Trial reportFrontiers in public health2021
A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients With Clear Cell Renal Cell Carcinoma: A Population-Based Study.
Trial report in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 12 citations in OpenAlex.
- Evaluating a user-centered design driven multifactorial falls risk assessment tool in primary care: a randomized effectiveness-implementation study.European geriatric medicine · 2026Trial
- Genetic characteristics and clinical-specific survival prediction in elderly patients with gallbladder cancer: a genetic and population-based study.Frontiers in endocrinology · 2023Trial
- A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients Undergoing Surgery With Prostate Cancer: A Population-Based Study.Frontiers in public health · 2022Trial
- Develop and validate nomogram to predict cancer-specific survival for patients with testicular yolk sac tumors.Frontiers in public health · 2022Trial
- Using Decision Tree to Predict Cancer-Specific Mortality in Patients with Clear Cell Renal Cancer Treated with Nephrectomy.Cancers · 2026Article
- Are We Accurately Predicting Mortality in Renal Cancer? A Systematic Review of Prognostic Models.Journal of clinical medicine · 2025Review
- Radiomics predicts the prognosis of patients with clear cell renal cell carcinoma by reflecting the tumor heterogeneity and microenvironment.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Serplulimab Plus Chemotherapy vs Chemotherapy for Treatment of US and Chinese Patients with Extensive-Stage Small-Cell Lung Cancer: A Cost-Effectiveness Analysis to Inform Drug Pricing.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2023Article
- Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients.Frontiers in medicine · 2023Article
- Development and validation of nomograms predicting postoperative survival in patients with chromophobe renal cell carcinoma.Frontiers in oncology · 2022Article
- Analysis and Prediction of the Survival Trends of Patients with Clear-Cell Renal Cell Carcinoma: A Model-Based Period Analysis, 2001-2015.Cancer control : journal of the Moffitt Cancer CenterArticle
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Clear cell renal cell carcinoma (ccRCC) is expected in the elderly and poor prognosis. We aim to explore prognostic factors of ccRCC in the elderly and construct a nomogram to predict cancer-specific survival (CSS) in elderly patients with ccRCC. Methods: Clinicopathological information for all elderly patients with ccRCC from 2004 to 2018 was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Univariate and multivariate Cox regression models were used to identify the independent risk factors for CSS. A new nomogram was constructed to predict CSS at 1-, 3-, and 5 years in elderly patients with ccRCC based on independent risk factors. Subsequently, we used the consistency index (C-index), calibration curves, and the area under the receiver operating curve (AUC) and decision curve analysis (DCA) to test the prediction accuracy of the model. Results: A total of 33,509 elderly patients with ccRCC were enrolled. Univariate and multivariate Cox regression analyses results showed that age, sex, race, marriage, tumor size, histological grade, tumor, nodes, and metastases (TNM) stage, and surgery were independent risk factors for CSS in elderly patients with ccRCC. We constructed a nomogram to predict CSS in elderly patients with ccRCC. The C-index of the training cohort and validation cohort was 0.81 (95% CI: 0.802-0.818) and 0.818 (95% CI: 0.806-0.830), respectively. The AUC of the training cohort and validation cohort also suggested that the prediction model had good accuracy. The calibration curve showed that the observed value of the prediction model was highly consistent with the predicted value. DCA showed good clinical application value of the nomogram. Conclusion: In this study, we explored prognostic factors in elderly patients with ccRCC. We found that age, sex, marriage, TNM stage, surgery, and tumor size were independent risk factors for CSS. We constructed a new nomogram to predict CSS in elderly patients with ccRCC with good accuracy and reliability, providing clinical guidance for patients and physicians.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.