Abstract

Purpose In the present study, we aimed to investigate whether the metabolic parameters on baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) could be used to predict prognosis in peripheral T-cell lymphomas (PTCL). Methods A total of 51 nodal PTCL patients who underwent baseline 18F-FDG PET/CT were retrospectively evaluated in the present study. Total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), and maximum standardized uptake value (SUVmax) were also assessed. Besides, the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) was also included. Log-rank test and Cox regression analysis were used to evaluate progression-free survival (PFS) and overall survival (OS). Results The median follow-up was 18 months. Patients with low TLG, TMTV, and SUVmax levels had a significantly better clinical outcome than those with high TLG, TMTV, and SUVmax levels. The 2-year PFS rates of the high- and low-TMTV groups were 34.62% and 80%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (p < 0.001), whereas the corresponding 2-year OS rates were 46.15% and 84.00%, respectively (n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively, n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively, n = 10), intermediate-risk group with TMTV > 62.405 or NCCN-IPI score of 4-8 (2-year PFS and OS were 52.4% and 66.7%, respectively, Conclusions Baseline TMTV and TLG were independent predictors of PFS and OS in PTCL patients, and SUVmax and NCCN-IPI scores were also independent predictors of OS. Moreover, the combination of TMTV and NCCN-IPI scores improved patient risk-stratification at the initial stage and might contribute to the adjustment of the therapeutic regime. This trial is registered with ChiCTR1900025526.

Highlights

  • Peripheral T-cell lymphoma (PTCL) is a heterogeneous disease that accounts for 5%-10% of all non-Hodgkin lymphomas (NHL) in Western countries and 15-20% of all lymphomas in Asia [1, 2]

  • We aimed to investigate whether the metabolic parameters Total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) could be used to predict prognosis in PTCL

  • A total of 51 PTCL patients who underwent pre-treatment 18F-FDG PET/CT were retrospectively enrolled in this study

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Summary

Introduction

Peripheral T-cell lymphoma (PTCL) is a heterogeneous disease that accounts for 5%-10% of all non-Hodgkin lymphomas (NHL) in Western countries and 15-20% of all lymphomas in Asia [1, 2]. BioMed Research International treatment strategies for nodal PTCL [4, 5]. Most PTCL patients have poor prognosis, with a 5-year overall survival (OS) between 32% and 49% [1, 6]. The International Prognostic Index (IPI) and National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) are the most widely used prognostic indicators for patients with aggressive lymphoma [1, 7,8,9]. They cannot identify this high-risk population [10, 11]. Reliable prognostic factors are needed to better identify populations at high risk

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