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

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.