ArticleFrontiers in surgery2022
A Simple-To-Use Nomogram for Predicting Early Death in Metastatic Renal Cell Carcinoma: A Population-Based Study.
Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 4 citations in OpenAlex.
- Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer.Frontiers in public health · 2022Trial
- Prediction model of all-cause death based on balance ability among middle-aged and older Chinese adults of overweight and obesity.Frontiers in public health · 2022Trial
- Application of a predictive model for postoperative pulmonary complications in patients with non-small cell lung cancer based on cardiopulmonary exercise testing.Journal of thoracic disease · 2026Article
- Based on Cardiopulmonary Exercise Testing to Construct and Validate Nomogram of Long-Term Prognosis Within 12 Months for NSCLC.The clinical respiratory journal · 2024Article
- Development and validation of a prognostic nomogram for bone metastasis from lung cancer: A large population-based study.Frontiers in oncology · 2022Article
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Metastatic renal cell carcinoma (mRCC) is usually considered to have a poor prognosis, which has a high risk of early death (≤3 months). Our aim was to developed a predictive nomogram for early death of mRCC. Methods: The SEER database was accessed to obtain the related information of 6,005 mRCC patients between 2010 and 2015. They were randomly divided into primary cohort and validation cohort in radio of 7:3. The optimal cut-off point regarding age at diagnosis and tumor size were identified by the X-tile analysis. Univariate and multivariate logistic regression models were applied to determine significant independent risk factors contributed to early death. A practical nomogram was constructed and then verified by using calibration plots, receiver operating characteristics (ROCs) curve, and decision curve analysis (DCA). Results: There were 6,005 patients with mRCC included in the predictive model, where 1,816 patients went through early death (death within ≤3 months of diagnosis), and among them 1,687 patients died of mRCC. Based on 11 significant risk factors, including age, grade, Conclusions: The nomogram may play a major part in distinguishing the early death of mRCC patients, which can assist clinicians in individualized medicine.
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