Improving strategies for diagnosing ovarian cancer: a summary of the International Ovarian Tumor Analysis (IOTA) studies. (25th December 2012)
- Record Type:
- Journal Article
- Title:
- Improving strategies for diagnosing ovarian cancer: a summary of the International Ovarian Tumor Analysis (IOTA) studies. (25th December 2012)
- Main Title:
- Improving strategies for diagnosing ovarian cancer: a summary of the International Ovarian Tumor Analysis (IOTA) studies
- Authors:
- Kaijser, J.
Bourne, T.
Valentin, L.
Sayasneh, A.
Van Holsbeke, C.
Vergote, I.
Testa, A. C.
Franchi, D.
Van Calster, B.
Timmerman, D. - Abstract:
- ABSTRACT: In order to ensure that ovarian cancer patients access appropriate treatment to improve the outcome of this disease, accurate characterization before any surgery on ovarian pathology is essential. The International Ovarian Tumor Analysis (IOTA) collaboration has standardized the approach to the ultrasound description of adnexal pathology. A prospectively collected large database enabled previously developed prediction models like the risk of malignancy index (RMI) to be tested and novel prediction models to be developed and externally validated in order to determine the optimal approach to characterize adnexal pathology preoperatively. The main IOTA prediction models (logistic regression model 1 (LR1) and logistic regression model 2 (LR2)) have both shown excellent diagnostic performance (area under the curve (AUC) values of 0.96 and 0.95, respectively) and outperform previous diagnostic algorithms. Their test performance almost matches subjective assessment by experienced examiners, which is accepted to be the best way to classify adnexal masses before surgery. A two‐step strategy using the IOTA simple rules supplemented with subjective assessment of ultrasound findings when the rules do not apply, also reached excellent diagnostic performance (sensitivity 90%, specificity 93%) and misclassified fewer malignancies than did the RMI. An evidence‐based approach to the preoperative characterization of ovarian and other adnexal masses should include the use of LR1, LR2ABSTRACT: In order to ensure that ovarian cancer patients access appropriate treatment to improve the outcome of this disease, accurate characterization before any surgery on ovarian pathology is essential. The International Ovarian Tumor Analysis (IOTA) collaboration has standardized the approach to the ultrasound description of adnexal pathology. A prospectively collected large database enabled previously developed prediction models like the risk of malignancy index (RMI) to be tested and novel prediction models to be developed and externally validated in order to determine the optimal approach to characterize adnexal pathology preoperatively. The main IOTA prediction models (logistic regression model 1 (LR1) and logistic regression model 2 (LR2)) have both shown excellent diagnostic performance (area under the curve (AUC) values of 0.96 and 0.95, respectively) and outperform previous diagnostic algorithms. Their test performance almost matches subjective assessment by experienced examiners, which is accepted to be the best way to classify adnexal masses before surgery. A two‐step strategy using the IOTA simple rules supplemented with subjective assessment of ultrasound findings when the rules do not apply, also reached excellent diagnostic performance (sensitivity 90%, specificity 93%) and misclassified fewer malignancies than did the RMI. An evidence‐based approach to the preoperative characterization of ovarian and other adnexal masses should include the use of LR1, LR2 or IOTA simple rules and subjective assessment by an experienced examiner. Copyright © 2012 ISUOG. Published by John Wiley & Sons, Ltd . … (more)
- Is Part Of:
- Ultrasound in obstetrics & gynecology. Volume 41:Number 1(2013:Jan.)
- Journal:
- Ultrasound in obstetrics & gynecology
- Issue:
- Volume 41:Number 1(2013:Jan.)
- Issue Display:
- Volume 41, Issue 1 (2013)
- Year:
- 2013
- Volume:
- 41
- Issue:
- 1
- Issue Sort Value:
- 2013-0041-0001-0000
- Page Start:
- 9
- Page End:
- 20
- Publication Date:
- 2012-12-25
- Subjects:
- biomarkers -- decision support techniques -- logistic models -- ovarian neoplasms -- ultrasonography
Ultrasonics in obstetrics -- Periodicals
Generative organs, Female -- Diseases -- Diagnosis -- Periodicals
Diagnosis, Ultrasonic -- Periodicals
Genital Diseases, Female -- ultrasonography -- Periodicals
Ultrasonography, Prenatal -- Periodicals
618.047543 - Journal URLs:
- http://obgyn.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)1469-0705/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/uog.12323 ↗
- Languages:
- English
- ISSNs:
- 0960-7692
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9082.815300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 1026.xml