ArticleBMC medical imaging2026
Predicting overall survival after initial chemotherapy for diffuse large B-cell lymphoma using CT nomogram analysis.
Article in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesThe study aims to evaluate the potential value of a CT nomogram in predicting overall survival in patients with diffuse large B-cell lymphoma (DLBCL) after initial chemotherapy.
methodsA retrospective analysis was conducted on the CT images and clinical data of DLBCL patients who received chemotherapy from January 2013 to May 2018. A total of 130 patients were included and randomly divided into a training cohort (n = 91) and a validation cohort (n = 39) at a 7:3 ratio. CT radiomics features were extracted, and the Rad-score was calculated using the least absolute shrinkage and selection operator (LASSO) algorithm. Independent clinical risk factors were identified using univariate and multivariate Cox regression, and then a nomogram model was developed jointly with the Rad-score. The operating characteristic curve (ROC), calibration curve, and decision curve assessments were utilized to assess the model’s predicting performance.
resultsThe 15 radiomics features highly correlated with OS in DLBCL patients were identified and used to calculate the Rad-score. A nomogram model was constructed by combining Rad-score with independent risk factors (Ann Arbor staging, International Prognostic Index (IPI) score, Karnofsky performance status (KPS), effectiveness) based on multivariate analysis. In the training and validation cohorts, the AUC values of the nomogram model for predicting 3 and 5 years OS were 0.860 and 0.810, respectively, 0.838 and 0.816, respectively, which were higher than the Rad-score model (0.744 and 0.763, respectively, 0.787 and 0.562, respectively). Furthermore, the calibration and decision curve evaluations revealed that the nomogram model provided accurate predictions and had high clinical utility in predicting OS in DLBCL patients.
conclusionThe nomogram model combined with clinical characteristics and Rad-score provides a good prediction of OS in DLBCL patients.
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