositis tolerance (tcp(max-early)) vary with schedule duration for head and neck squamous cell carcinoma (HNSCC).
Using maximum-likelihood techniques, we have fitted a range of tcp models to two HNSCC datasets (Withers' and British Institute of Radiology [BIR]), characterizing the dependence of tcp on duration and equivalent dose in 2 Gy fractions (EQD(2)). Models likely to best describe future data have been selected using the Akaike information criterion (AIC) and its quasi-AIC extension to overdispersed data. Setting EQD(2)s in the selected tcp models to levels just tolerable for mucositis, we have plotted tcp(max-early) against schedule duration.
While BIR dataset tcp fits describe dose levels isoeffective for tumor control as rising significantly with schedule protraction, indicative of accelerated tumor repopulation, repopulation terms in fits to Withers' dataset do not reach significance after accounting for overdispersion of the data. The tcp(max-early) curves calculated from tcp fits to the overall Withers' and BIR datasets rise by 8% and 0-4%, respectively, between 20 and 50 days duration; likewise, tcp(max-early) curves calculated for stage-specific cohorts also generally rise slowly with increasing duration. However none of the increases in tcp(max-early) calculated from the overall or stage-specific fits reach significance.
Local control rates modeled for treatments which lie just within mucosal tolerance rise slowly but insignificantly with increasing schedule length. This finding suggests that whereas useful gains may be made by accelerating unnecessarily slow schedules until they approach early reaction tolerance, little is achieved by shortening schedules further while reducing doses to remain within mucosal tolerance, an approach that may slightly worsen outcomes.
确定头颈部鳞状细胞癌(HNSCC)的最大肿瘤控制率模型(不超过粘膜炎耐受的 tcp(max-early))如何随方案持续时间而变化。
使用最大似然技术,我们拟合了一系列 tcp 模型到两个 HNSCC 数据集(Withers 和英国放射研究所 [BIR]),描述了 tcp 对持续时间和 2 Gy 分数等效剂量(EQD(2))的依赖性。使用 Akaike 信息准则(AIC)及其对过度分散数据的准 AIC 扩展选择最能描述未来数据的模型。将选定的 tcp 模型中的 EQD(2)设置为仅对粘膜炎可耐受的水平,我们绘制了 tcp(max-early)与方案持续时间的关系图。
虽然 BIR 数据集的 tcp 拟合描述了肿瘤控制的等效剂量水平随着方案的延长而显著升高,表明肿瘤再增殖加速,但在考虑到数据的过度分散后,与 Withers 数据集拟合的再增殖项并不显著。从整体 Withers 和 BIR 数据集的 tcp 拟合计算得出的 tcp(max-early)曲线在 20 到 50 天的持续时间内分别升高了 8%和 0-4%;同样,为特定阶段队列计算的 tcp(max-early)曲线也随着持续时间的增加而缓慢升高。然而,从整体或特定阶段拟合计算得出的 tcp(max-early)增加均无显著意义。
处于粘膜耐受范围内的治疗方案的局部控制率随着方案长度的增加而缓慢但无显著增加。这一发现表明,虽然通过加速不必要的缓慢方案直到它们接近早期反应耐受可以获得有用的收益,但在保持粘膜耐受的同时减少剂量以缩短方案进一步缩短方案,几乎没有什么效果,这种方法可能会略微恶化结果。