AI Article Synopsis
- The study investigated factors impacting cancer-specific survival (CSS) and overall survival (OS) in lung squamous cell carcinoma (LSCC) patients and aimed to create prognostic nomograms.
- Data from 23,004 LSCC patients were analyzed using the SEER database, employing Cox regression and Kaplan-Meier methods to evaluate survival variables.
- The resulting nomograms effectively predicted 3-, 5-, and 7-year CSS and OS rates, demonstrating strong discrimination through internal validation methods.
Article Abstract
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.
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| http://dx.doi.org/10.1272/jnms.JNMS.2020_86-610 | DOI Listing |
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