Langer M, Morrill S S, Lane R
Department of Radiation Therapy, University of Texas Medical Branch, Galveston 77555-0711, USA.
Int J Radiat Oncol Biol Phys. 1998 May 1;41(2):451-7. doi: 10.1016/s0360-3016(98)00057-1.
This study tests an accepted claim regarding tumor control (TCP) and normal tissue complication (NTCP) probability functions. The claim is that treatment plans can be ranked using relative probabilities, even when the absolute probabilities are unknown. The assumption supports the use of probability models for plan optimization and the comparison of treatment techniques.
The claim was tested using a hypothetical model consisting of two tissues, and illustrated with clinical data. Plans were scored using the probability of uncomplicated tumor control. The scores of different plans were compared by fixing their relative risks for an individual tissue complication, but adjusting the absolute probability levels up or down. The tested claim is that the plan rankings should not change.
In the two-tissue model, the rankings of competing plans were reversed by doubling all the probabilities. The preference ordering of lung cancer plans changed after the risk of pulmonary complication was reduced by 3-fold. In another site, the ranking of plans by overall complication-free probability was disturbed by errors that preserved the ordering of plans with respect to any individual complication. An adjustment of +/- 2.5% in the initial NTCP values for two tissues changed the direction in which a plan score moved in response to a fixed tradeoff in complication risk in an optimization search.
Contrary to claims, plan rankings are not determined by the relative probabilities of adverse events. The effect on plan scores of trading one complication for another depends on the absolute levels of risk. Absolute errors in NTCP and TCP functions result in the wrong ranking of plans, even when relative probabilities are correct. An optimization routine based on TCP and NTCP calculations may be forced in the wrong direction by small errors in the probability estimates.
本研究对一个关于肿瘤控制概率(TCP)和正常组织并发症概率(NTCP)函数的公认说法进行检验。该说法是,即使绝对概率未知,也可以使用相对概率对治疗计划进行排序。这一假设支持使用概率模型进行计划优化以及治疗技术比较。
使用由两种组织构成的假设模型对该说法进行检验,并用临床数据进行说明。根据无并发症肿瘤控制的概率对计划进行评分。通过固定个体组织并发症的相对风险,但上调或下调绝对概率水平,比较不同计划的得分。所检验的说法是计划排名不应改变。
在双组织模型中,将所有概率翻倍会使竞争计划的排名颠倒。将肺部并发症风险降低3倍后,肺癌计划的偏好顺序发生了变化。在另一个部位,按总体无并发症概率对计划进行的排名因误差而受到干扰,这些误差保持了各计划在任何个体并发症方面的排序。对两种组织的初始NTCP值进行±2.5%的调整,改变了在优化搜索中计划得分随并发症风险固定权衡而变化的方向。
与上述说法相反,计划排名并非由不良事件的相对概率决定。用一种并发症换取另一种并发症对计划得分的影响取决于绝对风险水平。NTCP和TCP函数中的绝对误差会导致计划排名错误,即使相对概率是正确的。基于TCP和NTCP计算的优化程序可能会因概率估计中的小误差而被迫朝着错误方向进行。