A Population-Based Nomogram for Predicting Overall Survival in Pulmonary Sarcomatoid Carcinoma With Real-World External Validation.

BACKGROUND

Pulmonary sarcomatoid carcinoma (PSC) is a rare and highly aggressive tumor. This study aimed to investigate the prognostic factors of PSC and develop a new risk classifier to predict patients' overall survival (OS).

METHODS

This retrospective study consisted of 675 PSC patients registered in the Surveillance, Epidemiology, and End Results (SEER) database, and 90 patients from the First Affiliated Hospital of Xi'an Jiaotong University. The univariate and multivariate Cox regression analyses were adopted to select the best prognostic variables. A nomogram was developed to predict the OS of these patients. The nomogram was assessed using receiver operating characteristic (ROC) curves, the concordance index (C-index), and calibration curves. Decision curve analysis (DCA) was adopted to assess its net clinical benefit. Additionally, a Lasso-Cox regression model was utilized to explore prognostic factors in real-world patients with PSC.

RESULTS

The multivariate analysis revealed that sex, T, N, and M stages, surgery, radiation, chemotherapy, and liver metastasis were independent prognostic factors of OS for patients with PSC, and a nomogram was developed to predict the OS of these patients. The ROC curves and the estimated C-index displayed that the nomogram yielded excellent performance in predicting OS. Calibration curves demonstrated satisfactory consistency between the actual and predicted OS. DCA illustrated that the nomogram would provide significant net clinical benefits. Consistent findings were discovered in the internal and external validation cohorts. Lasso-Cox regression models revealed that surgery and immunotherapy were key protective factors for OS, while ECOG ≥ 2, underlying medical history, and distant metastasis constituted major risk factors for OS.

CONCLUSIONS

The constructed nomogram is a reliable risk classifier to achieve personalized survival probability prediction for patients with PSC. Real-world data suggest that immunotherapy is associated with significantly prolonged survival in patients with PSC.