Applying nomograms based on the surveillance, epidemiology and end results database to predict long-term overall survival and cancer-specific survival in patients with oropharyngeal squamous cell carcinomas

Wang, Fengze; Wen, Jiao; Yang, Xinjie; Jia, Tingting; Du, Fangchong; Wei, Jianhua

doi:10.1097/md.0000000000020703

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…Nomogram can transform the independent risk factors from Cox regression survival analysis into visual graphics [12], which was widely applied to conduct personalized prognosis evaluation including prostate cancer [13], pulmonary adenocarcinoma [14], oral squamous cell carcinoma [15], oropharyngeal squamous cell carcinoma [16]. Most importantly, the 8th version of the AJCC staging manual recommended that the future version would embrace the nomogram to realize the pursuit of personalized medicine [17].…”

Section: Open Accessmentioning

confidence: 99%

Nomogram predicting long-term overall and cancer-specific survival of patients with buccal mucosa cancer

et al. 2022

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Background Few models about the personalized prognosis evaluation of buccal mucosa cancer (BMC) patients were reported. We aimed to establish predictive models to forecast the prognosis of BMC patients. Methods The complete clinicopathological information of BMC patients from the surveillance, epidemiology and end results program was collected and reviewed retrospectively. Two nomograms were established and validated to predict long-term overall survival (OS) and cancer-specific survival (CSS) of BMC patients based on multivariate Cox regression survival analysis. Results 1155 patients were included. 693 and 462 patients were distributed into modeling and validation groups with 6:4 split-ratio via a random split-sample method. Based on the survival analysis, independent prognostic risk factors (variables that can be used to estimate disease recovery and relapse chance) influencing OS and CSS were obtained to establish nomograms. Then, we divided the modeling group into high- and low-risk cohorts. The low-risk cohort had improved OS and CSS compared to the high-risk cohort, which was statistically significant after the Log-rank test (p < 0.05). Furthermore, we used the concordance index (C-index), calibration curve to validate the nomograms, showing high accuracy. The decision curve analyses (DCA) revealed that the nomograms had evident clinical value. Conclusions We constructed two credible nomogram models, which would give the surgeons reference to provide an individualized assessment of BMC patients.

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Section: Open Accessmentioning

confidence: 99%

Nomogram predicting long-term overall and cancer-specific survival of patients with buccal mucosa cancer

et al. 2022

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“…Currently, nomograms are widely used to transform the above clinicopathological parameters into a visualized graph and conveniently predict long-term 5- and 8-year survival [ 8 ]. To evaluate accuracy, the concordance index (C-index), receiver operating characteristic (ROC) and calibration curve were applied [ 21 , 22 , 23 ]. The results show that the two nomograms had a high discrimination (all the C-index > 0.7), high sensitivity and specificity (all the AUC > 0.7).…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of Nomograms Predicting the 5- and 8-Year Overall and Cancer-Specific Survival of Bladder Cancer Patients Based on SEER Program

Wen¹,

Wen²,

Huang

et al. 2023

JCM

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Background: Bladder cancer is often prone to recurrence and metastasis. We sought to construct nomogram models to predict the overall survival (OS) and cancer-specific survival (CSS) of bladder cancer patients. Methods: A reliable random split-sample approach was used to divide patients into two groups: modeling and validation cohorts. Uni-variate and multivariate survival analyses were used to obtain the independent prognostic risk factors based on the modeling cohort. A nomogram was constructed using the R package, “rms”. Harrell’s concordance index (C-index), calibration curves and receiver operating characteristic (ROC) curves were applied to evaluate the discrimination, sensitivity and specificity of the nomograms using the R packages “hmisc”, “rms” and “timeROC”. A decision curve analysis (DCA) was used to evaluate the clinical value of the nomograms via R package “stdca.R”. Results: 10,478 and 10,379 patients were assigned into nomogram modeling and validation cohorts, respectively (split ratio ≈ 1:1). For OS and CSS, the C-index values for internal validation were 0.738 and 0.780, respectively, and the C-index values for external validation were 0.739 and 0.784, respectively. The area under the ROC curve (AUC) values for 5- and 8-year OS and CSS were all greater than 0.7. The calibration curves show that the predicted probability values of 5- and 8-year OS and CSS are close to the actual OS and CSS. The decision curve analysis revealed that the two nomograms have a positive clinical benefit. Conclusion: We successfully constructed two nomograms to forecast OS and CSS for bladder cancer patients. This information can help clinicians conduct prognostic evaluations in an individualized manner and tailor personalized treatment plans.

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Survival comparison of different histological subtypes of oropharyngeal squamous cell carcinoma: A propensity-matched score analysis based on SEER database

Wang

Xiang

et al. 2022

Ear Nose Throat J

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Objective The purpose of this study was to analyze the difference of survival rates in paitents with oropharyngeal keratinizing squamous cell carcinoma (KSCC), nonkeratinizing squamous cell carcinoma (NKSCC), basaloid squamous cell carcinoma (BSCC), and papillary squamous cell carcinoma (PSCC). Materials and methods Patients diagnosed with oropharyngeal squamous cell carcinoma between 2004 and 2015 were collected from the SEER database. Cox proportional hazards models and Kaplan–Meier curves were used for survival analysis. Propensity score matching (PSM) was performed to adjust for the effect of confounding variables. Due to the small sample size of PSCC, this study did not perform PSM between it and other subtypes. Results The 5-year cancer-specific survival (CSS) rate of PSCC was higher than that of KSCC, NKSCC, and BSCC (0.627 vs. 0.812 vs. 0.789 vs. 0.875, P < 0.05); And the CSS rate of KSCC was lower than that of other subtypes both before and after PSM. In addition, the 5-year and 10-year CSS rates of BSCC were not different from NKSCC ( P > 0.05), but not as good as NKSCC in the long term ( P = 0.028). After PSM, the 5-year, 10-year, and long-term prognosis of BSCC were significantly worse than those of NKSCC ( P < 0.001). Conclusion The 5-year CSS of PSCC was better than the other three subtypes. The short-term prognosis of BSCC was not significantly different from NKSCC, but the long-term survival was lower than that of NKSCC, and the difference was more obvious after PSM. Meanwhile, the prognosis of KSCC was worst.

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Applying nomograms based on the surveillance, epidemiology and end results database to predict long-term overall survival and cancer-specific survival in patients with oropharyngeal squamous cell carcinomas

Cited by 3 publications

References 33 publications

Nomogram predicting long-term overall and cancer-specific survival of patients with buccal mucosa cancer

Nomogram predicting long-term overall and cancer-specific survival of patients with buccal mucosa cancer

Development and Validation of Nomograms Predicting the 5- and 8-Year Overall and Cancer-Specific Survival of Bladder Cancer Patients Based on SEER Program

Survival comparison of different histological subtypes of oropharyngeal squamous cell carcinoma: A propensity-matched score analysis based on SEER database

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