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The cause of death was defined according to the SEER mortality cause assignment. The outcome of interest was CSS. The medical records of the patients were randomly (7:3) divided into the training (n=3360) and validation (n=1436) cohorts. The Kaplan-Meier method was used to determine CSS.

The log-rank test was used to compare the CSS rates among the different groups. A logistical Cox regression model was used to select the most useful prognostic markers of CSS. For the AJCC-pathological prognostic group classification, including the tumor stage, node stage, and metastasis stage, only the latter factors were included in the multivariate analysis. Accordingly, a nomogram for the prediction of the individual probability of CSS was developed based on the training cohort. Bootstrap validation (resampling with 1000 iterations) was applied to validate the nomogram, whereas external validation was performed using the validation cohort.

For the model validation, we assessed its discrimination and calibration. Discrimination was measured using the c-index. The statistical analyses were performed, and a two-sided P<0.05 was considered significant. The models, statistical analysis, and figures were prepared using SAS 9.4 software version (Cary, NC) and R 3.5.1 (http://www.cran.r-project.org).

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