Published online Nov 16, 2022. doi: 10.12998/wjcc.v10.i32.11726
Peer-review started: August 8, 2022
First decision: September 25, 2022
Revised: October 2, 2022
Accepted: October 17, 2022
Article in press: October 17, 2022
Published online: November 16, 2022
Processing time: 91 Days and 22.9 Hours
There is no unified standard to predict postoperative survival in patients with tongue squamous cell carcinoma (TSCC), hence the urgency to develop a model to accurately predict the prognosis of these patients.
To develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) of patients with TSCC.
A cohort of 3454 patients with TSCC from the Surveillance, Epidemiology, and End Results (SEER) database was used to develop nomograms; another inde
Eight variables were selected and used to develop nomograms for patients with TSCC. The C-index (0.741 and 0.757 for OS and CSS in the training cohort and 0.800 and 0.830 in the validation cohort, respectively) and AUC indicated that the discrimination abilities of these nomograms were acceptable. The calibration curves of OS and CSS indicated that the predicted and actual values were consistent in both the training and validation cohorts. The NRI values (training cohort: 0.493 and 0.482 for 3- and 5-year OS and 0.424 and 0.402 for 3- and 5-year CSS; validation cohort: 0.635 and 0.750 for 3- and 5-year OS and 0.354 and 0.608 for 3- and 5-year CSS, respectively) and DCA results indicated that the nomograms were significantly better than the tumor-node-metastasis staging system in predicting the prognosis of patients with TSCC.
Our nomograms can accurately predict patient prognoses and assist clinicians in improving decision-making concerning patients with TSCC in clinical practice.
Core Tip: In order to predict prognosis more accurately and precisely, we used two cohorts to develop nomograms in predicting overall survival and cancer-specific survival of patients with tongue squamous cell carcinoma. We adhered to the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis statement-not only evaluated these nomograms in discrimination, calibration, but also their clinical utility. Additionally, the net reclassification index was also used to assess the accuracy of them. These nomograms provide patients and clinicians with an accurate prognosis, so as to facilitate patient-clinician communications and assist clinicians in improving decision-making.