Distinguishing lymphoma from benign lymphadenopathy in fever of unknown origin using a diagnostic model based on PET/CT and clinical-laboratory parameters

BACKGROUND: F-FDG PET/CT plays an indispensable role in lymphoma detection, significant metabolic overlap between malignant and benign lymphadenopathy limits its standalone diagnostic accuracy in FUO. Therefore, integrating PET/CT metabolic parameters with clinical features and laboratory markers may improve the differentiation between lymphoma and benign lymphadenopathy, facilitating timely and accurate diagnosis in FUO patients. RESULTS: This study retrospectively analyzed patients with FUO who underwent PET/CT. Lymph nodes were included if their short-axis diameter was ≥ 1 cm on axial CT or if metabolic activity exceeded that of the mediastinal blood pool. Volumes of interest were manually delineated in LIFEx using a 40% SUVmax threshold. Among 203 patients (114 with lymphoma and 89 with benign lymphadenopathy), logistic regression analyses identified independent predictors across three domains: hyperpyrexia, joint pain, and rash among clinical factors; albumin (ALB), procalcitonin (PCT), and serum amyloid A (SAA) among laboratory indicators; and SUVmean, total metabolic tumor volume (TMTV), and total lesion glycolysis (TLG) among PET parameters. A combined model incorporating rash, PCT, SAA, SUVmean, and TMTV achieved superior diagnostic performance, with an area under the ROC curve (AUC) of 0.965, significantly outperforming models based solely on clinical (AUC = 0.790), laboratory (AUC = 0.866), or PET (AUC = 0.845) variables (all P < 0.001). A nomogram was subsequently developed for individualized risk prediction. CONCLUSIONS: Rash, PCT, SAA, SUVmean, and TMTV were independent predictors distinguishing lymphoma from benign lymphadenopathy in FUO. Integrating clinical, laboratory, and PET parameters markedly improved diagnostic accuracy.