TY - JOUR
T1 - Modeling the impact of cardiopulmonary irradiation on overall survival in NRG oncology trial RTOG 0617
AU - Thor, Maria
AU - Deasy, Joseph O.
AU - Hu, Chen
AU - Gore, Elizabeth
AU - Bar-Ad, Voichita
AU - Robinson, Clifford
AU - Wheatley, Matthew
AU - Oh, Jung Hun
AU - Bogart, Jeffrey
AU - Garces, Yolanda I.
AU - Kavadi, Vivek S.
AU - Narayan, Samir
AU - Iyengar, Puneeth
AU - Witt, Jacob S.
AU - Welsh, James W.
AU - Koprowski, Cristopher D.
AU - Larner, James M.
AU - Xiao, Ying
AU - Bradley, Jeffrey
N1 - Publisher Copyright:
© 2020 American Association for Cancer Research.
PY - 2020/9
Y1 - 2020/9
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85086172648&partnerID=8YFLogxK
U2 - 10.1158/1078-0432.CCR-19-2627
DO - 10.1158/1078-0432.CCR-19-2627
M3 - Article
C2 - 32398326
AN - SCOPUS:85086172648
SN - 1078-0432
VL - 26
SP - 4643
EP - 4650
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 17
ER -