scholarly journals Validation of the 8th edition of the AJCC/UICC TNM staging system for tongue squamous cell carcinoma

2018 ◽  
Vol 23 (5) ◽  
pp. 844-850 ◽  
Author(s):  
Satoshi Kano ◽  
Tomohiro Sakashita ◽  
Nayuta Tsushima ◽  
Takatsugu Mizumachi ◽  
Akira Nakazono ◽  
...  
Proceedings ◽  
2019 ◽  
Vol 35 (1) ◽  
pp. 18
Author(s):  
Caponio ◽  
Troiano ◽  
Mascitti ◽  
Santarelli ◽  
Mauceri ◽  
...  

Tongue squamous cell carcinoma (TSCC) accounts for 40% of all squamous cell carcinoma involving the mucosal surface of the oral cavity. TSCC is highly invasive and aggressive and, nowadays, TNM staging system is considered the gold standard in predicting patients’ outcomes. [...]


2019 ◽  
Vol 39 (12) ◽  
Author(s):  
Mei-Di Hu ◽  
Si-Hai Chen ◽  
Yuan Liu ◽  
Ling-Hua Jia

Abstract Background: The present study aimed to develop and validate a nomogram based on expanded TNM staging to predict the prognosis for patients with squamous cell carcinoma of the bladder (SCCB). Methods: A total of 595 eligible patients with SCCB identified in the Surveillance, Epidemiology, and End Results (SEER) dataset were randomly divided into training set (n = 416) and validation set (n = 179). The likelihood ratio test was used to select potentially relevant factors for developing the nomogram. The performance of the nomogram was validated on the training and validation sets using a C-index with 95% confidence interval (95% CI) and calibration curve, and was further compared with TNM staging system. Results: The nomogram included six factors: age, T stage, N stage, M stage, the method of surgery and tumor size. The C-indexes of the nomogram were 0.768 (0.741–0.795) and 0.717 (0.671–0.763) in the training and validation sets, respectively, which were higher than the TNM staging system with C-indexes of 0.580 (0.543–0.617) and 0.540 (0.484–0.596) in the training and validation sets, respectively. Furthermore, the decision curve analysis (DCA) proved that the nomogram provided superior clinical effectiveness. Conclusions: We developed a nomogram that help predict individualized prognosis for patients with SCCB.


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