Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort

Abstract

Objective This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC). Methods For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves. Results A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718–0.735) and 0.721 (95% CI, 0.709–0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691–0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system. Conclusion We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions.

Prognostic factors and survival prediction of resected non-small cell lung cancer with ipsilateral pulmonary metastases: a study based on the Surveillance, Epidemiology, and End Results (SEER) database

“…Our data suggest that patients over 65 years old have a worse prognosis, which is consistent with other studies on lung cancer [ 20 , 21 ]. However, the prognostic value of age in relation to IPM has been reported differently [ 5 , 6 , 8 – 11 ].…”

Survival analysis and clinicopathological features of patients with stage IA lung adenocarcinoma

“…3) Our external validation group was a single center cohort, in which patients received the same level of diagnosis and treatment, which led to higher homogeneity of the cohort and might result in higher C-index and AUC values. This unusual observation also appeared in some research using the SEER database and nomogram [ 17 ]. According to the recent research, there were 16 existing studies in which a nomogram was constructed to predict the prognosis of stage IA lung cancer patients.…”

“…Besides, as a convenient tool to predict and quantify the probability of an individual patient developing a certain clinical event, nomogram is helpful in clinical decision making, risk stratification, personalized treatment and clinical trial design. Both the SEER database and nomogram have been extensively applied in clinical research [ [15] , [16] , [17] ]. However, nearly all of the current models for Stage IA LUAD patients have not included new statistical factors from the SEER database, such as DTI and Income Level [ 18 , 19 ].…”

Two machine learning-based nomogram to predict risk and prognostic factors for liver metastasis from pancreatic neuroendocrine tumors: a multicenter study

“…Nomograms are widely used for tumor prognosis and recurrence widely, mainly because they allow visualization of statistical prediction models that provide intuitive numerical evaluation of the possibility of incidents (e.g. death or recurrence) [ 9 , 10 ]. For PNET, TNM stage, a classic indicator, still has advantages for pathological staging [ 11 ].…”