接受酪氨酸激酶抑制剂治疗的慢性髓性白血病患者治疗失败的预测模型。

IF 21 1区 医学 Q1 HEMATOLOGY
Blood Pub Date : 2024-10-31 DOI:10.1182/blood.2024024761
Xiaoshuai Zhang, Bingcheng Liu, Jian Huang, Yanli Zhang, Na Xu, Robert Peter Gale, Weiming Li, Xiaoli Liu, Huanling Zhu, Ling Pan, Yunfan Yang, Hai Lin, Xin Du, Rong Liang, Chunyan Chen, Xiaodong Wang, Guohui Li, Zhuogang Liu, Yanqing Zhang, Zhenfang Liu, Jianda Hu, Chunshui Liu, Fei Li, Wei Yang, Li Meng, Yanqiu Han, Li'e Lin, Zhenyu Zhao, Chuanqing Tu, Caifeng Zheng, Yanliang Bai, Zeping Zhou, Suning Chen, Huiying Qiu, Lijie Yang, Xiuli Sun, Hui Sun, Li Zhou, Zelin Liu, Danyu Wang, Jianxin Guo, Liping Pang, Qingshu Zeng, Xiaohui Suo, Weihua Zhang, Yuanjun Zheng, Xiaojun Huang, Qian Jiang
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引用次数: 0

摘要

尽管酪氨酸激酶抑制剂(TKI)疗法显著提高了慢性期慢性髓性白血病(CML)患者的生存率,但仍有20%-30%的患者治疗失败。欧洲白血病网络(ELN)建议1个中心对1,955名连续接受初始TKI伊马替尼或第二代(2G-)TKI治疗的慢性期CML患者进行诊断,并对这些患者的数据进行了分析,从而建立了TKI治疗失败的临床预测模型。该模型随后在其他 76 个中心的 3,454 名受试者中得到了验证。利用与 TKI 治疗失败相关的预测性临床共变因素,我们建立了一个模型,将受试者分为低、中、高风险亚组,这些亚组的治疗失败累积发生率存在显著差异(p < 0.001)。外部验证数据集具有良好的区分度和校准性,其性能与训练数据集一致。与Sokal和ELTS评分相比,我们的模型具有更好的预测分辨能力,接收者-操作者特征曲线下的时间依赖性面积(AUROC)值更大,重新定义治疗失败风险的能力更强。我们的模型可以帮助医生估计慢性期CML患者初始伊马替尼或2G-TKI治疗失败的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A predictive model for therapy failure in patients with chronic myeloid leukemia receiving tyrosine kinase inhibitor therapy.

Abstract: Although tyrosine kinase inhibitor (TKI) therapy has markedly improved the survival of people with chronic-phase chronic myeloid leukemia (CML), 20% to 30% of people still experienced therapy failure. Data from 1955 consecutive patients with chronic-phase CML diagnosed by the European LeukemiaNet recommendations from 1 center receiving initial imatinib or a second-generation (2G) TKI therapy were interrogated to develop a clinical prediction model for TKI-therapy failure. This model was subsequently validated in 3454 patients from 76 other centers. Using the predictive clinical covariates associated with TKI-therapy failure, we developed a model that stratified patients into low-, intermediate- and high-risk subgroups with significantly different cumulative incidences of therapy failure (P < .001). There was good discrimination and calibration in the external validation data set, and the performance was consistent with that of the training data set. Our model had the better prediction discrimination than the Sokal and European Treatment and Outcome Study long-term survival scores, with the greater time-dependent area under the receiver-operator characteristic curve values and a better ability to redefine the risk of therapy failure. Our model could help physicians estimate the likelihood of initial imatinib or 2G TKI-therapy failure in people with chronic-phase CML.

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来源期刊
Blood
Blood 医学-血液学
CiteScore
23.60
自引率
3.90%
发文量
955
审稿时长
1 months
期刊介绍: Blood, the official journal of the American Society of Hematology, published online and in print, provides an international forum for the publication of original articles describing basic laboratory, translational, and clinical investigations in hematology. Primary research articles will be published under the following scientific categories: Clinical Trials and Observations; Gene Therapy; Hematopoiesis and Stem Cells; Immunobiology and Immunotherapy scope; Myeloid Neoplasia; Lymphoid Neoplasia; Phagocytes, Granulocytes and Myelopoiesis; Platelets and Thrombopoiesis; Red Cells, Iron and Erythropoiesis; Thrombosis and Hemostasis; Transfusion Medicine; Transplantation; and Vascular Biology. Papers can be listed under more than one category as appropriate.
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