High-dose Heart Irradiation is a Statistically Significant Risk Factor for Radiation Pneumonitis within Logistic-multivariate Modeling

Abstract

To detect and quantify, within a multivariate framework, the effect of heart irradiation on the risk of radiation pneumonitis (RP) for radiotherapy patients treated for lung cancer. All evaluable, archived 3D treatment plans for patients with registered outcomes treated for NSCLC between 1991 and 2001 were eligible. RP which resulted in steroid use or more intensive intervention was classified as an event (WUSTL Grade 2 or higher; RTOG Grade 3 or higher). Doses were retrospectively corrected for heterogeneity effects via a Monte Carlo-based method. Plans were processed and reviewed using CERR (computational environment for radiotherapy research). Heart volumes were re-contoured within CERR by a single physician (n = 209, with 48 RP events). Heart and normal lung (lung minus gross tumor volume) dose-volume parameters were extracted for further modeling using CERR. Evaluated factors included clinical (age, gender, race, performance status, weight loss, smoking, histology); dosimetric parameters for heart (D5-D100, V10-V80, mean dose, maximum dose, and minimum dose); treatment factors (chemotherapy, treatment time, fraction size); location parameters (heart center-of-dose, sup-inf within the heart); as well as previously identified significant lung parameters: mean lung dose and sup-inf tumor position (GTV center-of-mass) within the lung (Bradley JD et al., IJROBP 2007;69(4):985-992). A best multivariate model was obtained by step-wise variable selection and logistic regression. The best model order was determined using leave-one-out cross validation. Statistically significant variables with the highest univariate Spearman rank correlations included: maximum heart dose (0.227, p < 0.0006), heart V70 (0.239, p < 0.0003), heart D5 (minimum dose to the hottest 5% of the heart) (0.256, p < 0.0002), heart D10 (0.24, p < 0.0003), heart gEUD (0.249 for a = 10, p < 0.0001), and GTV_COMSI (0.219, p < 0.0008). Leave-one-out cross-validation analysis supported a model order of four variables (with rank correlation coefficients on the out-of-sample points of about 0.3). The most commonly selected variables were (in order of decreasing frequency): heart D10, heart D30, mean lung dose, and GTV_COMSI within the lung. Heart dose-volume parameters were more statistically significant than any previously derived lung parameters within a multivariate modeling framework to predict RP. These correlations should be tested further against new datasets.