Development and validation of a [18F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients

Objective In this study, based on PET/CT radiomics features, we developed and validated a nomogram to predict progression-free survival (PFS) for cases with diffuse large B cell lymphoma (DLBCL) treated with immunochemotherapy. Methods This study retrospectively recruited 129 cases with DLBCL. Among them, PET/CT scans were conducted and baseline images were collected for radiomics features along with their clinicopathological features. Radiomics features related to recurrence were screened for survival analysis using univariate Cox regression analysis with p < 0.05. Next, a weighted Radiomics-score (Rad-score) was generated and independent risk factors were obtained from univariate and multivariate Cox regressions to build the nomogram. Furthermore, the nomogram was tested for their ability to predict PFS using time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results Blood platelet, Rad-score, and gender were included in the nomogram as independent DLBCL risk factors for PFS. We found that the training cohort areas under the curve (AUCs) were 0.79, 0.84, and 0.88, and validation cohort AUCs were 0.67, 0.83, and 0.72, respectively. Further, the DCA and calibration curves confirmed the predictive nomogram's clinical relevance. Conclusion Using Rad-score, blood platelet, and gender of the DLBCL patients, a PET/CT radiomics-based nomogram was developed to guide cases' recurrence risk assessment prior to treatment. The developed nomogram can help provide more appropriate treatment plans to the cases.