Multi-institutional Development and External Validation of a Nomogram Predicting Recurrence After Curative Liver Resection for Neuroendocrine Liver Metastasis

Objectives: To establish and externally validate a novel nomogram to predict recurrence of patients undergoing curative liver resection for neuroendocrine liver metastasis (NELM). Methods: A total of 279 patients who underwent curative liver resection for NELM identified from an international multicenter database were utilized to develop a nomogram to predict recurrence; 98 cases from two different institutions were used to externally validate the nomogram. Results: Among 279 patients in the development cohort, median age was 57 years, and 50.5% were male. On multivariate analysis, primary tumor location (pancreatic vs nonpancreatic, HR 2.1, p = 0.004), tumor grade (Ref. well, moderate HR 1.9, p = 0.022; poor HR 1.6, p = 0.238), lymph node metastasis (positive vs negative, HR 2.6, p = 0.002), and extent of resection (major vs parenchymal-sparing resection, HR 0.3, p = 0.001) were independently associated with recurrence-free survival. The beta coefficients from the final multivariable model were utilized to develop a nomogram. The nomogram demonstrated good ability to predict risk of recurrence (training cohort, C-index 0.754; validation cohort, C-index 0.748). The calibrated nomogram predicted recurrence-free survival that closely corresponded to actual recurrence. Decision curve analysis demonstrated that the nomogram had a good net benefit for most of the threshold probabilities, especially between 20 and 60%, in both development and validation cohorts. Conclusions: The externally validated novel nomogram predicted 3- and 5-year recurrence-free survival among patients with NELM. Prediction of individual recurrence risk may help guide personalized estimates of prognosis, as well as surveillance protocols and consideration of adjuvant therapies.