Modeling the Impact of Cardiopulmonary Irradiation on Overall Survival in NRG Oncology Trial RTOG 0617

Abstract

Purpose: To quantitatively predict the impact of cardiopulmonary dose on overall survival (OS) after radiotherapy for locally advanced non-small cell lung cancer.Experimental Design: We used the NRG Oncology/RTOG 0617 dataset. The model building procedure was preregistered on a public website. Patients were split between a training and a set-aside validation subset (N ¼ 306/131). The 191 candidate variables covered disease, patient, treatment, and dose-volume characteristics from multiple cardiopulmonary substructures (atria, lung, pericardium, and ventricles), including the minimum dose to the hottest x% volume (Dx%[Gy]), mean dose of the hottest x% (MOHx%[Gy]), and minimum, mean (Mean[Gy]), and maximum dose. The model building was based on Cox regression and given 191 candidate variables; a Bonferroni-corrected P value threshold of 0.0003 was used to identify predictors. To reduce overreliance on the most highly correlated variables, stepwise multivariable analysis (MVA) was repeated on 1000 bootstrapped replicates. Multivariate sets selected in ≥10% of replicates were fit to the training subset and then averaged to generate a final model. In the validation subset, discrimination was assessed using Harrell c-index, and calibration was tested using risk group stratification.Results: Four MVA models were identified on bootstrap. The averaged model included atria D45%[Gy], lung Mean[Gy], pericardium MOH55%[Gy], and ventricles MOH5% [Gy]. This model had excellent performance predicting OS in the validation subset (c ¼ 0.89).Conclusions: The risk of death due to cardiopulmonary irradiation was accurately modeled, as demonstrated by predictions on the validation subset, and provides guidance on the delivery of safe thoracic radiotherapy.

Clinical Outcomes of Pencil Beam Scanning Proton Therapy in Locally Advanced Non-Small Cell Lung Cancer: Propensity Score Analysis

“…Atkins et al suggested stringent avoidance of cardiac radiation dose based on an increased risk of cardiotoxicity and mortality with increasing cardiac dose in patients with locally advanced NSCLC [ 7 ]. The recent post hoc modeling study of the RTOG 0617 trial also showed a relationship between a higher dose to cardiopulmonary substructures and unexpected mortality [ 35 ]. The reduced dose to those structures of PBT might translate into improved survival of patients undergoing PBT compared to IMRT, which was observed in the National Cancer Database; this potential benefit could thus be maximized when adopting PBSPT [ 36 ].…”

Quantifying inter-fraction cardiac substructure displacement during radiotherapy via magnetic resonance imaging guidance

“…Thus, recent attention has been focused toward local radiation dose deposition to substructures contained within the heart. Sub-analysis of RTOG 0617 revealed that atrial, ventricular, and pericardial doses had a stronger association with overall survival than using standard whole heart dose metrics [10] .…”

Cardio-pulmonary substructure segmentation of radiotherapy computed tomography images using convolutional neural networks for clinical outcomes analysis

“…Further, we extracted eight DVH metrics for the auto-generated DLS and the expert labeled contours pertaining to six structures that were found to be associated with high likelihood of heart toxicity after radiation therapy [21]. These metrics were minimum or average dosevolumes received by the atria, the left atrium, the pericardium, the SVC and the ventricles.…”