Construction and Validation of a Nomogram Based on the Log Odds of Positive Lymph Based on the Log Odds of Positive Lymph Nodes to Predict the Prognosis of Lung Neuroendocrine Tumors

Abstract

AbstractObjectivesThis study aimed to investigate the prognostic value of Log odds of positive lymph nodes (LODDS) for predicting the long-term prognosis of patients with node-positive lung neuroendocrine tumors (LNETs).Materials and MethodsWe collected 506 eligible patients with resected N1/N2 classification LNETs from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. First, we applied the Cox proportional-hazards regression model to evaluate the relationship between LODDS and study endpoints (cancer-specific survival [CSS] and overall survival [OS]) based on the entire cohort. Second, the study cohort was divided into derivation cohort (n=300) and external validation cohort (n=206) based on different geographic regions. Nomograms were constructed and validated based on these two cohorts to predict the 1-, 3- and 5-year survival of patients with LNETs. The accuracy and clinical practicability of nomograms were tested and compared by Harrell’s concordance index (C-index), integrated discrimination improvement (IDI), net reclassification improvement (NRI), calibration plots, and decision curve analyses.ResultsThe Cox proportional-hazards model showed the high LODDS group (-0.33≤LODDS≤1.14) had significantly higher mortality compared to those in the low LODDS group (-1.44 ≤LODDS<-0.33) for both CSS and OS. In addition, besides LODDS, age at diagnosis, histotype, type of surgery, radiotherapy, and chemotherapy were shown as independent predictors in Cox regression analyses and included in the nomograms. The values of c-index, NRI, and IDI indicated that the established nomogram performed significantly better than the conventional eighth edition of the TNM staging system alone. The calibration plots for predictions of the 1-, 3-, and 5-year OS were in excellent agreement. Decision curve analyses showed that the nomogram had value in terms of clinical application.ConclusionsWe created visualized nomograms for CSS and OS of LNET patients, facilitating clinicians to provide highly individualized risk assessment and therapy.