ArticleCancer management and research2019
A Novel Preoperative Nomogram for Predicting Lymph Node Invasion in Renal Cell Carcinoma Patients Without Metastasis.
Article in Cancer management and research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Physiological and cellular mechanisms of ischemic preconditioning microRNAs-mediated in underlying of ischemia/reperfusion injury in different organs.Molecular and cellular biochemistry · 2025Review
- The Current Role of Lymph Node Dissection in Nonmetastatic Localized Renal Cell Carcinoma.Journal of clinical medicine · 2023Review
- A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma.Journal of clinical medicine · 2023Article
- Using machine learning to predict lymph node metastasis in patients with renal cell carcinoma: A population-based study.Frontiers in public health · 2023Article
- Potential benefit of lymph node dissection during radical nephrectomy for kidney cancer: A review and critical analysis of current literature.Asian journal of urology · 2022Review
- Development and validation of a machine learning model to predict the risk of lymph node metastasis in renal carcinoma.Frontiers in endocrinology · 2022Article
- The Role of Lymph Node Dissection for Non-Metastatic Renal Cell Carcinoma: An Updated Systematic Review and Meta-Analysis.Frontiers in oncology · 2021Review
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo provide a preoperative predictive model to support clinical decision-making regarding the selection of in renal cell carcinoma (RCC) patients who will benefit the most from lymph node dissection.
methodsThis retrospective analysis enrolled 374 RCC patients without distant metastasis who underwent surgical treatment from January 2006 to December 2017. The relationships between lymph node invasion (LNI) and age at surgery; gender; body mass index(BMI); the presence of clinical symptoms such as flank pain, hematuria or a palpable mass; clinical T stage (cT stage); clinical N stage (cN stage); and the results of routine hematological and serum biochemical analyses were investigated. All the variables were included in univariate and multivariate logistic regression analyses, and the significant variables were then included in a novel nomogram to predict the probability of LNI. Then, we calibrated the nomogram with an internal validation set.
resultsSix of eighteen variables were significant in the univariate logistic regression analysis. After multivariate logistic regression analysis, age at surgery (OR=0.643, 95% CI: 0.421-0.975), cT stage (OR=3.034, 95% CI: 1.541-5.926), cN stage (OR=6.353, 95% CI: 3.273-12.456), lymphocyte percentage (OR=0.481, 95% CI: 0.256-0.894), and the presence of clinical symptoms (OR=2.045, 95% CI: 1.065-3.924) were independent predictors of LNI and were included in the nomogram. The C-index of this nomogram was 0.824.
conclusionPreoperative basic laboratory findings combined with the results of a physical examination and radiological examination can indicate the probability of LNI in RCC patients.
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