Prognostic nomogram predicts overall survival in pulmonary large cell neuroendocrine carcinoma

Yanqi He, Han Liu, Shuai Wang and Yu Chen

PLOS ONE, 2019, vol. 14, issue 9, 1-15

Abstract: Background: Large cell neuroendocrine carcinoma (LCNEC) is a rare and typically aggressive malignancy with poor prognosis. This study developed a nomogram model to predict the overall survival (OS) of patients with LCNEC. Methods: LCNEC patients were identified from the Surveillance, Epidemiology, and End Results database between 2004–2014. Univariate and multivariate Cox regression models were used to determine demographic and clinicopathological features associated with OS. A nomogram model was generated to predict OS and its performance was assessed by Harrell’s concordance index (C-index), calibration plots, and subgroup analysis by risk scores. Results: Of 3048 eligible patients with LCNEC, 2138 were randomly grouped into the training set and 910 into the validation set. Age at diagnosis, gender, tumor stage, N stage, tumor size, and surgery of primary site were independent prognostic factors of OS. C-index values of the nomogram were 0.75 (95% CI, 0.74–0.76) and 0.76 (95% CI, 0.74–0.77) in the training and validation sets, respectively. In both cohorts, the calibration plots showed good concordance between the predicted and observed OS at 3 and 5 years. Kaplan-Meier curves revealed significant differences in OS in patients stratified by nomogram-based risk score, and patients with a higher-than-median risk score had poorer OS. Conclusion: This is the first nomogram developed and validated in a large population-based cohort for predicting OS in patients with LCNEC, and it shows favorable discrimination and calibration abilities. Use of this proposed nomogram has the potential to improve prediction of survival risk, and lead to individualized clinical decisions for LCNEC.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0223275

DOI: 10.1371/journal.pone.0223275

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