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العنوان
Risk of Ovarian Malignancy Algorithm (ROMA) Versus Risk of Malignancy Index (RMI) for prediction of malignancy in women
presenting with Ovarian Tumours
المؤلف
Mostafa,Rania Hassan
هيئة الاعداد
باحث / Rania Hassan Mostafa
مشرف / Amr Ell Shalakany
مشرف / Ahmed Ellsayed Hassan Hamed
مشرف / Amall Abdell Salllam
الموضوع
Ovarian Malignancy Algorithm -
تاريخ النشر
2013
عدد الصفحات
173.p:
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
أمراض النساء والتوليد
تاريخ الإجازة
21/4/2013
مكان الإجازة
جامعة عين شمس - كلية الطب - Obsttettriics & Gynecollogy
الفهرس
Only 14 pages are availabe for public view

from 173

from 173

Abstract

Ovarian cancer accounts for 3.7% of all cancers in women and is the seventh leading cause of cancer-related deaths among women worldwide. The outcome for women with ovarian cancer is generally poor, with an overall 5-year survival rate of less than 35%, due to the advanced stage at time of presentation.
The symptoms of ovarian cancer are usually non-specific; however, there are a number of symptoms that do suggest ovarian cancer if they are experienced frequently and/or last a long time.
In women with an adnexal mass it is important to distinguish between benign and malignant pathology before surgical treatment.
As the risk of malignancy increases, the appropriate location for management changes; so that while a general gynaecologist might manage women with a low risk of malignancy, those at intermediate risk should be managed in a cancer unit and those at high risk in a cancer centre; that’s to say triaging women in order to decide the most appropriate place for them to be managed.
Different modalities have been tried to predict malignancy in ovarian masses, like tumor markers, ultrasound findings (or specific ultrasound “rules”), or combination of both.
Cancer antigen 125 (CA125) was the only FDA-approved biomarker for ovarian cancer before the year 2008. Although the CA125 serum level is elevated in 80% of epithelial ovarian cancer (EOC) patients with advanced stage, it’s increased in only 50% of patients with stage I EOC. In addition, CA125 serum levels are elevated in various benign gynecological diseases (including endometriosis) & non-gynecologic malignancies.
Recently, another tumour marker for ovarian cancer has been proposed, the HE4 protein, frequently overexpressed in ovarian cancers, especially in serous and endometrioid histology. It was reported that HE4 could be used as a biomarker for ovarian cancer with higher specificity than CA125.
An effective way of triaging women into those who are at low, moderate, or high risk of malignancy is to use a risk of malignancy index. First proposed by Jacobs et al., the Risk of Maignancy Index I (RMI I) is still the gold standard malignancy index recommended by the NICE guidelines, & the RCOG Green-top guidelines for prediction of malignancy in women presenting with adnexal mass; both in premenopausal & postmenopausal groups. Systematic reviews concluded that an RMI I cut-off of 250 should be used because this would ensure access to specialist centres whilst not overburdening them with benign disease (and the additional costs associated with this). In 2009; Moore et al., proposed the Risk of Ovarian Malignancy Algorithm (ROMA) which combines the two markers (CA125 & HE4) together with the menopausal state to accurately classify women with ovarian masses into high & low risk for ovarian malignancy. Moore et al., concluded that the dual marker algorithm utilizing HE4 and CA125 to calculate a ROMA value achieves a significantly higher sensitivity for identifying women with EOC than does RMI.
In this study, we compared the performance of the malignancy indices ROMA & RMI, as well as the performance of the tumor markers HE4 & CA125 in prediction of malignancy in women with ovarian masses. It was found that the RMI performs better than the ROMA as predictor for malignant ovarian masses. The RMI had higher specificity, higher positive likelihood ratio, & better overall predictive performance as compared to ROMA. HE4 is a novel biomarker that performs as efficiently as RMI in prediction of malignant ovarian masses (without the need for imaging), but needs further improvements to increase its sensitivity, & needs further evaluation as regards the cost & availability. Further studies on a large scale are needed to verify the inconsistencies as regards the results of the ROMA predictive model. To-date; RMI I is the gold standard predictive model to be used when managing women with ovarian mass.