Establishment and validation of a prognostic nomogram for patients with distant metastatic gallbladder cancer based on treatment benefits

Abstract

Abstract Purpose Whether different clinical treatments can benefit for the prognosis of patients with distant metastatic gallbladder cancer (GBC), and how to screen the corresponding candidate patients remained unclear. This study aimed to construct and validate a nomogram to predict the prognosis of these patients based on treatment benefits. Methods Patients diagnosed of distant metastatic GBC were retrospectively enrolled from the huge database during 2000 and 2017, and were randomly divided into the training and internal validation cohorts by 7:3. Another patients cohort was retrospectively enrolled from the Second Affiliated Hospital of Nanchang University during 2010 and 2020, and was subsequently used for external validation. Clinical data including various clinical treatment modalities were collected. Univariate and multivariate analyses were used to explore the potential prognostic factors in terms of overall survival and nomograms were constructed. The area under the receiver operating characteristic (ROC) curves (AUC) and the calibration curves were used to evaluate the efficacy of the nomograms. Decision curve analysis (DCA) was used to evaluate the clinical applicability of the nomograms. Results A total of 580 patients with distant metastatic GBC were enrolled from the SEER database, and another 49 patients were enrolled from the authors’ hospital. Age, lymph node dissections, radiotherapy, chemotherapy, T stage, N stage, liver metastasis and bone metastasis were independent prognostic factors, and two nomograms were established based on the above factors including or not including treatment factors. Further nomogram validations showed good prediction efficacy by AUC values and calibration curves, and good clinical applicability by DCA. Conclusion The prognostic nomogram for patients with distant metastatic GBC based on treatment benefits was established with good prediction efficacy and good clinical applicability, which might be of good value for the evaluation of the therapeutic significance for candidate patients.