Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database

Wei Li; Minghang Zhang; Siyun Fu; Xuefeng Hao; Liwei Song; Jinghui Wang; Bin Liu; Shaofa Xu

doi:10.21037/tcr-22-427

Development and validation of a prognostic predictive model of pulmonary spindle cell carcinoma from the surveillance, epidemiology and end results database

Transl Cancer Res. 2022 Aug;11(8):2783-2794. doi: 10.21037/tcr-22-427.

Authors

Wei Li¹, Minghang Zhang¹, Siyun Fu¹, Xuefeng Hao¹, Liwei Song¹, Jinghui Wang¹, Bin Liu¹, Shaofa Xu²

Affiliations

¹ Cancer Research Center, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
² Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.

Abstract

Background: Pulmonary spindle cell carcinoma (PSCC) is a rare type of non-small cell lung cancer (NSCLC). The prognostic influent factors and therapeutic methods of PSCC are unclear, for there are only some case reports or small samples' analysis. This study aims to find prognosis related factors of PSCC, develop and validate a nomogram to predict their survival probability.

Methods: The Surveillance, Epidemiology, and End Results (SEER) 18 Registries database (2000-2018) was searched to study PSCC. According to diagnosed time, data was divided into primary cohort (2000-2015) and validation cohort (2016-2018), both followed until December 31 2018. Chosen by Least Absolute Shrinkage and Selection Operator (LASSO) regression, age, sex, stage, surgery, chemotherapy, N, size and history of malignancy were taken out as predictive variables. The primary cohort was used to develop a nomogram to predict 1-, 3- and 5-year overall survival (OS) probability, and be validated by the validation cohort using concordance index (C-index) and calibration curves. Both cohorts were used to conduct a Cox regression to find the influential factors on OS of PSCC.

Results: The nomogram shows a good concordance and discrimination on the prediction of OS, both internal (n=457 and C-index is 0.79) and external validation (n=100 and C-index is 0.76). The median survival time of PSCC is 4 months, with 20.1% OS possibility in 5 years. Multivariate analysis identified patients of older age [hazard ratio (HR), 1.02; 95% confidence interval (CI): 1.01-1.04], larger size of neoplasm (HR, 1.01; 95% CI: 1.01-1.01), M1 (HR, 2.96; 95% CI: 2.17-4.04), N2 (HR, 2.55; 95% CI: 1.81-3.59) or N3 (HR, 2.99; 95% CI: 1.58-5.66), regional stages (HR, 2.11; 95% CI: 1.29-3.44) and distant stages (HR, 6.17; 95% CI: 3.83-9.94) had a lower OS possibility, while surgery (HR, 0.39; 95% CI: 0.28-0.53) and history of malignancy (HR, 0.68; 95% CI: 0.48-0.98) was protective factors for PSCC. PSCC survived longer with surgery performed instead of chemotherapy or radiotherapy.

Conclusions: Patients of PSCC have a poor prognosis, and using the nomogram developed by this study can predict their 1-, 3- and 5-year OS probability. Surgery is a better choice for PSCC and more studies are necessary to find potential treatment like targeted therapy, programmed death-1 (PD-1) and programmed death ligand 1 (PD-L1).

Keywords: Pulmonary spindle cell carcinoma (PSCC); Surveillance, Epidemiology, and End Results (SEER); prognosis; pulmonary sarcomatoid carcinoma (PSC).