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학술저널
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Xiaoyan Feng (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Xin Wen (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Ling Li (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Zhenchang Sun (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Xin Li (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Lei Zhang (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Jingjing Wu (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Xiaorui Fu (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Xinhua Wang (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Hui Yu (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Xinran Ma (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Xudong Zhang (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Xinli Xie (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Xingmin Han (The First Affiliated Hospital of Zhengzhou University Zhengzhou China) Mingzhi Zhang (The First Affiliated Hospital of Zhengzhou University Zhengzhou China)
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대한암학회 Cancer Research and Treatment Cancer Research and Treatment 제53권 제3호
발행연도
2021.1
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837 - 846 (10page)

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Purpose There is no optimal prognostic model for T-cell lymphoblastic lymphoma (T-LBL). Here, we discussed the predictive value of total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) measured on 18F-fluorodeoxyglucose positron emission tomography?computed tomography (PET-CT) in T-LBL.Materials and Methods Thirty-seven treatment naive T-LBL patients with PET-CT scans were enrolled. TMTV was obtained using the 41% maximum standardized uptake value (SUVmax) threshold method, and TLG was measured as metabolic tumor volume multiplied by the mean SUV. Progression-free survival (PFS) and overall survival (OS) were analyzed by Kaplan-Meier curves and compared by the log-rank test.Results The optimal cutoff values for SUVmax, TMTV, and TLG were 12.7, 302 cm3, and 890, respectively. A high SUVmax, TMTV, and TLG indicated a shorten PFS and OS. On multivariable analysis, TMTV ≥ 302 cm3, and central nervous system (CNS) involvement predicted inferior PFS, while high SUVmax, TLG and CNS involvement were associated with worse OS. Subsequently, we generated a risk model comprising high SUVmax, TMTV or TLG and CNS involvement, which stratified the population into three risk groups, which had significantly different median PFS of not reached, 14 months, and 7 months for low-risk group, mediate-risk group, and high-risk group, respectively (p < 0.001). Median OS were not reached, 27 months, and 13 months, respectively (p < 0.001).Conclusion Baseline SUVmax, TMTV, and TLG measured on PET-CT are strong predictors of worse outcome in T-LBL. A risk model integrating these three parameters with CNS involvement identifies patients at high risk of disease progression.

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