ArticleFrontiers in surgery2023
Development and validation of nomograms to predict early death for elderly lung cancer patients.
Article in Frontiers in surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 1 citations in OpenAlex.
- Forecasting the risk of early death among patients suffering from lung cancer with brain metastasis after radiotherapy using interpretable machine learning: a study based on the SEER database.Journal of thoracic disease · 2026Article
- Retrospective analysis of the occurrence pattern of complications and prognostic influencing factors in elderly patients with squamous cell lung cancer after radical surgery.World journal of surgical oncology · 2026Article
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5 authors at 1 institution in 1 country.
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Abstract
Background: Due to the aging of society, the average age of LC (lung cancer) patients has increased in recent years. The purpose of this study was to determine the risk factors and develop nomograms to predict the probability of early death (dead in three months) for elderly (≥ 75 years old) LC patients. Methods: Data of elderly LC patients were obtained from the SEER database by using the SEER stat software. All patients were randomly divided into a training cohort and a validation cohort in a ratio of 7:3. The risk factors of all-cause early and cancer-specific early death were identified by univariate logistic regression and backward stepwise multivariable logistic regression in the training cohort. Then, risk factors were used to construct nomograms. The performance of nomograms was validated by receiver operating curves (ROC), calibration curves, and decision curve analysis (DCA) in the training cohort and validation cohort. Results: A total of 15,057 elderly LC patients in the SEER database were included in this research and randomly divided into a training cohort ( Conclusion: The nomograms were constructed and validated to predict the early death probability of elderly LC patients based on the SEER database. The nomograms were expected to have high predictive ability and good clinical utility, which may help oncologists develop better treatment strategies.
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