Prognostic nomogram and novel risk-scoring system for small cell lung cancer with different patterns of metastases
Hongli Ruan1, Huali Sun2, Yu Guo2
1Department of Emergency Medicine, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, People's Republic of China.
Objective:
This research is aimed to develop the prognostic nomogram and novel risk-scoring system for small cell lung cancer (SCLC) with different patterns of metastases.
Methods:
Data on SCLC patients were extracted from the 2010-2015 Surveillance, Epidemiology, and End Results (SEER) database. This nomogram prognostic model was confirmed in the validation cohort. C-index and calibration curve were used to evaluate the accuracy of nomogram model. The predictive capability and net benefit of nomogram was estimated by decision curve analysis (DCA). The cut-off point of the risk stratification system based on nomogram was assessed by X-tile analysis.
Results:
Our Cox model indicated that age, gender, American Joint Committee on Cancer (AJCC) stage, metastases, chemotherapy, radiation and surgery were independent predictors for OS in SCLC patients. The C-index value of nomogram integrating significant variables for predicting OS in SCLC patients was 0.752 in SEER training set and 0.748 in SEER validation set, respectively. However, the TNM stage only had C-indexes of 0.464 and 0.472 for predicting OS, respectively. The nomogram prognostic model in this study showed higher C-indexes than those in the TNM stage. The C-index value and high quality of calibration plots indicate that the predictive ability of our nomogram model was of great superiority. DCA showed the nomogram had good clinical value. SCLC patients were further divided into low-risk and high-risk group according to nomogram predicted scores.
Conclusion:
Our nomogram model that integrated significant factors can aid as an individualized clinical predictive tool in SCLC patients.
