Welsh, James W.

Abstract Purpose: RTOG 0617 was a phase III randomized trial for patients with unresectable stage IIIA/IIIB non–small cell lung cancer comparing standard-dose (60 Gy) versus high-dose (74 Gy) radiotherapy and chemotherapy, plus or minus cetuximab. Although the study was negative, based on prior evidence that patients with the KRAS-variant, an inherited germline mutation, benefit from cetuximab, we evaluated KRAS-variant patients in RTOG 0617. Experimental Design: From RTOG 0617, 328 of 496 (66%) of patients were included in this analysis. For time-to-event outcomes, stratified log-rank tests and multivariable Cox regression models were used. For binary outcomes, Cochran—Mantel–Haenzel tests and multivariable logistic regression models were used. All statistical tests were two sided, and a P value <0.05 was considered significant. Results: A total of 17.1% (56/328) of patients had the KRAS-variant, and overall survival rates were similar between KRAS-variant and non-variant patients. However, there was a time-dependent effect of cetuximab seen only in KRAS-variant patients—while the hazard of death was higher in cetuximab-treated patients within year 1 [HR = 3.37, 95% confidence interval (CI): 1.13–10.10, P = 0.030], death was lower from year 1 to 4 (HR = 0.33, 95% CI: 0.11–0.97, P = 0.043). In contrast, in non-variant patients, the addition of cetuximab significantly increased local failure (HR = 1.59, 95% CI: 1.11–2.28, P = 0.012). Conclusions/Discussion: Although an overall survival advantage was not achieved in KRAS-variant patients, there is potential impact of cetuximab for this genetic subset of patients. In contrast, cetuximab seems to harm non-variant patients. These findings further support the importance of genetic patient selection in trials studying the addition of systemic agents to radiotherapy. Significance: The KRAS-variant is the first functional, inherited miRNA-disrupting variant identified in cancer. Our findings support that cetuximab has a potentially beneficial impact on KRAS-variant patients treated with radiation. The work confirms prior evidence that KRAS-variant patients are a subgroup who are especially sensitive to radiation. These findings further support the potential of this class of variants to enable true treatment personalization, considering the equally important endpoints of response and toxicity.

TPS9082 Background: Limited stage small cell lung cancer (LS-SCLC) is treated with standard of care platinum/etoposide (EP) and thoracic radiation therapy (TRT) with curative intent, however the majority of patients are not cured and median overall survival is approximately 30 months. Addition of atezolizumab to chemotherapy in extensive stage SCLC has improved progression free and overall survival in a non-curative setting leading to hope that addition of an immune checkpoint inhibitor to standard chemoradiotherapy could benefit LS-SCLC patients. LU005 is a randomized phase II/III trial of standard concurrent chemoradiation with or without atezolizumab for patients with LS-SCLC. Methods: Patients are randomly assigned in a 1:1 ratio to standard EP chemotherapy with concurrent TRT (45 Gy BID or 66 Gy QD) with or without atezolizumab beginning concurrently with TRT, and continued every 3 weeks for up to 12 months. Eligible patients have LS-SCLC, PS 0-2, adequate organ function, no concerning comorbidities (including no active autoimmune disease) and are eligible for TRT. Patients are randomized prior to their second cycle of EP and thoracic radiation begins with the second overall cycle of chemotherapy (first cycle of study therapy) in both treatment arms. Prophylactic cranial radiation (PCI) is recommended for patients who respond to treatment. The phase II/III primary endpoints are progression free (PFS) and overall survival (OS) respectively. Secondary endpoints include objective response rates, local and distant disease control, and quality of life/patient reported outcomes assessment. Translational science component includes blood and tissue based immune related assays. This study activated in May 2019. 50 of 506 planned patients have been accrued as of 2/1/2020. Supported by grants U10CA180868 (NRG Oncology Operations), U10CA180822 (NRG Oncology SDMC), U23CA180803 (IROC) from the National Cancer Institute (NCI) and Genentech. *Authors Ross and Higgins are co-first authors and contributed equally to this work. Clinical trial information: NCT03811002.

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 = 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 = 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.