Development and Validation of a Nomogram for Predicting the Prognosis of Multiple Myeloma Patients

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We used robust rank aggregation (RRA) and weighted gene coexpression network analysis (WGCNA) methods to screen differential genes associated with the international staging system (ISS) stage in multiple myeloma from the gene expression omnibus (GEO) and the cancer genome atlas (TCGA) datasets. Next, a gene signature was established using Cox regression, and its risk stratification ability was analyzed using clinical features, functional cluster, immunophenotypes, genetic mutation, and drug sensitivity analysis for high- and low-risk groups. Finally, a nomogram combining gene signature with clinical feature was constructed, and the stability of the nomogram was demonstrated through internal and external validation.

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