A Novel Nomogram Construction Method for Multiple Myeloma

Abstract

The present invention provides a method for constructing a multiple myeloma nomogram based on ten gene characteristics, serum β2-microglobulin and LDH, comprising the following steps: S1, obtaining the gene expression profile GSE24080 of MM patients from the GEO database, and Preprocessing the genes in the gene expression profile GSE24080 to obtain the top 25% of the 5413 genes with the largest variance in expression values; S2, performing WGCNA gene co-expression network analysis on the 5413 genes to identify co-expression functions modules; S3, the correlation between the functional modules and clinical information was evaluated by Pearson correlation test to identify the most significant modules; S4, the genes in the most significant modules were univariately evaluated using Cox proportional hazards model Survival analysis, and a scoring model consisting of the 10 best genes was screened by LASSO regression; S5, a novel nomogram based on the scoring model, serum β2M and high LDH was established to predict the 3-year OS and 5 years OS.

Description

technical field [0001] The invention relates to a multiple myeloma nomogram construction method based on ten gene characteristics, serum β2-microglobulin and LDH. Background technique [0002] Multiple myeloma (MM) is a malignant plasma cell disease in which tumor cells originate from plasma cells in the bone marrow, which are cells that develop to the final functional stage of B lymphocytes. At present, the heterogeneity of multiple myeloma has been paid more and more attention. However, no effective and simple MM prognostic model has been established in the world. Contents of the invention [0003] The present invention provides a multiple myeloma nomogram construction method based on ten gene characteristics, serum β2-microglobulin and LDH, which can effectively solve the above problems. [0004] The present invention is achieved like this: [0005] A method for constructing a multiple myeloma nomogram based on ten gene signatures, serum β2-microglobulin and LDH, comp...

AI Technical Summary

Problems solved by technology

At present, the heterogeneity of multiple myeloma has been paid more and more attention, however, no effective and simple MM prognostic model has been established in the world

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