Original Article
A new nomogram from the SEER database for predicting the prognosis of gallbladder cancer patients after surgery
Abstract
Background: To study the prognostic significance in gallbladder cancer (GBC) patients of the four N stage methods of log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and N stage in the 7th and 8th editions of the American Joint Committee on Cancer (AJCC), and to establish a prognostic model of GBC based on LODDS.
Methods: Data of 1,321 patients with GBC who underwent surgical resection of lymph nodes from 2010 to 2014 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. We then randomly divided these data into a training set (n=925) and a validation set (n=396). C-index, Akaike information criterion (AIC), and area under the curve (AUC) were calculated to evaluate the accuracy of LODDS, LNR, and N stage in the 7th and 8th editions of the AJCC. Cox multivariate analysis was performed to determine whether LODDS was an independent prognostic factor, and a nomogram model was established. C-index was used to evaluate the accuracy of the nomogram. A receiver operating characteristic (ROC) curve was drawn and the area under the AUC was calculated to evaluate the accuracy of the nomogram in predicting patients’ 1-, 3-, and 5-year overall survival (OS).
Results: Univariate analysis showed that the four methods were all correlated with OS. Through C-index, AIC and AUC, We found that LODDS had the best accuracy of the four methods. C-index and AUC analysis revealed that the nomogram based on LODDS had excellent prognostic ability. All the results were verified in the validation set.
Conclusions: LODDS is an independent prognostic factor for GBC patients, and it is the best N stage in the SEER database. This new nomogram-containing LODDS system is a great model to predict the prognosis of GBC patients.
Methods: Data of 1,321 patients with GBC who underwent surgical resection of lymph nodes from 2010 to 2014 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. We then randomly divided these data into a training set (n=925) and a validation set (n=396). C-index, Akaike information criterion (AIC), and area under the curve (AUC) were calculated to evaluate the accuracy of LODDS, LNR, and N stage in the 7th and 8th editions of the AJCC. Cox multivariate analysis was performed to determine whether LODDS was an independent prognostic factor, and a nomogram model was established. C-index was used to evaluate the accuracy of the nomogram. A receiver operating characteristic (ROC) curve was drawn and the area under the AUC was calculated to evaluate the accuracy of the nomogram in predicting patients’ 1-, 3-, and 5-year overall survival (OS).
Results: Univariate analysis showed that the four methods were all correlated with OS. Through C-index, AIC and AUC, We found that LODDS had the best accuracy of the four methods. C-index and AUC analysis revealed that the nomogram based on LODDS had excellent prognostic ability. All the results were verified in the validation set.
Conclusions: LODDS is an independent prognostic factor for GBC patients, and it is the best N stage in the SEER database. This new nomogram-containing LODDS system is a great model to predict the prognosis of GBC patients.
