Related Experiment Video
Updated: Dec 31, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Nomograms to Predict Survival in Patients with Lung Squamous Cell Cancer: A Population-Based Study
Rongjiong Zheng1, Xiaolong Gu1, Mingming Wang1
1Department of Pulmonology, Ningbo Yinzhou Second Hospital.
Background:
This study aimed to identify risk factors affecting cancer-specific survival (CSS) and overall survival (OS) in patients with lung squamous cell carcinoma (LSCC) and to develop nomograms for prognostic prediction in these patients.
Methods:
Patients who received an LSCC diagnosis between 2007 and 2013 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic effect of each variable on survival was evaluated with Cox regression and Kaplan-Meier analysis, and nomograms were developed to predict 3-, 5-, and 7-year CSS and OS rates.
Results:
Data from 23,004 patients with LSCC were analyzed. Nomograms were first developed by using variables that were significantly associated with CSS and OS and then validated by using an internal bootstrap resampling approach, which showed that they had a sufficient level of discrimination, according to the C-index.
Conclusions:
The nomograms satisfactorily predicted 3-, 5-, and 7-year CSS and OS rates for patients with LSCC.
More Related Videos
Related Concept Videos
Cancer Survival Analysis
Dosage Regimen Designs: Nomograms and Tabulations
Kaplan-Meier Approach
Comparing the Survival Analysis of Two or More Groups
Statistical Methods for Analyzing Epidemiological Data
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...

