The Prognosis of Pulmonary Sarcomatoid Carcinoma: Development and Validation of a Nomogram Based on SEER

Abstract

Background: The rarity of pulmonary sarcomatoid carcinoma (PSC) and the lack of prospective clinical trials have led to limited knowledge of its clinical characteristics. This study aimed to evaluate the survival and prognostic factors of PSC and to build a nomogram for clinical practice. Methods: Eligible patients diagnosed from 2010 to 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. We compared the clinical characteristics and survival times of PSC patients with those of lung adenocarcinoma (LADC) and lung squamous cell carcinoma (LSCC) patients. We also used univariate and multivariable Cox regression to estimate mortality hazard ratios among patients with PSC, while a visual nomogram was established to judge the prognosis. Discrimination, calibration, clinical utility, and reproducibility were validated by Harrell's concordance index (C-index), the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results: A total of 400 PSC patients (0.42%) were identified in the SEER database, whereas 58 474 and 33 637 patients were diagnosed with LADC and LSCC, respectively. Age, T stage, grade, surgery, and radiation were shown to be significant prognostic factors in the Cox regression analyses and were included in the nomogram as predictors. The C-index of the nomogram in the validation set was 0.759. The AUC also demonstrated the good performance of the nomogram, and DCA demonstrated its good clinical applicability. Conclusion: We established a novel nomogram to predict the prognosis of PSC, which can help clinicians make tailored decisions and adjust follow-up management strategies, and can provide accurate and individualized survival predictions.