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人附睾蛋白4——一种在卵巢癌诊断中颇具前景的新型血清标志物。

HE4--a novel promising serum marker in the diagnosis of ovarian carcinoma.

作者信息

Langmár Z, Németh M, Vleskó G, Király M, Hornyák L, Bösze P

机构信息

2nd Department of Obstetrics and Gynecology, Semmelweis University, Budapest, Hungary.

出版信息

Eur J Gynaecol Oncol. 2011;32(6):605-10.

PMID:22335019
Abstract

Biomarkers have a wide range of applications in the management of several cancers. To date serum markers have been the most extensively used biomarkers in everyday practice but few markers are elevated in preclinical or premalignant disease, limiting their importance for estimating risk or for screening. Human epididymis protein-4 (HE4) is a novel serum marker which is more sensitive in the prediction of risk of ovarian malignancy than CA125 alone in patients with a pelvic mass. HE4 in combination with CA125 appears to be an effective tool for the early detection of recurrence or monitoring the response to therapy. Risk of Ovarian Malignancy Algorithm, utilizing the dual marker combination of HE4 and CA125, can be used to stratify both postmenopausal and premenopausal women into high- and low-risk groups, allowing for an effective triage of women to appropriate institutions for their care. A review of HE4 and its feasibility as a novel diagnostic tool in the management of epithelial ovarian cancer is presented.

摘要

生物标志物在多种癌症的管理中有着广泛应用。迄今为止,血清标志物是日常实践中使用最为广泛的生物标志物,但在临床前或癌前疾病中,很少有标志物会升高,这限制了它们在评估风险或筛查方面的重要性。人附睾蛋白4(HE4)是一种新型血清标志物,对于盆腔肿块患者,它在预测卵巢恶性肿瘤风险方面比单独使用CA125更为敏感。HE4与CA125联合使用似乎是早期检测复发或监测治疗反应的有效工具。利用HE4和CA125双标志物组合的卵巢恶性肿瘤风险算法,可用于将绝经后和绝经前女性分层为高风险和低风险组,从而有效地将女性分流到合适的机构接受治疗。本文对HE4及其作为上皮性卵巢癌管理中新型诊断工具的可行性进行了综述。

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Exosomal CA125 as A Promising Biomarker for Ovarian Cancer Diagnosis.外泌体CA125作为卵巢癌诊断的一种有前景的生物标志物。
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Could HE4 level measurements during first-line chemotherapy predict response to treatment among ovarian cancer patients?
一线化疗期间 HE4 水平测量能否预测卵巢癌患者的治疗反应?
PLoS One. 2018 Mar 27;13(3):e0194270. doi: 10.1371/journal.pone.0194270. eCollection 2018.
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Can ROMA algorithm stratify ovarian tumor patients better when being based on specific age ranges instead of the premenopausal and postmenopausal status?基于特定年龄范围而非绝经前和绝经后状态时,ROMA算法能否更好地对卵巢肿瘤患者进行分层?
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