Development and validation of a nomogram for predicting survival time and making treatment decisions for clinical stage IA NSCLC based on the SEER database

The nomogram for the prediction of overall survival after surgery in patients in early-stage NSCLC based on SEER database and external validation cohort

BACKGROUND & AIMS

Currently, there is a lack of effective tools for predicting the prognostic outcome of early-stage lung cancer after surgery. We aim to create a nomogram model to help clinicians assess the risk of postoperative recurrence or metastasis.

MATERIALS AND METHODS

This work obtained 16,459 NSCLC patients based on SEER database from 2010 to 2015. In addition, we also enrolled 385 NSCLC patients (2017/01-2019/06) into external validation cohort at Tianjin Medical University General Hospital. Univariable as well as multivariable Cox regression was carried out for identifying factors independently predicting OS. In addition, we built a nomogram by incorporating the above prognostic factors for the prediction of OS.

RESULTS

Tumor size was positively correlated with the risk of poor differentiation. Advanced age, male and adenocarcinoma patients were factors independently predicting poor prognosis. The risk of white race is higher, followed by Black race, Asians and Indians, which is consistent with previous study. Chemotherapy is negatively related to prognostic outcome in patients of Stage IA NSCLC and positively related to that in those of Stage IB NSCLC. Lymph node dissection can reduce the postoperative mortality of patients. AUCs of the nomograms for 1, 2, and 3-year OS was 0.705, 0.712, and 0.714 for training cohort, while those were 0.684, 0.688, and 0.688 for validation cohort.

CONCLUSIONS

The nomogram could be used as a tool to predict the postoperative prognosis of patients with Stage I non-small cell lung cancer.