Establishment and validation of prognostic nomograms for patients suffering from metastatic pulmonary large cell neuroendocrine carcinoma

<bold>Background:</bold> This study aimed at developing nomograms that are capable of predicting the survival of patients suffering from metastatic LCNEC. <bold>Methods:</bold> With the use of the SEER database, patients diagnosed with metastatic pulmonary LCNEC were identified in a time scope from 2010 to 2017. Cox regression analyses were conducted to identify independent predictors of cancer-specific survival (CSS). A new nomogram was established in accordance with the above-mentioned notable independent predictors. The concordance index (C-index), receiver operating characteristic curves (ROC), and calibration curves were adopted with the aim of assessing whether the model can be discriminative and reliable. Decision curve analyses (DCAs) were employed for the assessment of the model’s utility and benefits from a clinical perspective. <bold>Results:</bold> This study included 616 patients suffering from metastatic LCNEC in the survival analysis, with 432 patients in the training group and 184 patients in the validation group. Age, T staging, N staging, metastatic sites, radiotherapy, and chemotherapy were identified as the independent prognostic factors. A new prediction model was established and exhibited impressive performance, as confirmed by the C-index, calibration curves, ROC curves, and DCAs. <bold>Conclusion:</bold> A new nomogram was established and then validated for predicting CSS in patients suffering from metastatic LCNEC.