COMPARATIVE STUDY
JOURNAL ARTICLE
Add like
Add dislike
Add to saved papers

Comparison of different ovarian cancer detection algorithms.

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.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app