Comparisons of Effectiveness in Differentiating Benign from Malignant Ovarian Masses between Conventional and Modified Risk of Malignancy Index (RMI)

被引:0
作者
Tantipalakorn, Charuwan [1 ]
Tinnangwattana, Dangcheewan [1 ]
Lerthiranwong, Thitikarn [1 ]
Luewan, Suchaya [1 ]
Tongsong, Theera [1 ]
机构
[1] Chiang Mai Univ, Fac Med, Dept Obstet & Gynecol, Chiang Mai 50200, Thailand
关键词
benign ovarian mass; malignant ovarian mass; risk of malignancy index; ultrasound; OPERATING CHARACTERISTIC CURVES; IOTA SIMPLE RULES; PREOPERATIVE DIAGNOSIS; MENOPAUSAL STATUS; ULTRASOUND; AREAS;
D O I
10.3390/ijerph20010888
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Objective: To compare the predictive performance in differentiating benign from malignant ovarian masses between the modified risk malignancy index (RMI) and the conventional RMI (RMI-1 and RMI-2). Methods: Women scheduled for elective surgery because of adnexal masses were recruited to undergo pelvic sonography within 24 h before surgery to assess the sonographic characteristics of the masses, focusing on loculi, solid part, ascites, bilateralness, papillary projection, and color flow mapping (CFM). Preoperative CA-125 levels were also measured. Modified RMI, RMI-1, and RMI-2 systems were used to predict malignant masses. The gold standard was pathological or intraoperative diagnosis. Results: A total of 342 ovarian masses, benign: 243 (71.1%); malignant: 99 (28.9%), meeting the inclusion criteria were analyzed. The sensitivity and the specificity of the modified RMI (87.9% and 81.9%) were significantly higher than those of RMI-1 (74.7% and 84.4%), and RMI-2 (79.8% and 81.1%, respectively). Based on ROC curves, the area under the curves were 0.930, 0.881 and 0.882 for modified RMI, RMI-1 and RMI-2, respectively. Conclusion: Modified RMI had better predictive performance than the conventional RMI in differentiating between benign and malignant ovarian masses. Modified RMI may be useful to help general gynecologists or practitioners to triage patients with an adnexal mass, especially in settings of low resources.
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