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血清肿瘤标志物动力学与晚期乳腺癌患者的临床病程

Serum tumor marker kinetics and the clinical course of patients with advanced breast cancer.

作者信息

Sonoo H, Kurebayashi J

机构信息

Department of Endocrine Surgery, Kawasaki Medical School, Okayama, Japan.

出版信息

Surg Today. 1996;26(4):250-7. doi: 10.1007/BF00311583.

Abstract

Serum carcinoembryonic antigens (CEA), CA 15-3, and tissue polypeptide antigens (TPA) have been used in monitoring the clinical course of patients with breast cancer. However, recent reports have suggested that the serial levels of these markers during therapy do not always correlate with the response to therapy. To clarify the usefulness of the serial combination assay of these markers in monitoring the clinical course of patients during therapy, we investigated the relationship between the initial changes and the kinetic patterns of the markers after therapy and the objective responses. When an increase or decrease of over 20% in these markers is taken to be significant, then the initial changes in all three markers significantly correlated with the therapeutic responses (P < 0.01). Five distinct kinetic patterns in the marker levels were observed. A paradoxical kinetic pattern of CEA and CA 15-3 levels--that is, an "initial surge and subsequent drop"--was seen in one-third of the responders. The TPA levels tended to exhibit a "steady decline" pattern in those responders. The sensitivity and specificity of the kinetic patterns to predict the clinical courses were significantly higher than those obtained from the analysis of initial changes. These findings thus suggest that adequate knowledge of the unique kinetics of each marker may help to make a more accurate prediction of the therapeutic responses.

摘要

血清癌胚抗原(CEA)、CA 15 - 3和组织多肽抗原(TPA)已被用于监测乳腺癌患者的临床病程。然而,最近的报告表明,这些标志物在治疗期间的系列水平并不总是与治疗反应相关。为了阐明这些标志物的系列联合检测在监测患者治疗期间临床病程中的有用性,我们研究了治疗后标志物的初始变化和动力学模式与客观反应之间的关系。当这些标志物增加或减少超过20%被视为有意义时,那么所有三种标志物的初始变化与治疗反应显著相关(P < 0.01)。观察到标志物水平有五种不同的动力学模式。在三分之一的缓解者中出现了CEA和CA 15 - 3水平的矛盾动力学模式,即“初始激增随后下降”。在那些缓解者中,TPA水平倾向于呈现“稳定下降”模式。动力学模式预测临床病程的敏感性和特异性显著高于从初始变化分析中获得的敏感性和特异性。因此,这些发现表明,充分了解每种标志物独特的动力学可能有助于更准确地预测治疗反应。

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