Abstract
AIM: To integrate clinically significant variables related to prognosis after curative resection for gallbladder carcinoma (GBC) into a predictive nomogram. METHODS: One hundred and forty-two GBC patients who underwent curative intent surgical resection at Peking Union Medical College Hospital (PUMCH) were included. This retrospective case study was conducted at PUMCH of the Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC) in China from January 1, 2003 to January 1, 2018. The continuous variable carbohydrate antigen 19-9 (CA19-9) was converted into a categorical variable (cCA19-9) based on the normal reference range. Stages 0 to IIIA were merged into one category, while the remaining stages were grouped into another category. Pathological grade X (GX) was treated as a missing value. A multivariate Cox proportional hazards model was used to select variables to construct a nomogram. Discrimination and calibration of the nomogram were performed via the concordance index (C-index) and calibration plots. The performance of the nomogram was estimated using the calibration curve. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to evaluate the predictive accuracy and net benefit of the nomogram, respectively. RESULTS: Of these 142 GBC patients, 55 (38.7%) were male, and the median and mean age were 64 and 63.9 years, respectively. Forty-eight (33.8%) patients in this cohort were censored in the survival analysis. The median survival time was 20 months. A series of methods, including the likelihood ratio test and Akaike information criterion (AIC) as well as stepwise, forward, and backward analyses, were used to select the model, and all yielded identical results. Jaundice [hazard ratio (HR) = 2.9; 95% confidence interval (CI): 1.60-5.27], cCA19-9 (HR = 3.2; 95%CI: 1.91-5.39), stage (HR = 1.89; 95%CI: 1.16-3.09), and resection (R) (HR = 2.82; 95%CI: 1.54-5.16) were selected as significant predictors and combined into a survival time predictive nomogram (C-index = 0.803; 95%CI: 0.766-0.839). High prediction accuracy (adjusted C-index = 0.797) was further verified via bootstrap validation. The calibration plot demonstrated good performance of the nomogram. ROC curve analysis revealed a high sensitivity and specificity. A high net benefit was proven by DCA. CONCLUSION: A nomogram has been constructed to predict the overall survival of GBC patients who underwent radical surgery from a clinical database of GBC at PUMCH.