Predicting prognosis in resected esophageal squamous cell carcinoma using a clinical nomogram and recursive partitioning analysis |
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Authors: | Yuzhen Zheng Shenshen Fu Tiancheng He Qihang Yan Wenyu Di Junye Wang |
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Institution: | 1. Department of Thoracic Surgery, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, PR China;2. Department of Ultrasonography, Guangzhou First People''s Hospital, Guangzhou Medical University, Guangzhou, PR China;3. Department of Thoracic Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation, Guangzhou, Guangdong, PR China |
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Abstract: | BackgroundDevelopment demand of precise medicine in resectable esophageal squamous cell carcinoma (ESCC) require to recognize patients at high risk treated by surgery alone. Thus, our aim was to construct a clinical nomogram and recursive partitioning analysis (RPA) to predict long-term survival in ESCC treated by surgery alone.MethodsBased on the patients with ESCC who treated by three-incisional esophagectomy and two-field lymphadenectomy alone, we identified and integrated significant prognostic factors for survival to build a nomogram. The nomogram was calibrated for overall survival (OS) and the predictive accuracy and discriminative ability was measured by concordance index (c-index) and Akaike information criterion (AIC). Based on the nomogram, the RPA was performed for risk stratification.ResultsA total of 747 patients were included for analysis. Five independent prognostic factors were identified and entered into the nomogram. The calibration curves for probability of 1-, 3-, and 5-year OS showed optimal agreement between nomogram prediction and actual observation. The AIC value of the nomogram was lower than that of the 7th edition staging system, whereas the c-index of the nomogram was higher than that of the 7th edition staging system. The risk groups stratified by RPA allowed significant distinction between survival curves within respective TNM categories.ConclusionThe RPA based on a clinical nomogram appears to be suitable for risk stratification in OS for resected ESCC. This practical system may help clinicians in decision making and design of clinical studies. |
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Keywords: | Esophageal squamous cell carcinoma Prognosis Nomogram Recursive partitioning analysis |
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