A nomogram prognostic model for large cell lung cancer: analysis from the Surveillance, Epidemiology and End Results Database.

ABSTRACT:

Background

Currently, there is no reliable method for predicting the prognosis of patients with large cell lung cancer (LCLC). The aim of this study was to develop and validate a nomogram model for accurately predicting the prognosis of patients with LCLC.

Methods

LCLC patients, diagnosed from 2007 to 2009, were identified from the Surveillance, Epidemiology and End Results (SEER) database and used as the training dataset. Significant clinicopathologic variables (P<0.05) in a multivariate Cox regression were selected to build the nomogram. The performance of the nomogram model was evaluated by the concordance index (C-index), the area under the curve (AUC), and internal calibration. LCLC patients diagnosed from 2010 to 2016 in the SEER database were selected as a testing dat

SUBMITTER: Lin G 

PROVIDER: S-EPMC7947411 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature