Lung Cancer

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TU_25_3570 - Predictive Model of Progression in Early Stage Non Small Cell Lung Cancer Treated with Stereotactic Ablative Radiation Therapy

Tuesday, October 23
2:45 PM - 4:15 PM
Location: Innovation Hub, Exhibit Hall 3

Predictive Model of Progression in Early Stage Non Small Cell Lung Cancer Treated with Stereotactic Ablative Radiation Therapy
H. Bahig1, E. D. Brooks1, T. Zhang1, H. LI2, J. W. Welsh1, S. H. Lin3, D. R. Gomez1, S. Gandhi1, J. Heymach1, and J. Y. Chang1; 1The University of Texas MD Anderson Cancer Center, Houston, TX, 2The University of Texas MD Anderson Cancer Center, HOUSTON, TX, 3Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX

Purpose/Objective(s): There is an emerging interest for combining stereotactic ablative radiotherapy (SABR) with immunotherapy in the management of early stage non small cell lung cancer (ES-NSCLC). To help best select which patients may benefit from immunotherapy in future trials, we aimed to determine the predictive factors of progression free survival (PFS) and time to progression (TTP) in a large cohort of ES-NSCLC patients treated with SABR.

Materials/Methods: A retrospective analysis of patients with stage I–II NSCLC treated with SABR from 2004 to 2015 was conducted. SABR doses of 34-70 Gy in 1-10 fractions were delivered. Cox proportional hazard ratio models were used for analysis of potential predictive variables. The following variables were included in the model: patient age, gender, ECOG performance status, Charlson co-morbidity index, pre-treatment pulmonary function tests (percent forced expiratory volume in 1 second [%FEV1]) and percent diffusing lung capacity for carbon monoxide [%DLCO]), tumor stage, size, histology, location and maximum standardized uptake value (SUVmax) on FDG/PET. Variables with significant association with PFS and TTP in univariate analysis were used for subsequent recursive partitioning analysis (RPA) to identify appropriate cut-off points.

Results: 912 patients with a median age of 72 years (range, 46-91) were included. Median follow-up was 59.3 months. Local recurrence, regional recurrence, distant metastasis and second primary lung cancer developed in 10.0%, 11.5%, 20.1% and 7.5% of patients, at a median time to recurrence of 14.9 months (range, 1.5–91.9), 10.5 months (range 1.4–70.7), 11.6 months (range, 0.2–91.9 months) and 23.6 months (range, 1.2–122.4), respectively. Actuarial 3- and 5-year PFS were 52.7% and 39.1%, and 3- and 5-year TTP were 72.2% and 66.7%, respectively. On univariate analysis, age (p=0.0009), ECOG (p<0.0001), Charlson score (p=0.0001), %DLCO (p<0.0001), %FEV1 (p=0.007), non-adenocarcinoma histology (p<0.0001), tumor size (p=0.01) and tumor SUVmax (p=0.0002) were associated with PFS, while %DLCO (p=0.002), tumor size (p=0.002) and tumor SUVmax (p=0.01) were associated with TTP. RPA identified age ≥ 78 years, Charlson score ≥ 5, %DLCO < 71%, %FEV1 < 65%, tumor size ≥ 3 cm and SUVmax ≥ 12 as significant cut-offs for adverse PFS outcome. RPA identified %DLCO < 71%, tumor size ≥ 3 cm and SUVmax ≥ 12 as significant cut-offs for adverse TTP. On multivariate analysis, age (p=0.05), Charlson score (p=0.03), %DLCO (p=0.00001), non-adenocarcinoma histology (p=0.02), and tumor size (p=0.002) remained predictive of PFS. Correlations with biological markers are currently on-going.

Conclusion: Age ≥ 78 years, Charlson score≥ 5, %DLCO < 71%, tumor size ≥ 3 cm and non-adenocarcinoma histology were found to be independent predictors of PFS. Patients with %DLCO < 71%, tumor size ≥ 3 cm and SUVmax ≥ 12 had adverse TTP outcomes, suggesting that they may benefit from treatment intensification. A predictive model is being develop and will be presented.

Author Disclosure: H. Bahig: Research Grant; varian medical systems. Honoraria; Siemens. E.D. Brooks: None. T. Zhang: None. H. LI: None. J.W. Welsh: Stock; Healios, MolecularMatch. Stock Options; OncoResponse, Reflexion Medical. S.H. Lin: Research Grant; Elekta, Inc, Hitachi Chemical, Inc, Peregrine Pharmaceuticals, Inc, Roche/Genentech, STCube Pharmaceuticals, Inc. D.R. Gomez: Research Grant; Merck, AstraZeneca. Honoraria; BMS. Speaker's Bureau; Merck, Varian. Advisory Board; AstraZeneca. S. Gandhi: None. J. Heymach: None. J.Y. Chang: Research Grant; MDACC-BMS Alliance Research Grant. Partnership; Global Oncology One. Chair of the Board of Directors; SANTRO. Chair; ACR. Chair for Thoracic Subcommittee; PTCOG.

Houda Bahig, MD

Centre Hospitalier de l'Universite de Montreal

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