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Updated: May 23, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Prognostic indicators and nomograms for postoperative survival among younger patients with non-small cell lung cancer
Yi Liu1, Qirui Chen1, Zhirong Zhang1
1Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Background:
Non-small cell lung cancer (NSCLC) diagnosed in younger patients represents a rare and distinct entity within lung cancer, yet prognostic indicators for younger patients surgically treated for NSCLC remain unclear. We aimed to analyze the long-term surgical outcomes in a large cohort and to identify predictors and to develop nomograms for effective survival prediction.
Methods:
The Surveillance, Epidemiology, and End Results (SEER) database [2010-2020] was queried for pathologically confirmed NSCLC cases who underwent cancer-directed surgery. We selected a cutoff age of 49 years or younger to define the younger cohort. The Kaplan-Meier method was used for survival analysis. Cox proportional hazards regression models were used to determine prognostic parameters associated with survival. Nomogram performance was assessed via receiver operating characteristic (ROC) curves and calibration curves in both the training and validation cohort.
Results:
Among the 2,584 younger patients surgically treated for NSCLC meeting the inclusion criteria, the 5-year overall survival (OS) and lung cancer-specific survival (LCSS) rates were 84.3% and 87.0%, respectively. Multivariate analysis identified age, gender, histology, T stage, tumor, node, metastasis (TNM) stage, and postoperative therapy as independent prognosticators. Nomograms exhibited robust predictive performance. The ROC areas for 5-year OS were 0.816 for the training cohort and 0.811 for the validation cohort, while for the 5-year LCSS, the areas were 0.845 and 0.848, respectively. Additionally, the calibration curves demonstrated a high degree of concordance between the actual and predicted values.
Conclusions:
We identified the independent survival factors among younger patients treated surgically for NSCLC and established nomograms for the prediction of the long-term survival, offering valuable insights into clinical decision-making for post-surgical treatment.
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