Nomograms forecasting long‐term overall and cancer‐specific survival of patients with oral squamous cell carcinoma

Wang, Fengze; Zhang, Hui; Wen, Jiao; Zhou, Jun; Liu, Yuan; Cheng, Bingkun; Chen, Xun; Wei, Jianhua

doi:10.1002/cam4.1216

Cited by 44 publications

(41 citation statements)

References 36 publications

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“…The C‐indexes for the 3‐, 5‐, and 8‐year OS and CSS rates were 0.748 and 0.783, respectively, in the internal validation, and 0.723 and 0.799 in the external validation. All of these C‐indexes exceed 0.7, and there was excellent coherence between the calibration curves and the 45‐degree ideal lines (Figure ) . The plots resembling 45‐degree lines indicate that the nomogram predictions were well calibrated both in the training and verification cohorts (Figures and ).…”

Section: Discussionmentioning

confidence: 69%

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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: Discussionmentioning

confidence: 69%

“…Calibration plotting was used to evaluate the agreement between the actual outcome and the predicted probability. There were two lines in the calibration plots: one was the data line and the other was a 45‐degree reference line; the discrepancy between these two lines reflects the accuracy of a nomogram …”

Section: Methodsmentioning

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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“…Our nomogram indicates that pathological grade is the most important factor, while age is the second most important one [15,16], and there is no signi cant difference between grades I and II. Multivariate analyses indicated that older age was an independent risk variable, with older patients having a lower survival rate [9,17,18]. Meanwhile, a higher AJCC stage was associated with worse survival [9].…”

Section: Discussionmentioning

confidence: 94%

“…We found that age, AJCC stage, N stage, M stage, pathological grade, and surgical status were important risk factors for survival. The accuracy of survival prediction may decrease if these important prognostic parameters are ignored [9].…”

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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“…The level of agreement for the second phase was 88% with a kappa of 0.77. A total of 44 studies remained for the final analysis . The list of excluded papers with the reasons for exclusion can be found in the Supporting Information S3.…”

Section: Methodsmentioning

confidence: 99%

Personalized prognostication in head and neck cancer: A systematic review of nomograms according to the AJCC precision medicine core (PMC) criteria

et al. 2019

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Background The American Joint Committee on Cancer (AJCC) Precision Medicine Core (PMC) has recognized the need for more personalized probabilistic predictions above the “TNM” staging system and has recently released a checklist of inclusion and exclusion criteria for evaluating prognostic models. Methods A systematic review of articles in which nomograms were created for head and neck cancer (HNC) was carried out according to Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines. The AJCC PMC criteria were used to score the individual studies. Results Forty‐four studies were included in the final qualitative analysis. The mean number of inclusion criteria met was 9.3 out of 13, and the mean number of exclusion criteria met was 2.1 out of 3. Studies were generally of high quality, but no single study fulfilled all of the AJCC PMC criteria. Conclusion This is the first study to utilize the AJCC checklist to comprehensively evaluate the published prognostic nomograms in HNC. Future studies should attempt to adhere to the AJCC PMC criteria. Recommendations for future research are given. Summary The AJCC recently released a set of criteria to grade the quality of prognostic cancer models. In this study, we grade all published nomograms for head and neck cancer according to the new guidelines.

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Nomograms forecasting long‐term overall and cancer‐specific survival of patients with oral squamous cell carcinoma

Cited by 44 publications

References 36 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

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

Personalized prognostication in head and neck cancer: A systematic review of nomograms according to the AJCC precision medicine core (PMC) criteria

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