ArticleInternational journal of molecular sciences2019
An Improved Prediction Model for Ovarian Cancer Using Urinary Biomarkers and a Novel Validation Strategy.
Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Urinary biomarkers for the detection of ovarian cancer: a systematic review.Carcinogenesis · 2022Pooled it
- Depressive symptoms and chronic disease trajectories and predictors in middle-aged and older adults in China: An eight-year multi-trajectory analysis.Global health & medicine · 2025Article
- Review
- Article
- Effect of Serum Level of Human Epididymis Protein 4 and Interleukin-6 as Biomarkers in Patients with Adnexal Mass.Archives of Razi Institute · 2022Article
- A Novel Stool Methylation Test for the Non-Invasive Screening of Gastric and Colorectal Cancer.Frontiers in oncology · 2022Article
- Proteome Analysis of Urinary Biomarkers in a Bovine IRBP-Induced Uveitis Rat ModelFrontiers in molecular biosciences · 2022Article
- Review
- WFDC Protein: A Promising Diagnosis Biomarker of Ovarian Cancer.Journal of Cancer · 2021Review
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
Abstract
This study was designed to analyze urinary proteins associated with ovarian cancer (OC) and investigate the potential urinary biomarker panel to predict malignancy in women with pelvic masses. We analyzed 23 biomarkers in urine samples obtained from 295 patients with pelvic masses scheduled for surgery. The concentration of urinary biomarkers was quantitatively assessed by the xMAP bead-based multiplexed immunoassay. To identify the performance of each biomarker in predicting cancer over benign tumors, we used a repeated leave-group-out cross-validation strategy. The prediction models using multimarkers were evaluated to develop a urinary ovarian cancer panel. After the exclusion of 12 borderline tumors, the urinary concentration of 17 biomarkers exhibited significant differences between 158 OCs and 125 benign tumors. Human epididymis protein 4 (HE4), vascular cell adhesion molecule (VCAM), and transthyretin (TTR) were the top three biomarkers representing a higher concentration in OC. HE4 demonstrated the highest performance in all samples withOC(mean area under the receiver operating characteristic curve (AUC) 0.822, 95% CI: 0.772-0.869), whereas TTR showed the highest efficacy in early-stage OC (AUC 0.789, 95% CI: 0.714-0.856). Overall, HE4 was the most informative biomarker, followed by creatinine, carcinoembryonic antigen (CEA), neural cell adhesion molecule (NCAM), and TTR using the least absolute shrinkage and selection operator (LASSO) regression models. A multimarker panel consisting of HE4, creatinine, CEA, and TTR presented the best performance with 93.7% sensitivity (SN) at 70.6% specificity (SP) to predict OC over the benign tumor. This panel performed well regardless of disease status and demonstrated an improved performance by including menopausal status. In conclusion, the urinary biomarker panel with HE4, creatinine, CEA, and TTR provided promising efficacy in predicting OC over benign tumors in women with pelvic masses. It was also a non-invasive and easily available diagnostic tool.
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