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European Journal of Gynaecological Oncology  2020, Vol. 41 Issue (3): 368-374    DOI: 10.31083/j.ejgo.2020.03.5197
Original Research Previous articles | Next articles
Is the Risk of Malignancy Index a predictive tool for preoperative differentiation between borderline ovarian tumor and ovarian cancer?
S.R Oh1, J.-W. Park1()
1Department of Obstetrics and Gynecology, Dong-A University Medical Center, Dong-A University, College of Medicine, Busan, 49201, South Korea
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Abstract  

Purpose: To determine an appropriate Risk of Malignancy Index (RMI) cutoff value by comparative analysisof the four malignancy risk indices for distinguishing between borderline ovarian tumor (BOT) and ovarian cancer (OC). Materials and Methods: Retrospective analysis of the medical records of 339 patients (115 BOTsand 224 OCs). Results: There were no significant differences in the area under the ROC curve (AUC) for RMI 1, RMI 2, RMI 3, and RMI 4 (0.792, 0.791, 0.785, and 0.785, respectively). However, the diagnostic capability of the RMI was significantly greater than that of other factors. Conclusion: This study is the first to investigate the performance of the four Risk of Malignancy Indices for distinguishing between BOT and invasive OC. Although there were no significant differences between RMI scores, the RMIs were very effective at predicting an accurate preoperative diagnosis in patients with all BOT and OC histotypes.
Key words:  Risk of Malignancy Index      Preoperative diagnosis      Borderline ovarian tumor      Ovarian cancer     
Submitted:  27 February 2019      Accepted:  03 June 2019      Published:  15 June 2020     
Fund: Dong-A University
*Corresponding Author(s):  J.-W. Park     E-mail:  obgypjw@dau.ac.kr
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Cite this article: 

S.R Oh, J.-W. Park. Is the Risk of Malignancy Index a predictive tool for preoperative differentiation between borderline ovarian tumor and ovarian cancer?. European Journal of Gynaecological Oncology, 2020, 41(3): 368-374.

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https://ejgo.imrpress.com/EN/10.31083/j.ejgo.2020.03.5197     OR     https://ejgo.imrpress.com/EN/Y2020/V41/I3/368

Table 1  - Distribution of diagnosis and stages in 339 patients presenting with a BOT and OC.
Diagnosis N (%) Stage N (%)
Premenopausal (n = 174) Postmenopausal (n = 165) I II III IV Total (n = 339)
BOT?
Mucinous 58 (71.6) 26 (76.5) 84 0 0 0 84 (73.1)
Serous 21 (26.0) 4 (11.8) 24 0 0 1 25 (21.7)
Seromucinous 1 (1.2) 1 (2.9) 2 0 0 0 2 (1.7)
Clear cell 0 (0.0) 2 (5.9) 2 0 0 0 2 (1.7)
Endometrioid 1 (1.2) 0 (0.0) 1 0 0 0 1 (0.9)
Brener 0 (0.0) 1 (2.9) 1 0 0 0 1 (0.9)
Total BOT cases 81 (100) 34 (100) 114 0 0 1 115 (100)
OC?
Serous 49 (52.6) 73 (55.7) 26 7 82 7 122 (54.5)
Mucinous 15 (16.1) 15 (11.5) 20 3 7 0 30 (13.4)
Endometrioid 14 (15.1) 10 (7.6) 9 6 9 0 24 (10.7)
Clear cell 11 (11.8) 11 (8.4) 14 2 6 0 22 (9.7)
Malignant mixed müllerian tumor 2 (2.2) 5 (3.8) 2 0 4 1 7 (3.2)
Transitional cell carcinoma 1 (1.1) 6 (4.6) 2 2 3 0 7 (3.2)
Squamous cell carcinoma 1 (1.1) 3 (2.2) 2 2 0 0 4 (1.8)
Undifferentiated 0 (0.0) 3 (2.2) 2 0 1 0 3 (1.3)
Seromucinous 0 (0.0) 1 (0.8) 1 0 0 0 1 (0.4)
Peritoneal carcinoma 0 (0.0) 1 (0.8) 0 0 1 0 1 (0.4)
Small cell carcinoma 0 (0.0) 1 (0.8) 1 0 0 0 1 (0.4)
Papillary adenocarcinoma 0 (0.0) 1 (0.8) 0 0 1 0 1 (0.4)
X-müllerian adenosarcoma 0 (0.0) 1 (0.8) 0 1 0 0 1 (0.4)
Total OC cases 93 (100) 131 (100) 79 23 114 8 224 (100)
Table 2  - The distribution of BOT and OC cases by age, menopausal status, ultrasound score, tumor size, and serum CA 125.
Variables BOT OC Significance level
N 115 (33.9%) N = 224 (66.1%) Test p
Age (years) 41.37 ± 17.64 52.22 ± 14.64 χ2 < 0.001
Menopausal status
Premenopausal 81 (70.4%) 93 (41.5%) χ2 < 0.001
Postmenopausal 34 (29.6%) 131 (58.5%)
Ultrasound score χ2 < 0.001
0 7(6.1%) 0 (0%)
1 41 (35.7%) 49 (21.9%)
2 51 (44.3%) 96 (42.9%)
3 11 (9.6%) 54 (24.1%)
4
5		 5 (4.3%)
0 (0%)		 23 (10.3%)
2 (0.9%)
Tumor size 16.46 ± 8.65 11.49 ± 5.95 χ2 < 0.001
CA 125 (IU/ml) 95.41 ± 185.12 659.98 ± 831.67 U-test < 0.001
Table 3  - Sensitivity, Specificity, and Positive (PPV) and Negative (NPV) Predictive Values for predicting malignancy at different cutoff levels of four malignancy risk indices (RMI 1, RMI 2, RMI 3, and RMI 4).
Cutoff Sensitivity (%) Specificity (%) PPV (%) NPV (%)
RMI 1 170 59.1 77.2 57.1 78.6
200 65.2 75.5 57.7 80.9
230 70.4 71.4 55.9 82.5
260 73.9 69.2 55.2 83.8
290 74.8 67.0 53.8 83.8
RMI 2 280 74.8 67.9 54.4 84.0
310 74.8 66.5 53.4 83.7
340 80.0 66.1 54.8 86.6
370 80.0 65.2 54.1 86.4
400 80.0 63.4 52.9 86.1
RMI 3 170 59.1 77.2 57.1 78.7
200 65.2 75.5 57.7 80.9
230 70.4 71.4 55.9 82.5
260 73.9 69.2 55.2 83.8
290 74.8 67.0 53.8 83.8
RMI 4 530 84.4 61.2 52.7 88.4
580 86.1 61.2 53.2 89.6
630 87.8 60.7 53.4 90.7
680 88.7 58.9 52.6 91.0
730 90.4 58.0 52.5 92.2
Table 4  - The predictive performance of serum CA 125, menopausal status, tumor size, ultrasound score, and RMIs in AUROC for discrimination between BOT and OC groups.
Variables AUROC? Asymptomatic 95% Confidence Interval p-value
Lower bound Upper bound
RMI 1 0.792 0.745 0.838 < 0.001
RMI 2 0.791 0.744 0.838 < 0.001
RMI 3 0.785 0.738 0.832 < 0.001
RMI 4 0.785 0.737 0.832 < 0.001
CA 125 0.739 0.689 0.785 < 0.001
Menopause 0.645 0.591 0.696 < 0.001
Tumor size 0.672 0.620 0.722 < 0.001
Ultrasound 0.655 0.601 0.705 < 0.001
Figure 1.  — Receiver operating characteristic (ROC) curves of the individual predictors showing the relationship between sensitivity and specificity of serum CA 125 level, menopause score, tumor size, ultrasound score, and RMI in the discrimination between BOTs and OCs.

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