C-reactive protein as a diagnostic marker for ovarian carcinoma
Accepted: 16 October 2024
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Ovarian carcinoma is a leading cause of death in gynecological cancers, making early detection crucial for improving survival rates. C-reactive protein (CRP) has shown promise as a cost-effective biomarker to distinguish ovarian carcinoma from benign ovarian masses. Elevated CRP levels are associated with an increased risk of ovarian cancer. This cross-sectional study included 87 patients: 59 with ovarian carcinoma and 28 with ovarian cysts. The aim was to evaluate CRP as a diagnostic marker to improve early detection and clinical management of ovarian carcinoma. CRP levels were measured using the enzyme-linked immunosorbent assay method. Statistical analysis was conducted to assess the differences in CRP levels between the ovarian carcinoma group and the ovarian cyst group. All statistical analyses were performed using the Statistical Program for Social Sciences (IBM SPSS 24, IL, USA). Most subjects in the study were 50 years old or younger (69%) and had ovarian carcinoma (67.8%). Age over 50 [odds ratio (OR) 5.71, p=0.01] and menopausal status (OR 4.72, p=0.01) were significant risk factors for ovarian carcinoma. No significant difference in CRP levels was found between ovarian carcinoma and ovarian cyst patients (p=0.23). Based on the results, CRP cannot be used as an effective predictor to differentiate ovarian carcinoma from ovarian cysts.
Downloads
PlumX Metrics
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
How to Cite
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.