Nomograms for predicting long-term overall survival and disease-specific survival of patients with clear cell renal cell carcinoma

Zhang, Guanghao; Wu, Yungang; Zhang, Jiashu; Fang, Zhiqing; Liu, Zhaoxu; Xu, Zhonghua; Fan, Yi‐Ming

doi:10.2147/ott.s171881

Cited by 66 publications

(77 citation statements)

References 59 publications

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“…8 A nomogram is a convenient diagrammatic representation of a mathematical model that combines various key variables to forecast a specific outcome. 9 Nomograms have been widely used to help surgeons develop treatment plans and assess the prognosis of various types of cancer, [10][11][12] and National Comprehensive Cancer Network guidelines have introduced nomograms that perform well. 13 The aim of the present study was to establish a comprehensive prognostic evaluation system for LSCC and validate its prediction accuracy.…”

Section: Introductionmentioning

confidence: 99%

Nomograms for predicting long‐term overall survival and cancer‐specific survival in lip squamous cell carcinoma: A population‐based study

Pan

Yang

et al. 2019

Cancer Medicine

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Background The goal of this study was to establish and validate two nomograms for predicting the long‐term overall survival (OS) and cancer‐specific survival (CSS) in lip squamous cell carcinoma (LSCC). Methods This study selected 4175 patients who were diagnosed with LSCC between 2004 and 2015 in the SEER (Surveillance, Epidemiology, and End Results) database. The patients were allocated randomly to a training cohort and validation cohort. Variables were selected using a backward stepwise method in a Cox regression model. Based on the predictive model with the identified prognostic factors, nomograms were established to predict the 3‐, 5‐, and 8‐year survival OS and CSS rates of LSCC patients. The accuracy of the nomograms was evaluated based on the consistency index (C‐index), while their prediction accuracy was evaluated using calibration plots. Decision curve analyses (DCAs) were used to evaluate the performance of our survival model. Results The multivariate analyses demonstrated that age at diagnosis, marital status, sex, race, American Joint Committee on Cancer stage, surgery status, and radiotherapy status were risk factors for both OS and CSS. The C‐index, area under the time‐dependent receiver operating characteristic curve, and calibration plots demonstrated the good performance of the nomograms. DCAs of both nomograms further showed that they exhibited good 3‐, 5‐, and 8‐year net benefits. Conclusions We have developed and validated LSCC prognosis nomograms for OS and CSS for the first time. These nomograms can be valuable tools for clinical practice when clinicians are helping patients to understand their survival risk for the next 3, 5, and 8 years.

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Section: Introductionmentioning

confidence: 99%

Nomograms for predicting long‐term overall survival and cancer‐specific survival in lip squamous cell carcinoma: A population‐based study

Pan

Yang

et al. 2019

Cancer Medicine

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“…6 and 7). [12] found that age at diagnosis, race, sex, Fuhrman grade, marital status, TNM stage and surgical approach were markedly associated with the prognosis of patients with ccRCC, and they developed nomograms based on the factors mentioned above to predict three-, ve-and 10-year overall and disease-speci c survival. To our knowledge, a disease-speci c survival nomogram for patients with PRCC was constructed by Klatte et al for the rst time [26].…”

Section: Validation Of the Nomogrammentioning

confidence: 99%

“…Many previous studies have proposed methods to assist physicians in treatment decision-making for patients with RCC. The vast majority focus on RCC [9,10] and ccRCC [11,12]. At present, there is a lack of agreement regarding how best to predict the survival prognosis of patients with PRCC.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a nomogram for predicting overall survival in papillary renal cell carcinoma: a retrospective cohort study

Wang

Zhang

Lin

et al. 2020

Preprint

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Background Papillary RCC (PRCC) is the second most common pathological subtype after clear cell RCC (ccRCC), representing 10–20% of treatment of renal tumors. The aim of this study was to establish a reliable nomogram model to evaluate the prognosis of papillary renal cell carcinoma (PRCC) for overall survival (OS). Patients and methods : In total, 6,028 patients with PRCC from the Surveillance, Epidemiology, and End Results (SEER) database were randomly separated into training (n = 4,220) and validation (n = 1,808) cohorts. Cox regression analyses were used to identify the significant variables. A nomogram was established to predict the prognosis of an individual patient with PRCC in terms of OS based on the Cox model. The predictive accuracy of the nomogram model was assessed via discrimination and calibration plots. Results Data of 6,028 patients with PRCC were retrieved from the SEER database. Age at diagnosis, grade, Tumor-Node-Metastasis stage (TNM, AJCC, 7th edition), surgical treatment, tumor number and marital status were the significant independent prognostic variables. All variables were combined to establish a nomogram. Compared to the TNM stage system 7th edition, our nomogram exhibited a favorable discrimination power for OS prediction both in the training and validation cohorts. The calibration curves revealed high consistency between the prognosis prediction of our nomogram and the actual survival. Conclusions The nomogram displayed a excellent performance, suggesting that it could be considered an effective and individualized tool for prognosis prediction of OS in patients with PRCC.

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“…Our aim is to create a graphical representation of a convenient and simple mathematical prediction model that includes multiple factors that contribute to the prognosis of patients with BSCC. Nomogram is a model that combines various important factors to predict a particular endpoint [6]. Nomogram has become a reliable and convenient risk quanti cation tool and is widely used in cancer prognosis [7,8].…”

Section: Introductionmentioning

confidence: 99%

Nomogram for predicting cancer-specific survival of patients with buccal squamous cell carcinoma: a population-based study

Wang

chu²,

Yang

et al. 2020

Preprint

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Background The use of the traditional American Joint Committee on Cancer (AJCC) staging system alone has limitations in predicting the survival of buccal squamous cell carcinoma (BSCC) patients. We aimed to establish a comprehensive prognostic nomogram whose prognostic value compared with AJCC system. Methods Patients were obtained from the SEER (Surveillance, Epidemiology, and End Result) database. The Cox regression model was used to select variables using a backward stepwise selection method. Based on the predictive model for determining prognostic factors, a nomogram was developed to predict the cancer-specific survival rates of BSCC patients at 3, 5 and 8 years. We used several standard model validation methods to evaluate the performance of the survival model: concordance index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), net reclassification improvement (NRI), calibration plots, decision curve analyses (DCAs), and integrated discrimination improvement (IDI). Results Multivariate analysis showed that age, AJCC stage, N stage, M stage, pathological grade, and surgical status were risk factors for survival. The c-index chart, the AUC chart, and the calibration chart show that the performance of the nomogram is better, and the NRI and IDI values show that the performance of the nomogram is better than that of the AJCC staging system. The 3-year, 5-year and 8-year DCA curves of nomogram show that it has more net benefit than traditional AJCC staging system, both in terms of training and validation queues. Conclusion We developed and validated the first BSCC prognosis nomogram, which has a better prognostic value than the separate AJCC staging system. Our BSCC prognosis nomogram is a valuable tool for explaining the risks of the next 3, 5 and 8 years in clinical practice.

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Nomograms for predicting long-term overall survival and disease-specific survival of patients with clear cell renal cell carcinoma

Cited by 66 publications

References 59 publications

Nomograms for predicting long‐term overall survival and cancer‐specific survival in lip squamous cell carcinoma: A population‐based study

Nomograms for predicting long‐term overall survival and cancer‐specific survival in lip squamous cell carcinoma: A population‐based study

Development and validation of a nomogram for predicting overall survival in papillary renal cell carcinoma: a retrospective cohort study

Nomogram for predicting cancer-specific survival of patients with buccal squamous cell carcinoma: a population-based study

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