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Nomograms have become very useful tools among clinicians as they provide individualized predictions based on the characteristics of the patient. For complex design survey data with survival outcome, Binder (1992) proposed methods for fitting survey-weighted Cox models, but to the best of our knowledge there is no available software to build a nomogram based on such models. This paper introduces an R package, SvyNom, to accomplish this goal and illustrates its use on a gastric cancer dataset. Validation and calibration routines are also included.