Abstract A05: Nomograms based on the SEER database for predicting the prognosis of pulmonary large-cell neuroendocrine carcinoma: A population-based STROBE cohort study

Abstract

Abstract Background: This work aimed at the development and validation of nomograms for predicting patient survival cancer-specific survival (CSS) and overall survival (OS) in the context of pulmonary large-cell neuroendocrine carcinoma (LCNEC). Material and Methods: Based on the SEER database, patients were selected who received diagnosis between the period 2004 and 2014, through the Surveillance, Epidemiology, and End Results (SEER) database. Variables were subjected to univariate and multivariate studies, performed through Cox’s Proportional Hazards Regression model. The 3- and 5-year CSS and OS were predicted based on a nomogram constructed from prognostic factors that were independent. The accuracy of the nomogram was evaluated using discrimination and calibration plots. Results: From 1,837 eligible patients based on the SEER database, assignment of 1,276 patients was done to the training set, while that of 561 patients was done to the validation set. Multivariate analyses revealed that age, laterality, tumor size, N stage, M stage, surgery, and chemotherapy were significant prognostic factors for CSS, while those of OS were age, laterality, tumor size, surgery, N and M stages, chemotherapy, and radiation. The concordance index (C-index) for CSS was 0.781 (95% CI: 0.766-0.796) and 0.754 (95% CI: 0.730-0.778) for the internal and external validations, respectively. The values for OS were 0.791 (95%CI: 0.776-0.806) and 0.775 (95% CI: 0.751-0.799), respectively. For the training and the validation sets, discrimination in terms of prediction of OS and CSS was better in the nomograms against the SEER summary stage as well as AJCC TNM staging systems (6th edition) (P<0.001). The CSS and OS predicted by the nomograms closely corresponded to actual observation as shown by calibration plots. Conclusion: Prediction of the 3- and 5-year CSS and OS of patients with pulmonary LCNEC by nomograms with higher accuracy than existing staging models was demonstrated. Note: This abstract was not presented at the conference. Citation Format: Hong-fen Wu. Nomograms based on the SEER database for predicting the prognosis of pulmonary large-cell neuroendocrine carcinoma: A population-based STROBE cohort study [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A05.