Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy.
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ABSTRACT:
SUBMITTER: Cao J
PROVIDER: S-EPMC4877645 | biostudies-literature | 2016 May
REPOSITORIES: biostudies-literature
Publications
Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy.
Cao Jinlin J Yuan Ping P Wang Luming L Wang Yiqing Y Ma Honghai H Yuan Xiaoshuai X Lv Wang W Hu Jian J
Scientific reports 20160524
The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resamplin ...[more]
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Project description:BackgroundEsophageal cancer is one of the deadliest malignancies in the world, and 5-year overall survival (OS) of esophageal cancer ranges from 12% to 20%. Surgical resection remains the principal treatment. The American Joint Commission on Cancer (AJCC) TNM (tumor, node, and metastasis) staging system is a key guideline for prognosis and treatment decisions, but it cannot fully predict outcomes. Therefore, targeting the molecular and biological features of each patient's tumor, and identifying key prognostic biomarkers as effective survival predictors and therapeutic targets are highly important to clinicians and patients.MethodsIn this study, three different methods, including Univariate Cox regression, Lasso regression, and Randomforest regression were used to screen the independent factors affecting the prognosis of esophageal squamous cell carcinoma and construct a nomogram prognostic model. The accuracy of the model was verified by comparing with TNM staging system and the reliability of the model was verified by internal cross validation.ResultsPreoperative neutrophil lymphocyte ratio(preNLR), N-stage, p53 level and tumor diameter were selected to construct the new prognostic model. Patients with higher preNLR level, higher N-stage, lower p53 level and larger tumor diameter had worse OS. The results of C-index, Decision Curve Analysis (DCA), and integrated discrimination improvement (IDI) showed that the new prognostic model has a better prediction than the TNM staging system.ConclusionThe accuracy and reliability of the nomogram prognostic model were higher than that of TNM staging system. It can effectively predict individual OS and provide theoretical basis for clinical decision making.
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