Li Z Y, Zhang M Y, Zhang X S, Jiang Q
Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Beijing 100044, China.
Zhonghua Xue Ye Xue Za Zhi. 2023 Feb 14;44(2):106-111. doi: 10.3760/cma.j.issn.0253-2727.2023.02.004.
To develop a scoring system to predict molecular responses in patients with chronic myeloid leukemia in the chronic phase (CML-CP) receiving initial imatinib therapy. Data from consecutive adults with newly diagnosed CML-CP treated by initial imatinib was interrogated and subjects were distributed randomly into training and validation cohort, in a ratio of 2∶1. Fine-gray models were applied in the training cohort to identify co-variates of predictive value for major molecular response (MMR) and MR4. A predictive system was built using significant co-variates. The predictive system was then tested in the validation cohort and the area under the receiver-operator characteristic curve (AUROC) was used to estimate accuracy of the predictive system. 1 364 CML-CP subjects receiving initial imatinib were included in this study. Subjects were distributed randomly into training cohort (=909) and validation cohort (=455) . In the training cohort, the male gender, European Treatment and Outcome Study for CML (EUTOS) Long-Term Survival (ELTS) intermediate-risk, ELTS high-risk, high WBC (≥130×10(9)/L or 120×10(9)/L, MMR or MR4) and low HGB (<110 g/L) at diagnosis were significantly related with poor molecular responses and were given points based on their regression coefficients. For MMR, male gender, ELTS intermediate-risk and low HGB (<110 g/L) were given 1 point; ELTS high-risk and high WBC (≥130×10(9)/L) , 2 points. For MR4, male gender was given 1 point; ELTS intermediate-risk and low HGB (<110 g/L) were given 2 points; high WBC (≥120×10(9)/L) , 3 points; ELTS high-risk, 4 points. We divided all subjects into 3 risk subgroups according to the predictive system above. Cumulative incidence of achieving MMR and MR4 in 3 risk subgroups was significantly different in both training and validation cohort (all values <0.001) . In the training and validation cohorts, the time-dependent AUROC ranges of MMR and MR4 predictive systems were 0.70-0.84 and 0.64-0.81, respectively. A scoring system combining gender, WBC, HGB level and ELTS risk was built to predict MMR and MR4 in CML-CP patients receiving initial imatinib therapy. This system had good discrimination and accuracy, which could help phsicians optimize the selsction of initial TKI-therapy.
开发一种评分系统，以预测慢性期慢性髓性白血病（CML-CP）患者接受初始伊马替尼治疗后的分子反应。对接受初始伊马替尼治疗的新诊断CML-CP的连续成年患者的数据进行分析，并将受试者以2∶1的比例随机分配到训练队列和验证队列。在训练队列中应用Fine-gray模型来识别主要分子反应（MMR）和MR4的预测价值协变量。使用显著协变量构建预测系统。然后在验证队列中测试该预测系统，并使用受试者工作特征曲线下面积（AUROC）来估计预测系统的准确性。本研究纳入了1364例接受初始伊马替尼治疗的CML-CP患者。受试者被随机分配到训练队列（n = 909）和验证队列（n = 455）。在训练队列中，男性、欧洲CML治疗与预后研究（EUTOS）长期生存（ELTS）中危、ELTS高危、诊断时高白细胞计数（≥130×10⁹/L或120×10⁹/L，MMR或MR4）和低血红蛋白（<110 g/L）与分子反应不良显著相关，并根据其回归系数给予分数。对于MMR，男性、ELTS中危和低血红蛋白（<110 g/L）给予1分；ELTS高危和高白细胞计数（≥130×10⁹/L）给予2分。对于MR4，男性给予1分；ELTS中危和低血红蛋白（<110 g/L）给予2分；高白细胞计数（≥120×10⁹/L）给予3分；ELTS高危给予4分。根据上述预测系统，我们将所有受试者分为3个风险亚组。在训练队列和验证队列中，3个风险亚组实现MMR和MR4的累积发生率均有显著差异（所有P值<0.001）。在训练队列和验证队列中，MMR和MR4预测系统的时间依赖性AUROC范围分别为0.70 - 0.84和0.64 - 0.81。构建了一个结合性别、白细胞计数、血红蛋白水平和ELTS风险的评分系统，以预测接受初始伊马替尼治疗的CML-CP患者的MMR和MR4。该系统具有良好的区分度和准确性，有助于医生优化初始TKI治疗的选择。
