Difan Zheng1,2, Yiyang Wang3, Yuan Li2,4, Yihua Sun1,2, Haiquan Chen1,2. 1. Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China. 2. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200433, China. 3. Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200433, China. 4. Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Abstract
BACKGROUND: Recently, nomogram has been widely used in cancer prognoses. However, the predicting model for post-chemotherapy patients with resected IIIA non-small cell lung cancer (NSCLC) still remains scarce. Here, we tried to develop nomograms for predicting the recurrence and survival of these patients. METHODS: We retrospectively analyzed our database from October 2007 to May 2013 at Fudan University Shanghai Cancer Center. 437 qualified patients were included. Univariable and multivariable analyses of cox regression were performed successively to select prognostic factors and nomograms for recurrence-free survival (RFS) and overall survival (OS) were developed. Concordance indexes (C-index) and calibration curves were created to measure the consistency between predicted and actual survivals. Finally, risk group stratifications according to risk scores calculated from nomograms were delineated. RESULTS: With a total of 437 patients, five independent prognostic factors related to RFS and two to OS were selected to develop nomograms, respectively. Both 3- and 5-year RFS and OS calibration curves indicated a moderate concordance between the predicted and actual outcomes, consisted with the C-index 0.656 (95% CI: 0.626-0.687) for RFS and 0.651 (95% CI: 0.611-0.691) for OS. Different risk groups showed significant differences in RFS and OS. CONCLUSIONS: We developed nomograms of RFS and OS for predicting recurrence and survival of post-chemotherapy patients with resected IIIA NSCLC. These nomograms could help doctors more easily estimate the prognosis and choose optimal decisions for individual during clinical practices.
BACKGROUND: Recently, nomogram has been widely used in cancer prognoses. However, the predicting model for post-chemotherapy patients with resected IIIA non-small cell lung cancer (NSCLC) still remains scarce. Here, we tried to develop nomograms for predicting the recurrence and survival of these patients. METHODS: We retrospectively analyzed our database from October 2007 to May 2013 at Fudan University Shanghai Cancer Center. 437 qualified patients were included. Univariable and multivariable analyses of cox regression were performed successively to select prognostic factors and nomograms for recurrence-free survival (RFS) and overall survival (OS) were developed. Concordance indexes (C-index) and calibration curves were created to measure the consistency between predicted and actual survivals. Finally, risk group stratifications according to risk scores calculated from nomograms were delineated. RESULTS: With a total of 437 patients, five independent prognostic factors related to RFS and two to OS were selected to develop nomograms, respectively. Both 3- and 5-year RFS and OS calibration curves indicated a moderate concordance between the predicted and actual outcomes, consisted with the C-index 0.656 (95% CI: 0.626-0.687) for RFS and 0.651 (95% CI: 0.611-0.691) for OS. Different risk groups showed significant differences in RFS and OS. CONCLUSIONS: We developed nomograms of RFS and OS for predicting recurrence and survival of post-chemotherapy patients with resected IIIA NSCLC. These nomograms could help doctors more easily estimate the prognosis and choose optimal decisions for individual during clinical practices.
Authors: John L Mikell; Theresa W Gillespie; William A Hall; Dana C Nickleach; Yuan Liu; Joseph Lipscomb; Suresh S Ramalingam; Raj S Rajpara; Seth D Force; Felix G Fernandez; Taofeek K Owonikoko; Rathi N Pillai; Fadlo R Khuri; Walter J Curran; Kristin A Higgins Journal: J Thorac Oncol Date: 2015-03 Impact factor: 15.609
Authors: W van Gijn; R G P M van Stiphout; C J H van de Velde; V Valentini; G Lammering; M A Gambacorta; L Påhlman; K Bujko; P Lambin Journal: Ann Oncol Date: 2015-01-21 Impact factor: 32.976
Authors: Andrea Maurichi; Rosalba Miceli; Tiziana Camerini; Luigi Mariani; Roberto Patuzzo; Roberta Ruggeri; Gianfranco Gallino; Elena Tolomio; Gabrina Tragni; Barbara Valeri; Andrea Anichini; Roberta Mortarini; Daniele Moglia; Giovanni Pellacani; Sara Bassoli; Caterina Longo; Pietro Quaglino; Nicola Pimpinelli; Lorenzo Borgognoni; Daniele Bergamaschi; Catherine Harwood; Odysseas Zoras; Mario Santinami Journal: J Clin Oncol Date: 2014-07-07 Impact factor: 44.544