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Single and combined use of red cell distribution width, mean platelet volume, and cancer antigen 125 for differential diagnosis of ovarian cancer and benign ovarian tumors

Overview of attention for article published in Journal of Ovarian Research, January 2018
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Title
Single and combined use of red cell distribution width, mean platelet volume, and cancer antigen 125 for differential diagnosis of ovarian cancer and benign ovarian tumors
Published in
Journal of Ovarian Research, January 2018
DOI 10.1186/s13048-018-0382-3
Pubmed ID
Authors

Yuan-yuan Qin, Yang-yang Wu, Xiao-ying Xian, Jin-qiu Qin, Zhan-feng Lai, Lin Liao, Fa-quan Lin

Abstract

Cancer is widely believed to result from chronic inflammation, and red cell distribution width (RDW) and mean platelet volume (MPV) are considered as inflammatory markers for cancer. We investigated the values of RDW, MPV, and cancer antigen 125 (CA125), alone or in combination, for distinguishing between ovarian cancer and benign ovarian tumors. The study included 326 patients with ovarian cancer, 290 patients with benign ovarian tumors, and 162 control subjects. Hematologic tests were performed at initial diagnosis. RDW was increased and MPV was decreased in the ovarian cancer group compared with the control and benign ovarian tumor groups. RDW was positively correlated and MPV was negatively correlated with cancer stage. Area under the curve (AUC) analysis for ovarian cancer versus benign ovarian tumors revealed that the specificity and sensitivity were increased for the combination of MPV and CA125 compared with either marker alone, and the specificity was increased for the combination of RDW and CA125, compared with either alone. The AUCs for RDW plus CA125 and MPV plus CA125 were significantly larger than for any of the markers alone. In conclusion, combinations of the markers RDW, MPV, and CA125 may improve the differential diagnosis of ovarian cancer and benign ovarian tumors.

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 3 33%
Researcher 3 33%
Student > Doctoral Student 1 11%
Student > Master 1 11%
Professor > Associate Professor 1 11%
Other 0 0%
Readers by discipline Count As %
Unspecified 3 33%
Medicine and Dentistry 3 33%
Immunology and Microbiology 1 11%
Biochemistry, Genetics and Molecular Biology 1 11%
Design 1 11%
Other 0 0%