ArticleTranslational andrology and urology2020
Development and internal validation of nomograms for the prediction of postoperative survival of patients with grade 4 renal cell carcinoma (RCC).
Article in Translational andrology and urology, 2020. 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, 7 citations in OpenAlex.
- Are We Accurately Predicting Mortality in Renal Cancer? A Systematic Review of Prognostic Models.Journal of clinical medicine · 2025Review
- Identification of ALDOB as a novel prognostic biomarker in kidney clear cell renal cell carcinoma.Heliyon · 2024Article
- Deep learning can predict survival directly from histology in clear cell renal cell carcinoma.PloS one · 2022Article
- Development and validation of a machine learning model to predict the risk of lymph node metastasis in renal carcinoma.Frontiers in endocrinology · 2022Article
- Bioinformatics analysis reveals biomarkers with cancer stem cell characteristics in kidney renal clear cell carcinoma.Translational andrology and urology · 2021Article
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10 authors at 2 institutions in 1 country.
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Abstract
backgroundTo develop successful prognostic models for grade 4 renal cell carcinoma (RCC) following partial nephrectomy and radical nephrectomy.
methodsThe nomograms were established based on a retrospective study of 135 patients who underwent partial and radical nephrectomy for grade 4 RCC at the Department of Urology, Peking University First Hospital from January 2013 to October 2018. The predictive performance of the nomograms was assessed by the calibration plot and C-index. The results were validated using bootstrap resampling.
resultsAspartate transaminase (AST), the maximum diameter of tumor (cutoff value =7 cm), lymph node metastasis, and the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk group were independent factors for determining the overall survival (OS) and cancer-specific survival (CSS) in multivariate analysis. AST, the maximum diameter of the tumor (cutoff value =7 cm), and lymph node metastasis were found to be independent variables for progression-free survival (PFS) in multivariate analysis. These variables were used for the studies to establish nomograms. All calibration plots revealed excellent predictive accuracy of the models. The C-indexes of the nomograms for predicting OS, CSS and PFS were 0.729 (95% CI, 0.659-0.799), 0.725 (95% CI, 0.654-0.796) and 0.702 (95% CI, 0.626-0.778), respectively. Moreover, the recurrence rate was not associated with open or laparoscopic radical nephrectomy in our cohort (P=0.126).
conclusionsWe have developed easy-to-use models that are internally validated to predict postoperative 1-, 3-, and 5-year OS, CSS, and PFS rates of grade 4 RCC patients. The new models could aid in identifying high-risk patients, making postoperative therapeutic and follow-up strategies as well as predicting patients' survival after externally validated. Besides, our study shows that the recurrence rate is not associated with open or laparoscopic radical nephrectomy.
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