由年龄、CRP、Ki67 和 POD24 组成的新型血管免疫母细胞 T 细胞淋巴瘤患者预后模型的实用性

Yudi Wang, Suzhen Jia, Yinyan Jiang, Xiubo Cao, Shengchen Ge, Kaiqian Yang, Yi Chen, Kang Yu
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摘要

为了寻找影响AITL患者预后的独立因素,建立一个新的预测模型,并对AITL患者的预后进行分层。我们回顾性分析了温州医科大学附属第一医院自2010年12月至2022年3月期间确诊的86例AITL患者的临床资料。收集并统计分析了患者的临床特征、复发时间和死亡时间。患者的中位年龄为68岁,男女比例为2.2:1。男性和女性在 ECOG PS 评分(P = 0.037)、β2 微球蛋白水平(P = 0.018)和 IgM(P = 0.021)方面存在差异。多变量 COX 回归分析显示,C 反应蛋白为 39.3 mg/L(危险比(HR)为 5.41;P = 0.0001)、年龄为 66 岁(危险比(HR)为 3.06;P = 0.0160)、Ki67 阳性(危险比(HR)为 4.86;P = 0.0010)和诊断后 24 个月(POD24)内疾病早期进展(危险比(HR),12.47;P = 0.0001)是影响 OS 预后的独立因素。KM分析表明,由这四个因素建立的预测模型能有效预测AITL患者的预后(p < 0.0001),ROC曲线显示,新预测模型的预测能力(AUC = 0.909)明显优于传统预测模型,如IPI(AUC = 0.730)、PIT(AUC = 0.720)、PIAI(AUC = 0.715)和AITL评分(AUC = 0.724)。年龄、C反应蛋白、Ki67和POD24是影响OS预后的独立因素。他们建立的预后模型结合了临床特征、血清学和病理学指标,能有效预测AITL患者的预后。
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Prognostic Utility of a Novel Prognostic Model Consisting of Age, CRP, Ki67, and POD24 in Patients with Angioimmunoblastic T-Cell Lymphoma

To find the independent factors affecting the prognosis of AITL patients, establish a novel predictive model, and stratify the prognosis of AITL patients. We retrospectively analyzed the clinical data of 86 patients diagnosed with AITL in the First Affiliated Hospital of Wenzhou Medical University from December 2010 to March 2022. The clinical features, recurrence time, and death time of patients were collected and analyzed statistically. The median age of our patients was 68 years old, and the male-to-female ratio was 2.2: 1. There are differences between males and females in ECOG PS score (p = 0.037), β2 microglobulin levels (p = 0.018) and IgM (p = 0.021). Multivariate COX regression analysis showed that C-reactive protein > 39.3 mg/L (hazard ratio (HR), 5.41; p = 0.0001), Age > 66 years (hazard ratio (HR), 3.06; p = 0.0160), Ki67 positive (hazard ratio (HR), 4.86; p = 0.0010) and early progression of disease within 24 months (POD24) after diagnosis (hazard ratio (HR), 12.47; p = 0.0001) were independent factors affecting the prognosis of OS. KM analysis showed that the predictive model established by these four factors could effectively predict the prognosis of patients with AITL (p < 0.0001), and the ROC curve showed that the predictive ability of the new predictive model (AUC = 0.909) was significantly better than that of the traditional predictive models, such as IPI (AUC = 0.730), PIT (AUC = 0.720), PIAI (AUC = 0.715) and AITL score (AUC = 0.724). Age, C-reactive protein, Ki67, and POD24 were independent factors affecting the prognosis of OS. The prognostic model established by them combined clinical features, and serological and pathological indicators and could effectively predict the prognosis of AITL patients.

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期刊介绍: Indian Journal of Hematology and Blood Transfusion is a medium for propagating and exchanging ideas within the medical community. It publishes peer-reviewed articles on a variety of aspects of clinical hematology, laboratory hematology and hemato-oncology. The journal exists to encourage scientific investigation in the study of blood in health and in disease; to promote and foster the exchange and diffusion of knowledge relating to blood and blood-forming tissues; and to provide a forum for discussion of hematological subjects on a national scale. The Journal is the official publication of The Indian Society of Hematology & Blood Transfusion.
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