A Prognostic Nomogram Based on Log Odds of Positive Lymph Nodes for Patients with Gastroenteropancreatic Neuroendocrine Tumors
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Keywords

Log odds of positive lymph nodes
Online dynamitic nomograms
Overall survival
Cancer-specific survival

DOI

10.26689/par.v8i6.8907

Submitted : 2024-10-23
Accepted : 2024-11-07
Published : 2024-11-22

Abstract

Objective: To explore the prognostic value of log odds of positive lymph nodes (LODDS) in patients with gastroenteropancreatic neuroendocrine tumors (GEPNET) and to develop nomograms based on LODDS for predicting 1-year, 3-year, and 5-year overall survival (OS) and cancer-specific survival (CSS). Methods: This retrospective cohort study was based on the Surveillance, Epidemiology, and End Results (SEER) Program. Demographic data, clinical data, and survival status were extracted, with endpoints of OS and CSS. Multivariate Cox proportional hazards regression analysis assessed predictors associated with OS and CSS, with hazard ratios (HRs) and 95% confidence intervals (CIs) evaluated. Nomogram performance was assessed by calculating the area under the receiver operating characteristic (ROC) curve (AUC). Results: A total of 1,673 patients were included and divided into a training set (n = 1,172) and a testing set (n = 501). Multivariate Cox proportional hazards regression analyses identified LODDS as an independent prognostic factor for OS (HR = 1.79, 95% CI: 1.44–2.24) and CSS (HR = 1.81, 95% CI: 1.41–2.31). The OS and CSS nomograms, developed from multivariate Cox regression analyses, showed good performance, with AUCs of 0.858, 0.878, and 0.852 for predicting 1-year, 3-year, and 5-year OS, and AUCs of 0.859, 0.887, and 0.865 for 1-year, 3-year, and 5-year CSS in the testing set. The nomograms are accessible online (OS: https://zhmte.shinyapps.io/DynNomapp/; CSS: https://zhmty.shinyapps.io/DynNomapp/). Conclusions: LODDS serves as an independent prognostic factor in GEPNET. Online nomograms based on LODDS demonstrated effective performance in predicting OS and CSS in GEPNET patients, providing a convenient tool for clinical application.

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