首页> 外文期刊>Physics in medicine and biology. >Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-) radiotherapy
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Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-) radiotherapy

机译:食管壁剂量表面图不会改善用强度调节(化学)放射治疗的晚期NSCLC患者的急性食管毒性的多变量NTCP模型的预测性能

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摘要

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade. 2 after highly conformal (chemo-) radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC = 0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.
机译:在我们之前的工作中,一种多变量的正常组织并发症概率(NTCP)模型用于急性食管毒性(AET)等级。 2在非小细胞肺癌(NSCLC)高度保形(Chemo-)放射疗法后,使用多变量逻辑回归分析进行临床参数,平均食管剂量(MED)。由于食道是管状器官,因此食管壁剂量分布的空间信息对于预测AET可能是重要的。我们调查了具有空间信息的食管壁剂量表面数据是否提高了我们已建立的NTCP模型的预测力。对于用高度保形放射治疗治疗食管壁剂量表面直方图(DSHS)和极性剂量表面图(DSM)的149例NSCLC患者。 DSM用于生成新的DSH和剂量长度直方图,其包含剂量表面分布的空间信息。来自这些直方图的剂量参数来源和单变量逻辑回归分析显示它们与AET显着相关。在我们以前的工作之后,使用基于单变量分析的最重要的剂量直方图参数(总共有19个)开发了新的多变量NTCP模型。然而,基于常规剂量数据(AUC = AUC = AUC =,包含具有空间信息的19个新模型,其具有空间信息的具有空间信息,没有显示出改进的预测性能(AUC,AUC范围0.79-0.84的区域0.79-0.84) 0.84)。对于AET的预测,基于所提出的多变量统计方法,食管壁剂量分布的空间信息是没有附加值的,并且仅考虑MED作为预测剂量分析。

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