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The following is a summary of “A novel prognostic model utilizing TMTV and SUVmax from ¹⁸F-FDG PET/CT for predicting overall survival in patients with extranodal NK/T-cell lymphoma,” published in the March 2025 issue of the BMC Cancer by Wang et al.

The prognostic utility of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in extra-nodal natural killer/T-cell lymphoma (ENKTL) remains a subject of debate. This study aimed to assess the predictive value of key PET/CT metabolic parameters, including maximum standardized uptake value (SUVmax), total metabolic tumor volume (TMTV), and total lesion glycolysis (TLG), and to develop a novel prognostic model for ENKTL. A cohort of 390 patients with comprehensive clinical and survival data was analyzed. Patients received asparaginase-based chemotherapy with or without radiotherapy, or radiotherapy alone. 

Metabolic tumor volume (MTV) was calculated using a 41% SUVmax threshold, and TLG was determined as MTV multiplied by the mean SUV. Kaplan–Meier survival analyses, log-rank tests, and Cox regression models were used to evaluate the association between PET/CT parameters and survival outcomes. The optimal cut-off values for SUVmax (>12.8), TMTV (>16.4 cm³), and TLG (>137.0) were identified using Youden’s index and were significantly associated with worse (OS) (p=0.009) and progression-free survival (PFS) (p=0.003). Multivariate analysis revealed that age >60 years (HR=1.923, 95% CI: 1.001–3.693), presence of B symptoms (HR=1.861, 95% CI: 1.132–3.059), Eastern Cooperative Oncology Group (ECOG) score ≥2 (HR=2.076, 95% CI: 1.165–3.699), extranodal involvement at ≥2 sites (HR=2.349, 95% CI: 1.384–3.988), bone marrow involvement (HR=4.884, 95% CI: 2.137–11.163), SUVmax >12.8 (HR=2.226, 95% CI: 1.260–3.930), and TMTV >16.4 cm³ (HR=1.854, 95% CI: 1.093–3.147) were independent predictors of poor OS. 

A prognostic model incorporating PET/CT metrics and clinical variables was developed, achieving a concordance index (C-index) of 0.772 for OS and 0.750 for PFS in the training set, and 0.777 for OS and 0.696 for PFS in the validation set. The model’s predictive performance was further demonstrated by area under the curve (AUC) values for 1-, 3-, and 5-year OS of 0.841, 0.804, and 0.767 in the training set, and 0.718, 0.786, and 0.893 in the validation set. Risk stratification using the model effectively categorized patients into four distinct survival groups (p<0.001), demonstrating its clinical utility in identifying high-risk individuals. These findings establish SUVmax, TMTV, and TLG as independent prognostic indicators in ENKTL and highlight the value of integrating PET/CT-derived metabolic parameters with clinical factors to refine risk assessment. 

The proposed prognostic model offers a more precise approach for survival prediction and personalized treatment planning, though additional validation in larger, multi-center cohorts is warranted.

Source: bmccancer.biomedcentral.com/articles/10.1186/s12885-025-13725-9