• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

用于诊断卵巢癌的卵巢癌评分多中心研究。

Multicenter study of ovarian cancer score for diagnosing ovarian cancer.

作者信息

Wang Haixia, Zhu Jianqing, Zou Dongling, Rao Qunxian, Han Liping, Lu Huaiwu, Wang Junjian, Liu Liya, Ma Lifang, Sun Lu, Yi Lin, Feng Wenlong, Zhang Yanan, Du Ye, Yang Min, Feng Yan, Zhang Dadong, Lin Zhongqiu, Zhou Qi

机构信息

Department of Gynecologic Oncology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China; Chongqing Specialized Medical Research Center of Ovarian Cancer, Chongqing, China; Organoid Transformational Research Center, Chongqing Key Laboratory for the Mechanism and Intervention of Cancer Metastasis, Chongqing University Cancer Hospital, Chongqing, China.

Department of Gynecologic Oncology, Zhejiang Cancer Hospital, Hangzhou, China.

出版信息

Gynecol Oncol. 2025 Feb;193:58-64. doi: 10.1016/j.ygyno.2024.12.017. Epub 2025 Jan 9.

DOI:10.1016/j.ygyno.2024.12.017
PMID:39793443
Abstract

BACKGROUND

Early detection is crucial for improving survival of patients with ovarian cancer (OC), yet current diagnostic tools lack adequate sensitivity and specificity, especially for early stage disease. The study aimed to validate the serum small extracellular vesicles (sEV) protein based Ovarian Cancer Score (OCS) in detecting OC.

METHODS

This multicenter study included 1183 adult females with adnexal masses from four hospitals in China (October 2019-April 2023). Of these, 1024 samples were prospectively collected, and 159 were from biobanks. All serum samples were collected before surgery. The concentrations of sEV carbohydrate antigen 125 (CA125), human epididymis protein 4 (HE4), and complement component 5a protein (C5a) were quantified using chemiluminescence immunoassay and then used for calculating OCS. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

RESULTS

The OCS demonstrated high sensitivity (95.4 %) and specificity (90.4 %) in diagnosis of OC in the prospective cohort (n = 1024) and in total cases (n = 1183, 95.5 % and 90.2 %), with stable performance across menopausal status and FIGO stages. The OCS maintained a high specificity in premenopausal patients (89.6 %) and postmenopausal patients (92.1 %). The OCS showed high sensitivity in early stage epithelial OC (FIGO I: 89.7 %, I + II: 91.4 %), in patients aged ≤45 years (92.7 %), and in patients with normal CA125 levels (72.7 %), although these results were obtained from subgroups with small sample sizes.

CONCLUSION

This multicenter study demonstrated that the OCS is a promising non-invasive diagnostic tool for the detection of OC.

TRIAL REGISTRY

This study was registered at ClinicalTrials.gov: NCT06366997.

摘要

背景

早期检测对于提高卵巢癌(OC)患者的生存率至关重要,但目前的诊断工具缺乏足够的敏感性和特异性,尤其是对于早期疾病。本研究旨在验证基于血清小细胞外囊泡(sEV)蛋白的卵巢癌评分(OCS)在检测OC中的作用。

方法

这项多中心研究纳入了来自中国四家医院的1183名患有附件肿块的成年女性(2019年10月至2023年4月)。其中,前瞻性收集了1024份样本,159份来自生物样本库。所有血清样本均在手术前采集。使用化学发光免疫分析法对sEV糖类抗原125(CA125)、人附睾蛋白4(HE4)和补体成分5a蛋白(C5a)的浓度进行定量,然后用于计算OCS。计算敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)。

结果

OCS在前瞻性队列(n = 1024)和所有病例(n = 1183,95.5%和90.2%)中对OC诊断显示出高敏感性(95.4%)和特异性(90.4%),在绝经状态和国际妇产科联盟(FIGO)分期中表现稳定。OCS在绝经前患者(89.6%)和绝经后患者(92.1%)中保持高特异性。OCS在早期上皮性OC(FIGO I:89.7%,I + II:91.4%)、年龄≤45岁的患者(92.7%)以及CA125水平正常的患者(72.7%)中显示出高敏感性,尽管这些结果来自样本量较小的亚组。

结论

这项多中心研究表明,OCS是一种有前景的用于检测OC的非侵入性诊断工具。

试验注册

本研究已在ClinicalTrials.gov注册:NCT06366997。

相似文献

1
Multicenter study of ovarian cancer score for diagnosing ovarian cancer.用于诊断卵巢癌的卵巢癌评分多中心研究。
Gynecol Oncol. 2025 Feb;193:58-64. doi: 10.1016/j.ygyno.2024.12.017. Epub 2025 Jan 9.
2
Blood biomarkers for the non-invasive diagnosis of endometriosis.用于子宫内膜异位症无创诊断的血液生物标志物。
Cochrane Database Syst Rev. 2016 May 1;2016(5):CD012179. doi: 10.1002/14651858.CD012179.
3
Menopausal status, ultrasound and biomarker tests in combination for the diagnosis of ovarian cancer in symptomatic women.绝经状态、超声和生物标志物联合检测在有症状女性中的卵巢癌诊断。
Cochrane Database Syst Rev. 2022 Jul 26;7(7):CD011964. doi: 10.1002/14651858.CD011964.pub2.
4
Plasma Concentrations of Matrilysins (MMP-7, MMP-26) and Stromelysins (MMP-3, MMP-10) as Diagnostic Biomarkers in High-Grade Serous Ovarian Cancer Patients.基质溶素(MMP - 7、MMP - 26)和基质溶解素(MMP - 3、MMP - 10)的血浆浓度作为高级别浆液性卵巢癌患者的诊断生物标志物
Int J Mol Sci. 2025 Jun 13;26(12):5661. doi: 10.3390/ijms26125661.
5
Monitoring ovarian cancer patients during chemotherapy and follow-up with the serum tumor marker CA125.在化疗期间及随访过程中,通过血清肿瘤标志物CA125对卵巢癌患者进行监测。
Dan Med J. 2018 Apr;65(4).
6
A Clinical Diagnostic Value Analysis of Serum CA125, CA199, and HE4 in Women with Early Ovarian Cancer: Systematic Review and Meta-Analysis.血清 CA125、CA199 和 HE4 对早期卵巢癌患者的临床诊断价值分析:系统评价和荟萃分析。
Comput Math Methods Med. 2022 May 25;2022:9339325. doi: 10.1155/2022/9339325. eCollection 2022.
7
Ovarian cancer recurrence and early detection: may HE4 play a key role in this open challenge? A systematic review of literature.卵巢癌复发与早期检测:HE4 在这一开放性挑战中可能发挥关键作用?文献系统综述。
Med Oncol. 2017 Aug 20;34(9):164. doi: 10.1007/s12032-017-1026-y.
8
Impact of residual disease as a prognostic factor for survival in women with advanced epithelial ovarian cancer after primary surgery.原发性手术后晚期上皮性卵巢癌患者残留病灶对生存预后的影响。
Cochrane Database Syst Rev. 2022 Sep 26;9(9):CD015048. doi: 10.1002/14651858.CD015048.pub2.
9
Intraoperative frozen section analysis for the diagnosis of early stage ovarian cancer in suspicious pelvic masses.术中冰冻切片分析用于诊断可疑盆腔肿块中的早期卵巢癌。
Cochrane Database Syst Rev. 2016 Mar 1;3(3):CD010360. doi: 10.1002/14651858.CD010360.pub2.
10
Combination of the non-invasive tests for the diagnosis of endometriosis.用于诊断子宫内膜异位症的非侵入性检查组合
Cochrane Database Syst Rev. 2016 Jul 13;7(7):CD012281. doi: 10.1002/14651858.CD012281.

引用本文的文献

1
Multimodal Deep Learning Based on Ultrasound Images and Clinical Data for Better Ovarian Cancer Diagnosis.基于超声图像和临床数据的多模态深度学习用于更好地诊断卵巢癌。
J Imaging Inform Med. 2025 Jun 24. doi: 10.1007/s10278-025-01566-8.