A Risk Model and Nomogram to Help in DLBCL Prediction and Prognosis

Researchers developed a risk model to better help predict the prognosis of diffuse large B-cell lymphoma (DLBCL). The findings were published in Expert Review of Hematolgy.

To identify a potential biomarker by analyzing gene expression data, and to predict DLBCL patient’s survival rates, researchers constructed a risk model using mRNA chip data and clinical data of DLBCL patients they obtained from Gene Expression Omnibus (GEO) database.

The risk model comprised five feature genes (CD163, CLEC4A, COL15A1, GABRB2, IFIT3), which were discerned using univariate Cox, LASSO and multivariate Cox regression.

According to the results, the researchers reported that the risk model was capable of independently determining the prognosis of patients, and a nomogram was sequentially established. They concluded that “the risk model and nomogram will help individuals accurately predict the prognosis of DLBCL patients.”