Lung Cancer

SS 02 - Lung 1 - SBRT

20 - An Externally Validated Nomogram for Predicting Distant Metastasis after Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer: Implications for Adjuvant Systemic Therapy

Sunday, October 21
2:15 PM - 2:25 PM
Location: Room 004

An Externally Validated Nomogram for Predicting Distant Metastasis after Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer: Implications for Adjuvant Systemic Therapy
A. Juloori1, A. Zajichek2, M. W. Kattan2, D. Mullen3, P. Samson3, N. M. Woody1, M. C. Roach Jr4, J. D. Bradley4, G. M. Videtic1, C. G. Robinson5, and K. L. Stephans1; 1Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, 2Cleveland Clinic Foundation, Cleveland, OH, 3Washington University in St. Louis, Department of Radiation Oncology, St. Louis, MO, 4Washington University School of Medicine, St. Louis, MO, 5Washington University School of Medicine, Department of Radiation Oncology, St. Louis, MO

Purpose/Objective(s): SBRT is a standard treatment option for patients with early stage NSCLC who are considered medically inoperable. While SBRT is associated with excellent local control, distant metastases (DM) represent the primary pattern of failure. Adjuvant systemic therapy has not traditionally been used in this patient population due to medical comorbidities. With the advent of immunotherapy that may be better tolerated, there has been a renewed interest in identifying patients that may derive benefit. We developed and internally validated a nomogram to predict the likelihood of DM after SBRT for early stage NSCLC which was then externally validated.

Materials/Methods: Our institutional registry of patients treated with lung SBRT was queried for patients with early stage NSCLC treated with definitive intent from 2003-2017 and 1002 patients were identified for analysis to develop the model. A large dataset from an external institution was used to similarly identify patients and 737 patients were used for the model validation cohort. Random Survival Forest was used as an exploratory phase to assess importance, interactivity, and overall predictive ability with respect to distant failure for 14 variables. A Fine-Gray competing-risks regression model was then formulated where apparent interactions/non-linear relationships were examined with likelihood-ratio (LR) tests. Backward variable selection was then implemented to reduce to a parsimonious model. The concordance probability (C-index) of the final model was internally validated with 10-fold cross validation.

Results: The median overall survival was 1.71 years internally and 1.92 years externally. Median follow-up was 18.3 months and 21.1 months. The 1-year incidence of distant failure was 16% and 12.1% in the internal and external cohorts, respectively. The results from the random forest suggest that tumor size and PET SUV are the most important predictors of distant failure. The 1-year cumulative incidence (CI) of DM was 18.5% for PET SUV ≥4.1 vs 8.4% for <4.1. 1-year CI for tumor size >3 cm was 26% vs 12.6% for ≤3 cm. The median time to distant failure was 0.86 years internally and 1.1 years externally. The final nomogram included tumor size, histology, PET SUV, age, KPS, and active smoking status, and had a cross-validated C-index of 0.62. The nomogram provides predictive value for probability of DM at 1-year between 10 and 70%.

Conclusion: This novel nomogram with external validation can be used to predict the 1-yr risk of DM after SBRT for pts with early-stage NSCLC, accounting for the competing risk of death. This nomogram may help define patient subsets for stratification in future clinical trials to help identify who may benefit from adjuvant systemic therapy after SBRT to reduce the incidence of distant failure and disease-related death.

Author Disclosure: A. Juloori: None. A. Zajichek: None. M.W. Kattan: Consultant; Novartis. D. Mullen: None. P. Samson: Employee; Washington Univeristy. Data management committee chair; member of PLG; ImproveCareNow. M.C. Roach: Travel Expenses; BTG, Varian, Elekta. J.D. Bradley: None. G.M. Videtic: Advisory Board; Astra Zeneca. Member; ASTRO, RTOG, IASLC. C.G. Robinson: Research Grant; Varian Medical Systems, Elekta. Speaker's Bureau; Varian Medical Systems, DFINE. Advisory Board; Radialogica. Stock Options; Radialogica. K.L. Stephans: None.

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