BACKGROUND There are few effective tools to predict survival in patients with invasive intraductal papillary mucinous neoplasms of the pancreas.AIM To develop comprehensive nomograms to individually estimate the survi...BACKGROUND There are few effective tools to predict survival in patients with invasive intraductal papillary mucinous neoplasms of the pancreas.AIM To develop comprehensive nomograms to individually estimate the survival outcome of patients with invasive intraductal papillary mucinous neoplasms of the pancreas.METHODS Data of 1219 patients with invasive intraductal papillary mucinous neoplasms after resection were extracted from the Surveillance,Epidemiology,and End Results database,and randomly divided into the training(n=853)and the validation(n=366)cohorts.Based on the Cox regression model,nomograms were constructed to predict overall survival and cancer-specific survival for an individual patient.The performance of the nomograms was measured according to discrimination,calibration,and clinical utility.Moreover,we compared the predictive accuracy of the nomograms with that of the traditional staging system.RESULTS In the training cohort,age,marital status,histological type,T stage,N stage,M stage,and chemotherapy were selected to construct nomograms.Compared with the American Joint Committee on Cancer 7th staging system,the nomograms were generally more discriminative.The nomograms passed the calibration steps by showing high consistency between actual probability and nomogram prediction.Categorial net classification improvements and integrated discrimination improvements suggested that the predictive accuracy of the nomograms exceeded that of the American Joint Committee on Cancer staging system.With respect to decision curve analyses,the nomograms exhibited more preferable net benefit gains than the staging system across a wide range of threshold probabilities.CONCLUSION The nomograms show improved predictive accuracy,discrimination capability,and clinical utility,which can be used as reliable tools for risk classification and treatment recommendations.展开更多
基金Supported by National Natural Science Foundation of China,No.81702270the Natural Science Foundation of Guangdong,No.2015A030313827The Affiliated Hospital of Guangdong Medical University Clinical Research Program,No.LCYJ2018C012
文摘BACKGROUND There are few effective tools to predict survival in patients with invasive intraductal papillary mucinous neoplasms of the pancreas.AIM To develop comprehensive nomograms to individually estimate the survival outcome of patients with invasive intraductal papillary mucinous neoplasms of the pancreas.METHODS Data of 1219 patients with invasive intraductal papillary mucinous neoplasms after resection were extracted from the Surveillance,Epidemiology,and End Results database,and randomly divided into the training(n=853)and the validation(n=366)cohorts.Based on the Cox regression model,nomograms were constructed to predict overall survival and cancer-specific survival for an individual patient.The performance of the nomograms was measured according to discrimination,calibration,and clinical utility.Moreover,we compared the predictive accuracy of the nomograms with that of the traditional staging system.RESULTS In the training cohort,age,marital status,histological type,T stage,N stage,M stage,and chemotherapy were selected to construct nomograms.Compared with the American Joint Committee on Cancer 7th staging system,the nomograms were generally more discriminative.The nomograms passed the calibration steps by showing high consistency between actual probability and nomogram prediction.Categorial net classification improvements and integrated discrimination improvements suggested that the predictive accuracy of the nomograms exceeded that of the American Joint Committee on Cancer staging system.With respect to decision curve analyses,the nomograms exhibited more preferable net benefit gains than the staging system across a wide range of threshold probabilities.CONCLUSION The nomograms show improved predictive accuracy,discrimination capability,and clinical utility,which can be used as reliable tools for risk classification and treatment recommendations.
