Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Nuclear Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Cancer Res Treat. 2021 Jul;53(3):837-846. doi: 10.4143/crt.2020.123. Epub 2020 Dec 2.
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.
Thirty-seven treatment naïve 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.
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).
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.
目前尚不存在用于 T 细胞淋巴母细胞淋巴瘤（T-LBL）的最佳预后模型。在此，我们探讨了 18F-氟脱氧葡萄糖正电子发射断层扫描-计算机断层扫描（PET-CT）上测量的总代谢肿瘤体积（TMTV）和总病变糖酵解（TLG）的预测价值。
纳入了 37 例初治 T-LBL 患者，他们均接受了 PET-CT 扫描。使用 41%最大标准化摄取值（SUVmax）阈值法获取 TMTV，将代谢肿瘤体积乘以平均 SUV 来测量 TLG。通过 Kaplan-Meier 曲线分析无进展生存期（PFS）和总生存期（OS），并通过对数秩检验进行比较。
SUVmax、TMTV 和 TLG 的最佳截断值分别为 12.7、302cm3 和 890。SUVmax、TMTV 和 TLG 较高提示 PFS 和 OS 较短。多变量分析显示，TMTV≥302cm3 和中枢神经系统（CNS）受累预示着较差的 PFS，而 SUVmax、TLG 和 CNS 受累与较差的 OS 相关。随后，我们构建了一个包含 SUVmax、TMTV 或 TLG 以及 CNS 受累的风险模型，该模型将人群分为低危组、中危组和高危组三个风险组，低危组、中危组和高危组的中位 PFS 分别为未达到、14 个月和 7 个月，差异具有统计学意义（p<0.001）。中位 OS 分别为未达到、27 个月和 13 个月，差异具有统计学意义（p<0.001）。
PET-CT 上测量的基线 SUVmax、TMTV 和 TLG 是 T-LBL 患者预后不良的有力预测指标。将这三个参数与 CNS 受累相结合的风险模型可识别出疾病进展风险高的患者。
