Evidence map›Paper›PMID 39974418›Full record

ArticleTranslational cancer research2025

A new risk algorithm combining D-dimer and HE4 differentiates borderline tumor from patients with ovarian tumor.

Mi Zhang, Ya Zhang, Guangquan Liu, Lili Ge

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Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mi Zhang *Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China.
Ya Zhang *Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China.
Guangquan LiuDepartment of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China.
Lili GeDepartment of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Timely diagnosis of borderline ovarian tumors (BOTs) is crucial for preserving fertility and ovarian function. However, current markers for detecting BOTs lack effectiveness. This research aims to identify and validate the role of small molecular markers in diagnosing BOTs. Six small molecule markers-human epididymis protein 4 (HE4), carbohydrate antigen 125 (CA125), fibrinogen (FIB), D-dimer (DD), platelet (PLT), and homocysteine (HCY)-were identified as candidate markers. Methods: Candidate markers were evaluated using the receiver operating characteristic (ROC) curve to assess their diagnostic efficacy for BOTs. Suitable markers were chosen through statistical methods to develop a risk prediction model. The model's diagnostic performance was assessed using parameters such as the area under the ROC curve (AUC), Youden index, sensitivity, and specificity. Results: There were significant differences in the levels of HE4, CA125, FIB, and DD between the group of BOTs and benign ovarian tumors. while PLT and HCY levels did not show significant variation. Notably, DD, with an AUC of 0.818, demonstrated utility in diagnosing BOTs. Building on this, a risk prediction model was created based on the diagnostic value of DD and HE4, resulting in an AUC of 0.852, particularly effective in diagnosing serous BOTs (AUC: 0.941). Significant diagnostic value was also observed in ovarian tumors with a diameter less than 4 cm (AUC: 0.772). Conclusions: Changes in DD levels in BOTs patients can be utilized for disease diagnosis, especially when combined with HE4, resulting in improved diagnostic efficiency.

Indexed as

Borderline ovarian tumor (BOT)D-dimer (DD)diagnosisfibrinogen (FIB)human epididymis protein 4 (HE4)

Identifiers

PMID39974418
PMCPMC11833360

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.