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Prediction of Ovarian Tumor Malignancy

Authors: Soljačić Vraneš, Hrvojka; Klarić, Petar; Sonicki, Zdenko; Gall, Vesna; Jukić, Marija; Vuković, Ante;

Prediction of Ovarian Tumor Malignancy

Abstract

Ovarian cancer is the leading cause of mortality among gynecological cancers. The aim of the study was to form the decision rules for distinguishing benign from malignant ovary lesions. The research was conducted on 201 women with ovary tumor. Commonly used specific markers for ovarian cancer (biochemical marker Ca 125, ultrasound and vascular markers) were used. The significant difference in the presence of an ultrasound and vascular markers between benign and malignant ovary changes along with the significantly different level of Ca 125 is confirmed. To a specific marker certain score number was appointed and the scoring system was formed. The incidence of benign/malignant ovary changes was observed in the researched group regarding anthropometric parameters (age, marital and menopausal status and number of deliveries). There is also significant difference in the incidence of benign/malignant ovary tumor regarding these parameters. Based on combination of the scoring system and anthropometric parameters the decision rules for distinguishing benign from malignant ovary tumors were formed. The logistic regression method was used. We proved that this method has higher accuracy in prediction of malignancy in women with ovary tumors than using morphological, Doppler or anthropometric parameters separately.

Country
Croatia
Related Organizations
Keywords

ovarian cancer; prediction; malignancy; scoring system; decision rules, Adult, Aged, 80 and over, Ovarian Neoplasms, Adolescent, Middle Aged, Logistic Models, CA-125 Antigen, Humans, Female, Menopause, Aged

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
gold
Related to Research communities
Cancer Research