Kaplan–Meier (KM) analysis and a two-sided log-rank test were used to determine overall survival in different clusters or in the high- and low-risk groups. Receiver operating curve (ROC) analyses using survivalROC package evaluated the specificity and sensitivity of prognosis prediction. Univariate and multivariate Cox regression analyses were used to evaluate correlation between prognosis and the clinicopathological features in KIRC patients.

An ARG-clinicopathologic nomogram based on multivariate analysis results was used to predict 1-, 3-, and 5-year OS. The nomogram was subjected to 1000 bootstrap resamples for internal validation of the analyzed database. Analysis of nomogram discrimination performance was determined by concordance index (C-index) analysis, which predicts the model's prognostic value. Calibration plots were also used to determine the nomogram's prognostic value. Nomogram calibration for 1-, 3-, and 5-year OS was done by comparing observed survival with the predicted probability. Additionally, a nomogram and calibration curve were developed on R using the package rms. Decision curve analyses (DCAs) were used to determine the nomogram's clinical utility by quantifying net benefit at various threshold probabilities in KIRC patients. DCA for 1-, 3-, and 5-year OS was done using stdca and dca packages. These analyses were done on R (version 3.5.3).

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