New App Predicts Ovarian Tumor Cancer Risk


A new app, called ADNEX, helps distinguish between benign and malignant ovarian tumors, potentially improving triage and management decisions.

[[{"type":"media","view_mode":"media_crop","fid":"28839","attributes":{"alt":"","class":"media-image media-image-right","id":"media_crop_9859429830685","media_crop_h":"284","media_crop_image_style":"-1","media_crop_instance":"2953","media_crop_rotate":"0","media_crop_scale_h":"0","media_crop_scale_w":"0","media_crop_w":"168","media_crop_x":"25","media_crop_y":"23","style":"line-height: 1.538em; float: right;","title":"Screenshot of ADNEX app showing bar chart probabilities.","typeof":"foaf:Image"}}]]A new test is available aimed at diagnosing ovarian tumors and selecting the best treatment course.

The test, which is called the Assessment of Different NEoplasias in the adneXa (ADNEX) and was highlighted in a study published this month in the British Medical Journal, was designed to differentiate between benign and malignant tumors as well as identify specific malignancies.

ADNEX was formed using data from 3,506 patients from 10 European countries from 1999 to 2007. The researchers looked at what information available before the operation could be used to predict the diagnosis that was ultimately given. The model was then tested on 2,403 patients between 2009 and 2012.

The researchers suggest that the test can now be used clinically and could improve triage and management decisions. The ADNEX model works off the following predictors: age, serum CA-125 level, type of center (oncology vs other hospitals), maximum diameter of the lesion, proportion of solid tissue, more than 10 cyst locules, number of papillary projections, acoustic shadows, and ascites. By entering a patient’s clinical and ultrasound information into the ADNEX database, the test can help identify the type of tumor prior to surgery, since the test was found to have fair to excellent ability to distinguish between four types of ovarian malignancy.

“This new approach to classifying ovarian tumours can help doctors make the right management decisions, which will improve the outcome for women with cancer,” said Tom Bourne, of the Department of Surgery and Cancer at Imperial College London, in a news release. “It will also reduce the likelihood of women with all types of cysts having excessive or unnecessary treatment that may impact on their fertility"

The developers have also made a smartphone app ($200) for the test.

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