Prognostic nomograms and Aggtrmmns scoring system for predicting overall survival and cancer‐specific survival of patients with kidney cancer
Abstract Background Currently, the prognosis of kidney cancer depends mainly on the pathological grade or tumor stage. Clinicians have few effective tools that can personalize and adequately evaluate the prognosis of kidney cancer patients. Methods A total of 70 481 kidney cancer patients were selec...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-04-01
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| Series: | Cancer Medicine |
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| Online Access: | https://doi.org/10.1002/cam4.2916 |
| _version_ | 1818281861512691712 |
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| author | Yuan Zhou Rentao Zhang Yinman Ding Zhengquan Wang Cheng Yang Sha Tao Chaozhao Liang |
| author_facet | Yuan Zhou Rentao Zhang Yinman Ding Zhengquan Wang Cheng Yang Sha Tao Chaozhao Liang |
| author_sort | Yuan Zhou |
| collection | DOAJ |
| description | Abstract Background Currently, the prognosis of kidney cancer depends mainly on the pathological grade or tumor stage. Clinicians have few effective tools that can personalize and adequately evaluate the prognosis of kidney cancer patients. Methods A total of 70 481 kidney cancer patients were selected from the Surveillance, Epidemiology, and End Results database, among which patients diagnosed in 2005‐2011 (n = 42 890) were used to establish nomograms for overall survival (OS) and cancer‐specific survival (CSS), and those diagnosed in 2012‐2015 (n = 24 591) were used for external validation. Univariate and multivariate Cox analyses were used to determine independent prognostic factors. Concordance index (C‐index), receiver operating characteristic curve, and calibration curve were used to evaluate the predictive capacity of the nomograms. We further reduced subgroup classification and used propensity score matching to balance clinical informations, and analyzed the effect of other variables on survival. We established a new kidney cancer prognostic score system based on the effect of all available variables on survival. Cox proportional hazard model and Kaplan‐Meier curves were used for survival comparison. Results Age, gender, marital status, surgery, grade, T stage, and M stage were included as independent risk factors in the nomograms. The favorable area under the curve (AUC) value (for OS, AUC = 0.812‐0.858; and for CSS, AUC = 0.890‐0.921), internal (for OS, C‐index = 0.776; and for CSS, C‐index = 0.856), and external (for OS, C‐index = 0.814‐0.841; and for CSS, C‐index = 0.894‐0.904) validation indicated that the proposed nomograms could accurately predict 1‐, 3‐, and 5‐year OS and CSS of kidney cancer patients. The Aggtrmmns prognostic scoring system based on age, gender, race, marital status, grade, TNM stage, and surgery of kidney cancer patients could stage patients more explicitly than the AJCC staging system. Conclusion The nomogram and Aggtrmmns scoring system can predict OS and CSS in kidney cancer patients effectively, which may help clinicians personalize prognostic assessments and clinical decisions. |
| first_indexed | 2024-12-13T00:11:51Z |
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| id | doaj.art-fedbd49a81134aaebb6e2dc591901d97 |
| institution | Directory Open Access Journal |
| issn | 2045-7634 |
| language | English |
| last_indexed | 2024-12-13T00:11:51Z |
| publishDate | 2020-04-01 |
| publisher | Wiley |
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| series | Cancer Medicine |
| spelling | doaj.art-fedbd49a81134aaebb6e2dc591901d972022-12-22T00:05:56ZengWileyCancer Medicine2045-76342020-04-01982710272210.1002/cam4.2916Prognostic nomograms and Aggtrmmns scoring system for predicting overall survival and cancer‐specific survival of patients with kidney cancerYuan Zhou0Rentao Zhang1Yinman Ding2Zhengquan Wang3Cheng Yang4Sha Tao5Chaozhao Liang6Department of Urology Surgery The People's Hospital of Xuancheng City Xuancheng ChinaDepartment of Urology Surgery The People's Hospital of Xuancheng City Xuancheng ChinaDepartment of Urology Surgery The People's Hospital of Xuancheng City Xuancheng ChinaDepartment of Urology Surgery The People's Hospital of Xuancheng City Xuancheng ChinaDepartment of Urology Surgery The First Affiliated Hospital of Anhui Medical University Hefei ChinaDepartment of Urology Surgery The People's Hospital of Xuancheng City Xuancheng ChinaDepartment of Urology Surgery The First Affiliated Hospital of Anhui Medical University Hefei ChinaAbstract Background Currently, the prognosis of kidney cancer depends mainly on the pathological grade or tumor stage. Clinicians have few effective tools that can personalize and adequately evaluate the prognosis of kidney cancer patients. Methods A total of 70 481 kidney cancer patients were selected from the Surveillance, Epidemiology, and End Results database, among which patients diagnosed in 2005‐2011 (n = 42 890) were used to establish nomograms for overall survival (OS) and cancer‐specific survival (CSS), and those diagnosed in 2012‐2015 (n = 24 591) were used for external validation. Univariate and multivariate Cox analyses were used to determine independent prognostic factors. Concordance index (C‐index), receiver operating characteristic curve, and calibration curve were used to evaluate the predictive capacity of the nomograms. We further reduced subgroup classification and used propensity score matching to balance clinical informations, and analyzed the effect of other variables on survival. We established a new kidney cancer prognostic score system based on the effect of all available variables on survival. Cox proportional hazard model and Kaplan‐Meier curves were used for survival comparison. Results Age, gender, marital status, surgery, grade, T stage, and M stage were included as independent risk factors in the nomograms. The favorable area under the curve (AUC) value (for OS, AUC = 0.812‐0.858; and for CSS, AUC = 0.890‐0.921), internal (for OS, C‐index = 0.776; and for CSS, C‐index = 0.856), and external (for OS, C‐index = 0.814‐0.841; and for CSS, C‐index = 0.894‐0.904) validation indicated that the proposed nomograms could accurately predict 1‐, 3‐, and 5‐year OS and CSS of kidney cancer patients. The Aggtrmmns prognostic scoring system based on age, gender, race, marital status, grade, TNM stage, and surgery of kidney cancer patients could stage patients more explicitly than the AJCC staging system. Conclusion The nomogram and Aggtrmmns scoring system can predict OS and CSS in kidney cancer patients effectively, which may help clinicians personalize prognostic assessments and clinical decisions.https://doi.org/10.1002/cam4.2916kidney cancernomogramprognostic scoreregional lymph nodeSEERsurvival |
| spellingShingle | Yuan Zhou Rentao Zhang Yinman Ding Zhengquan Wang Cheng Yang Sha Tao Chaozhao Liang Prognostic nomograms and Aggtrmmns scoring system for predicting overall survival and cancer‐specific survival of patients with kidney cancer Cancer Medicine kidney cancer nomogram prognostic score regional lymph node SEER survival |
| title | Prognostic nomograms and Aggtrmmns scoring system for predicting overall survival and cancer‐specific survival of patients with kidney cancer |
| title_full | Prognostic nomograms and Aggtrmmns scoring system for predicting overall survival and cancer‐specific survival of patients with kidney cancer |
| title_fullStr | Prognostic nomograms and Aggtrmmns scoring system for predicting overall survival and cancer‐specific survival of patients with kidney cancer |
| title_full_unstemmed | Prognostic nomograms and Aggtrmmns scoring system for predicting overall survival and cancer‐specific survival of patients with kidney cancer |
| title_short | Prognostic nomograms and Aggtrmmns scoring system for predicting overall survival and cancer‐specific survival of patients with kidney cancer |
| title_sort | prognostic nomograms and aggtrmmns scoring system for predicting overall survival and cancer specific survival of patients with kidney cancer |
| topic | kidney cancer nomogram prognostic score regional lymph node SEER survival |
| url | https://doi.org/10.1002/cam4.2916 |
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