Andrew J Plodkowski1, Jose Arimateia Batista Araujo-Filho2, Cameron D A Simmers2, Jeffrey Girshman2, Micheal Raj2, Junting Zheng3, Andreas Rimner4, Michelle S Ginsberg2. 1. Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA. Electronic address: plodkowa@mskcc.org. 2. Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA. 3. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA. 4. Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
Abstract
OBJECTIVES: The aim of this study was to delineate computed tomography (CT) features of stage IIIA non-small cell lung cancers on pre-treatment staging studies and identify features that could predict local recurrence after definitive concurrent chemoradiotherapy. MATERIALS AND METHODS: We retrospectively reviewed pre- and post-treatment CT scans for 91 patients with Stage IIIA non-small cell lung cancer undergoing definitive concurrent chemoradiotherapy. Pre-treatment CT qualitative features were evaluated by consensus. The primary endpoint was local recurrence as determined on post-treatment CT scans along with the radiotherapy fields. Local recurrence was defined as intrathoracic in-field and marginal as opposed to out-of-field failures. Competing risk regressions were used to examine associations between CT features and recurrence. RESULTS: The median follow-up was 51.5 months (range 2.4-111.2). Median overall survival was 25.6 months (95% CI: 20.4-30). At last follow-up, 72 (79.1%) patients had died, 48 (52.7%) had in-field recurrence, and 30 (32.9%) presented with out-of-field recurrence. On pre-treatment CT scans, tumors presenting as pulmonary consolidations (hazard ratio = 2.34, 95% CI: 1.05-5.22; p 0.038) were more likely to have in-field failure. Tumors with 50-100% necrosis (hazard ratio = 0.15, 95% CI: 0.02-1.06) were associated with decreased out-of-field failure (overall p = 0.038). However, these were rare features in our sample which limit the ability of these features to be associated with such outcomes. CONCLUSIONS: Pre-treatment CT features alone are limited in predicting locoregional recurrence. Larger studies using quantitative tools are needed to predict such outcomes.
OBJECTIVES: The aim of this study was to delineate computed tomography (CT) features of stage IIIA non-small cell lung cancers on pre-treatment staging studies and identify features that could predict local recurrence after definitive concurrent chemoradiotherapy. MATERIALS AND METHODS: We retrospectively reviewed pre- and post-treatment CT scans for 91 patients with Stage IIIA non-small cell lung cancer undergoing definitive concurrent chemoradiotherapy. Pre-treatment CT qualitative features were evaluated by consensus. The primary endpoint was local recurrence as determined on post-treatment CT scans along with the radiotherapy fields. Local recurrence was defined as intrathoracic in-field and marginal as opposed to out-of-field failures. Competing risk regressions were used to examine associations between CT features and recurrence. RESULTS: The median follow-up was 51.5 months (range 2.4-111.2). Median overall survival was 25.6 months (95% CI: 20.4-30). At last follow-up, 72 (79.1%) patients had died, 48 (52.7%) had in-field recurrence, and 30 (32.9%) presented with out-of-field recurrence. On pre-treatment CT scans, tumors presenting as pulmonary consolidations (hazard ratio = 2.34, 95% CI: 1.05-5.22; p 0.038) were more likely to have in-field failure. Tumors with 50-100% necrosis (hazard ratio = 0.15, 95% CI: 0.02-1.06) were associated with decreased out-of-field failure (overall p = 0.038). However, these were rare features in our sample which limit the ability of these features to be associated with such outcomes. CONCLUSIONS: Pre-treatment CT features alone are limited in predicting locoregional recurrence. Larger studies using quantitative tools are needed to predict such outcomes.
Authors: Neil M Woody; Kevin L Stephans; Martin Andrews; Tingliang Zhuang; Priyanka Gopal; Ping Xia; Carol F Farver; Daniel P Raymond; Craig D Peacock; Joseph Cicenia; Chandana A Reddy; Gregory M M Videtic; Mohamed E Abazeed Journal: J Thorac Oncol Date: 2016-12-22 Impact factor: 15.609