ArticleOncoTargets and therapy2018
Nomograms for predicting long-term overall survival and disease-specific survival of patients with clear cell renal cell carcinoma.
Article in OncoTargets and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
54 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- A systematic investigation of clear cell renal cell carcinoma using meta-analysis and systems biology approaches.Molecular genetics and genomics : MGG · 2024Pooled it
- Pooled it
- Identification of EGFR as a Novel Key Gene in Clear Cell Renal Cell Carcinoma (ccRCC) through Bioinformatics Analysis and Meta-Analysis.BioMed research international · 2019Pooled it
- Development and Validation of a Nomogram to Predict Cancer-Specific Survival in Elderly Patients With Papillary Renal Cell Carcinoma.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
- Development and Validation of a Prognostic Model to Predict Overall Survival for Lung Adenocarcinoma: A Population-Based Study From the SEER Database and the Chinese Multicenter Lung Cancer Database.Technology in cancer research & treatmentTrial
- An explainable clinical-radiomics machine learning model for preoperative prediction of WHO/ISUP nuclear grade in clear cell renal cell carcinoma.Abdominal radiology (New York) · 2026Article
- Survival Prediction for Postoperative Patients With Kidney Cancer Based on Computed Tomography Radiomics: Retrospective Cohort Study.JMIR medical informatics · 2025Article
- Are We Accurately Predicting Mortality in Renal Cancer? A Systematic Review of Prognostic Models.Journal of clinical medicine · 2025Review
- p32 regulates glycometabolism and TCA cycle to inhibit ccRCC progression via copper-induced DLAT lipoylation oligomerization.International journal of biological sciences · 2024Article
- Survival nomogram for patients withCancer pathogenesis and therapy · 2023Article
- Computer tomography-based shape of tumor contour and texture of tumor heterogeneity are independent prognostic indicators for clinical T1b-T2 renal cell carcinoma.World journal of urology · 2023Article
- A radiomics model fusing clinical features to predict microsatellite status preoperatively in colorectal cancer liver metastasis.BMC gastroenterology · 2023Article
- Machine learning for the prediction of cognitive impairment in older adults.Frontiers in neuroscience · 2023Article
- Clear cell renal cell carcinoma: immunological significance of alternative splicing signatures.Frontiers in oncology · 2023Article
- Prognostic Significance ofMolecular imaging and radionuclide therapy · 2022Article
- The Impact of Image Acquisition Parameters and ComBat Harmonization on the Predictive Performance of Radiomics: A Renal Cell Carcinoma Model.Applied sciences (Basel, Switzerland) · 2022Article
- Nomogram for predicting the overall survival of patients with early-onset prostate cancer: A population-based retrospective study.Cancer medicine · 2022Article
- Characterization of Platelet Function-Related Gene Predicting Survival and Immunotherapy Efficacy in Gastric Cancer.Frontiers in genetics · 2022Article
- PI3K/AKT/mTOR Pathway-Associated Genes Reveal a Putative Prognostic Signature Correlated with Immune Infiltration in Hepatocellular Carcinoma.Disease markers · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe aim of this study was to establish comprehensive and practical nomograms, based on significant clinicopathological parameters, for predicting the overall survival (OS) and the disease-specific survival (DSS) of patients with clear cell renal cell carcinoma (ccRCC). PATIENTS AND
methodsThe data of 35,151 ccRCC patients, diagnosed between 2004 and 2014, were obtained from the database of the Surveillance, Epidemiology, and End Results (SEER) program. The Kaplan-Meier method and Cox proportional hazards regression model were used to evaluate the prognostic effects of multiple clinicopathological variables on survival. Based on Cox models, a nomogram was constructed to predict the probabilities of OS and DSS for an individual patient. The predictive performance of nomograms was evaluated using the concordance index (
resultsAccording to univariate and multivariate analyses, age at diagnosis, sex, race, marital status, surgical approach, tumor node metastasis (TNM) stage, and Fuhrman grade significantly correlated with the survival outcomes. These characteristics were used to establish nomograms. The nomograms showed good accuracy in predicting 3-, 5-, and 10-year OS and DSS, with a
conclusionNomograms were developed to predict death from ccRCC treated with nephrectomy. These new prognostic tools could aid in improving the predictive accuracy of survival outcomes, thus leading to reasonable individualized treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.