Related Experiment Video
Updated: May 29, 2026
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Comparison of different ovarian cancer detection algorithms
R Macuks1, I Baidekalna, S Donina
1Riga Stradins University, A. Kirhenstein's Institute of Microbiology and Virology, Riga, Latvia. r.macuks@gmail.com
Unlabelled:
The objective of the study was to evaluate the accuracy of a combined-two step ovarian cancer screening tool consisting of the ovarian cancer symptom index combined with either a risk of ovarian malignancy algorithm (ROMA) or a risk of malignancy index.
Material And Methods:
The case-control study consisted of 31 patients with ovarian cancer, 30 patients with benign ovarian diseases and 27 age-matched healthy controls.
Results:
Sensitivity and specificity of the ovarian cancer symptom index among menopausal women were 84.6% and 52.9%, respectively. ROMA revealed the highest discriminative value when compared to others (AUC 98.4%). When the cutoff level of 28 was applied for menopausal women, ROMA revealed sensitivity and specificity of 95.8% and 93.1%, respectively.
Conclusions:
The ovarian cancer symptom index could be used as the first step in ovarian cancer screening with subsequent application of ROMA as a second step screening tool. A larger sample size in both control and patient groups should be evaluated to reach clear conclusions.
