Sara Pilotto1, Isabella Sperduti2, Giovanni Leuzzi3, Marco Chiappetta2, Felice Mucilli4, Giovanni Battista Ratto5, Filippo Lococo6, Pier Lugigi Filosso7, Lorenzo Spaggiari8, Silvia Novello9, Michele Milella2, Antonio Santo1, Aldo Scarpa10, Maurizio Infante1, Giampaolo Tortora1, Francesco Facciolo2, Emilio Bria11. 1. Medical Oncology, University of Verona, University Hospital of Verona, Verona, Italy. 2. Regina Elena National Cancer Institute, Rome, Italy. 3. Scientific Institute for Research, Hospitalization and Health Care (IRCSS) National Cancer Institute, Milan, Italy. 4. University Hospital SS. Annunziata, Chieti, Italy. 5. IRCCS University Hospital San Martino National Cancer Institute, Genoa, Italy. 6. IRCSS Santa Maria Nuova Hospital, Reggio Emilia, Italy. 7. University of Turin, San Giovanni Battista Hospital, Turin, Italy. 8. European Institute of Oncology, University of Milan, Milan, Italy. 9. Department of Oncology, University of Turin, University Hospital San Luigi Orbassano, Turin, Italy. 10. Department of Diagnostics and Public Health, University of Verona, Verona, Italy; Center for Applied Research on Cancer (ARC-NET), University of Verona, Verona, Italy. 11. Medical Oncology, University of Verona, University Hospital of Verona, Verona, Italy. Electronic address: emilio.bria@univr.it.
Abstract
INTRODUCTION: We developed one of the first clinicopathological prognostic nomograms for resected squamous cell lung cancer (SQLC). Herein, we validate the model in a larger multicenter cohort and we explore the impact of adjuvant and neoadjuvant treatment (ANT). METHODS: Patients with resected SQLC from January 2002 to December 2012 in six institutions were eligible. Each patient was assigned a prognostic score based on the clinicopathological factors included in the model (age, T descriptor according to seventh edition of the TNM classification, lymph node status, and grading). Kaplan-Meier analysis for disease-free survival, cancer-specific survival (CSS), and overall survival was performed according to a three-class risk model. Harrell's C-statistics were adopted for model validation. The effect of ANT was adjusted with propensity score. RESULTS: Data on 1375 patients were gathered (median age, 68 years; male sex, 86.8%; T descriptor 1 or 2 versus 3 or 4, 71.7% versus 24.9%; nodes negative versus positive, 53.4% versus 46.6%; and grading of 1 or 2 versus 3, 35.0% versus 41.1%). Data for survival analysis were available for 1097 patients. With a median follow-up of 55 months, patients at low risk had a significantly longer disease-free survival than did patients at intermediate risk (hazard ratio [HR] = 1.67, 95% confidence interval [CI]: 1.40-2.01) and patients at high risk (HR = 2.46, 95% CI: 1.90-3.19); they also had a significantly longer CSS (HR = 2.46, 95% CI: 1.80-3.36 versus HR = 4.30, 95% CI: 2.92-6.33) and overall survival (HR = 1.79, 95% CI: 1.48-2.17 versus HR = 2.33, 95% CI: 1.76-3.07). A trend in favor of ANT was observed for intermediate-risk/high-risk patients, particularly for CSS (p = 0.06 [5-year CSS 72.7% versus 60.8%]). CONCLUSIONS: A model based on a combination of easily available clinicopathological factors effectively stratifies patients with resected SQLC into three risk classes.
INTRODUCTION: We developed one of the first clinicopathological prognostic nomograms for resected squamous cell lung cancer (SQLC). Herein, we validate the model in a larger multicenter cohort and we explore the impact of adjuvant and neoadjuvant treatment (ANT). METHODS:Patients with resected SQLC from January 2002 to December 2012 in six institutions were eligible. Each patient was assigned a prognostic score based on the clinicopathological factors included in the model (age, T descriptor according to seventh edition of the TNM classification, lymph node status, and grading). Kaplan-Meier analysis for disease-free survival, cancer-specific survival (CSS), and overall survival was performed according to a three-class risk model. Harrell's C-statistics were adopted for model validation. The effect of ANT was adjusted with propensity score. RESULTS: Data on 1375 patients were gathered (median age, 68 years; male sex, 86.8%; T descriptor 1 or 2 versus 3 or 4, 71.7% versus 24.9%; nodes negative versus positive, 53.4% versus 46.6%; and grading of 1 or 2 versus 3, 35.0% versus 41.1%). Data for survival analysis were available for 1097 patients. With a median follow-up of 55 months, patients at low risk had a significantly longer disease-free survival than did patients at intermediate risk (hazard ratio [HR] = 1.67, 95% confidence interval [CI]: 1.40-2.01) and patients at high risk (HR = 2.46, 95% CI: 1.90-3.19); they also had a significantly longer CSS (HR = 2.46, 95% CI: 1.80-3.36 versus HR = 4.30, 95% CI: 2.92-6.33) and overall survival (HR = 1.79, 95% CI: 1.48-2.17 versus HR = 2.33, 95% CI: 1.76-3.07). A trend in favor of ANT was observed for intermediate-risk/high-risk patients, particularly for CSS (p = 0.06 [5-year CSS 72.7% versus 60.8%]). CONCLUSIONS: A model based on a combination of easily available clinicopathological factors effectively stratifies patients with resected SQLC into three risk classes.