https://jiangyanxiamm.shinyapps.io/MMprognosis/) were built based on the UPS signature and its clinical features. Analyses of calibration plots and decision curves showed clinical utility for both training and validation datasets.

Conclusions: As a result of these results, we established a genetic signature for MM based on UPS. This genetic signature could contribute to improving individualized survival prediction, thereby facilitating clinical decisions in patients with MM." name="description"> A nomogram for predicting prognosis of multiple myeloma patients based on a ubiquitin-proteasome gene signature - Figure f8 | Aging

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Research Paper Volume 14, Issue 24 pp 9951—9968

A nomogram for predicting prognosis of multiple myeloma patients based on a ubiquitin-proteasome gene signature

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Figure 8. Construction of a prognostic nomogram in the training set based on the independent risk factors. (A) Nomogram based on the age, stage, and UPS signature. (B) Calibration plot of the nomogram for the prediction of OS. (C) A time-dependent ROC analysis for 1-, 3-, and 5-years OS prediction. (D) Survival analysis between low-risk and high-risk MM patients. (E) The relative proportion of alive and death cases between two groups. (F) DCA of the nomogram for the prediction of 1-year OS. (G) DCA of the nomogram for the prediction of 3-year OS. (H) DCA of the nomogram for the prediction of 5-year OS.