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European Journal of Gynaecological Oncology  2020, Vol. 41 Issue (2): 200-207    DOI: 10.31083/j.ejgo.2020.02.4971
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Preoperative discriminating performance of the IOTA-ADNEX model and comparison with Risk of Malignancy Index: an external validation in a non-gynecologic oncology tertiary center
N. Tug1, M. Yassa2, *(), M. Akif Sargın1, B. Dogan Taymur2, K. Sandal2, Ertunc Mega3
1Associate Professor of Gynecology, Health Sciences University, Sehit Prof Dr Ilhan Varank Sancaktepe Training and Research Hospital, Department of Obstetrics and Gynecology, Istanbul, Turkey
2Gynecologist, Health Sciences University, Sehit Prof Dr Ilhan Varank Sancaktepe Training and Research Hospital, Department of Obstetrics and Gynecology, Istanbul, Turkey
3Gynecologist, Health Sciences University, Sehit Prof Dr Ilhan Varank Sancaktepe Training and Research Hospital, Department of Obstetrics and Gynecology, Istanbul, Turkey
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Abstract  

Aim: This study aimed to externally validate the International Ovarian Tumor Analysis-Assessment of Different Neoplasias in the adnexa IOTA-ADNEX model in a tertiary center without a specific gynecologic oncology unit to be used for referral to an oncology center, and to compare its performance with Risk of Malignancy Index (RMI) I-IV. Materials and Methods: Data of 285 women who underwent surgery for an adnexal mass with known CA-125 values were prospectively collected and retrospectively analyzed. Preoperative scores of ADNEX model and RMI I-IV were compared with final histopathological diagnosis. Patients were further classified according to their menopausal state. Results: Rate of malignancy was 9.1%. Sensitivity and specificity rates of ADNEX model in discriminating malignant tumors were found to be 88.5% and 84.6%, respectively (AUC 0.865 ± 0.039), irrespective of menopausal state at 10% cut-off value as proposed by the original article. Optimal cut-off value of ADNEX model to discriminate malign tumors was found as 14%. ADNEX model exhibited superior sensitivity and specificity compared to all four RMI models. This model was able to discriminate benign lesions from borderline, Stage I ovarian cancer (OC) and Stage II-IV OC, borderline tumors from Stage II-IV OC, and Stage I from Stage II-IV OC (AUC > 0.700) very well. On the other hand, discrimination between borderline with Stage I tumors (AUC 0.576 ± 0.152) was mediocre. Conclusion: ADNEX model adds a stratified classification and might be clinically useful for the triage of patients admitted to a non-oncologic center with suspicious adnexal masses to be referred to specialized oncology units.

Key words:  Adnexal mass      Decision support techniques      Ovarian neoplasms      Sensitivity and specificity      Ultrasonography     
Published:  15 April 2020     
*Corresponding Author(s):  M. Yassa     E-mail:  murat.yassa@gmail.com

Cite this article: 

N. Tug, M. Yassa, M. Akif Sargın, B. Dogan Taymur, K. Sandal, Ertunc Mega. Preoperative discriminating performance of the IOTA-ADNEX model and comparison with Risk of Malignancy Index: an external validation in a non-gynecologic oncology tertiary center. European Journal of Gynaecological Oncology, 2020, 41(2): 200-207.

URL: 

https://ejgo.imrpress.com/EN/10.31083/j.ejgo.2020.02.4971     OR     https://ejgo.imrpress.com/EN/Y2020/V41/I2/200

Table 1  — Histologic subtypes of the adnexal masses (n=285).
Histological subtypes Total, n (%) Premenopausal, n (%) Postmenopausal, n (%)
Benign (90.9%)
Benign brenner tumours 3 (1.1) 0 3
Cystadenofibromas 16 (6.1) 10 6
Endometriomas 69 (26.6) 64 5
Fibromas 11 (4.2) 0 11
Functional cysts 17 (6.5) 14 3
Mixed 4 (1.5) 4 0
Mucinous cystadenomas 20 (7.7) 15 5
Serous cystadenomas 70 (27) 32 38
Teratomas 40 (15.4) 31 9
Tubal torsion 1 (0.3) 1 0
Tubo-ovarian abscesses 8 (3) 4 4
Total 259 (100) 175 (67.6) 84 (32.4)
Malignant (9.1%)
Adult granulosa cell tumors 1 (3.8) 0 1
Clear cell carcinomas 1 (3.8) 0 1
Endometrioid/clear cell carcinomas 1 (3.8) 0 2
Serous adenocarcinomas 10 (38.4) 8 1
Serous papillary/clear cell adenocarcinomas 2 (7.7) 1 1
Serous papillary/endometrioid adenocarcinomas 1 (3.8) 0 1
Sertoli Leydig 1 (3.8) 0 1
Endometrioid borderline 1 (3.8) 0 1
Mucinous borderline 3 (11.5) 3 0
Serous borderline 2 (7.7) 0 2
Ovarian metastasis 3 (11.5) 2 1
Total 26 (100) 14 (53.9) 1
Table 2  — Patients’ clinical and sonographic features.
Benign (n=259) Malignant (n=26) Malignant Pa Pb
Borderline (n=6) Stage I (n=11) Stage II-IV (n=6) Metastasis (n=3)
Median (Min-Max) Median (Min-Max) Median (Min-Max) Median (Min-Max) Median (Min-Max) Median (Min-Max)
Age 43 (14-83) 50.5 (22 -73) 38.5 (22-73) 47 (34-65) 57.5 (41-69) 51 (50-51) 0.01* 0.06
Parity 2 (0-10) 2.0 (0-5) 1 (0-4) 2 (0-5) 2 (1-3) 2 (0-4) 0.77 0.69
CA-125 20.7 (3-951) 22.8 (7.5-827) 13.3 (8-211) 21.4 (9-570) 248.7 (11-828) 9.2 (8-34) 0.43 0.05
Max lesion size (mm) 70 (22-255)1 84.5 (50-210) 107 (60-210) 85 (50-150) 85 (61-120) 84 (80-85) 0.003* 0.03*
Max solid tissue size (mm) 0 (0-60)1.2.3 45.5 (0-130) 44.25 (0-130) 43 (0-130) 45.45 (38.5-60) 55.8 (41-64) < 0.001* < 0.001*
Proportion of solid tissue 0 (0-1)1.3 0.54 (0-0.95) 0.58 (0-0.95) 0.45 (0-0.91) 0.55 (0.43-0.68) 0.66 (0.51-0.75) < 0.001* < 0.001*
n (%) n (%) n (%) n (%) n (%) n (%) < 0.001* < 0.001*
Numb. of papillas
0 246 (95) 15 (57) 4 (67) 5 (45) 4 (67) 2 (67)
1 11 (4) 3 (11) 1 (17) 2 (18) 0 (0) 0 (0)
2 1 (0) 4 (15) 1 (17) 0 (0) 2 (67) 1 (33)
3 1 (0) 3 (11) 0 (0) 3 (27) 0 (0) 0(0)
> 3 0 (0) 1 (4) 0 (0) 1 (1) 0 (0) 0 (0)
Menopausal state
Postmen 84 (32.4) 12 (46.2) 3 (50.0) 5 (45.5) 3 (50.0) 1 (33.3) 0.19 0.49
Premen. 175 (67.6) 14 (53.8) 3 (50.0) 6 (54.5) 3 (50.0) 2 (66.7)
Laterality
Bilat. 43 (16.6) 6 (23.1) 0 (0.0) 2 (18.2) 4 (66.7) 0 (0.0) 0.27 0.02*
Unilat. 216 (83.4)3 20 (76.9) 6 (100.0) 9 (81.8) 2 (33.3) 3 (100.0)
Solid tissue
No 205 (79.2) 3 (11.5) 1 (16.7) 1 (9.1) 0 (0.0) 1 (33.3) < 0.001* < 0.001*
Yes 54 (20.8)1 2 23 (88.5) 5 (83.3) 10 (90.9) 6 (100.0) 2 (66.7)
> 10 locules
No 257 (99.2) 26 (100.0) 6 (100.0) 11 (100.0) 6 (100.0) 3 (100.0) - -
Yes 2 (0.8) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
Acoustic shadow
No 256 (98.8) 26 (100.0) 6 (100.0) 11 (100.0) 6 (100.0) 3 (100.0) - -
Yes 3 (1.2) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
Ascites
No 258 (99.6) 19 (73.1) 6 (100.0) 8 (72.7) 3 (50.0) 2 (66.7) < 0.001* < 0.001*
Yes 1 (0.4)2 3 7 (26.9) 0 (0.0) 3 (27.3) 3 (50.0) 1 (33.3)
Frozen section
No 116 (44.8) 3 (11.5) 1 (16.7) 1 (9.1) 1 (16.7) 0 (0.0) 0.001 0.026*
Yes 143 (55.2)2 23 (88.5) 5 (83.3) 10 (90.9) 5 (83.3) 3 (100.0)
Table 3  — Diagnostic performance of IOTA ADNEX model at different cut-offs for total probability of malignancy depending on menopausal state.
Cut-off* Sensitivity Specificity Accuracy rate UC ± SE p OR (95% CI)
Postmenopausal
ADNEX 3% 91.7% 66.7% 69.8% 0.001 22,0 (179.1 - 2.7)
5% 91.7% 75.0% 77.1% < 0.001 33.0 (271.1 - 4.0)
10% 91.7% 77.4% 79.2% < 0.001 37.6 (310.4 - 4.6)
15% 91.7% 81.0% 82.3% < 0.001 46.8 (388.8 - 5.6)
Optimal (332) 83.3% 97.6% 95.8% 0.950 ± 0.035 < 0.001 205.0 (1.619.7 - 25.9)
RMI type
(Standard cut-off) 1 (200) 25.0% 89.3% 81.3% 0.571 ± 0.095 0.425 2.8 (12.2 - 0.6)
2 (200) 50.0% 78.6% 75.0% 0.643 ± 0.091 0.111 3.7 (12.7 - 1.1)
3 (200) 25.0% 86.9% 79.2% 0.560 ± 0.094 0.506 2.2 (9.5 - 0.5)
4 (450) 33.3% 88.1% 81.3% 0.607 ± 0.095 0.232 3.7 (14.6 - 0.9)
Frozen section 81.8% 98.4% 95.9% 0.901 ± 0.070 < 0.001 274.5 (22.5 - 3.345.4)
Premenopausal
ADNEX 3%
92.9%

69.1%

70.9%

< 0.005

29.1 (228.3 - 3.7)
5% 92.9% 80.0% 81.0% < 0.006 52.0 (411.0 - 6.6)
10% 85.7% 88.0% 87.8% < 0.007 44.0 (210.4 - 9.2)
15% 78.6% 94.3% 93.1% < 0.008 60.5 (252.1 - 14.5)
Optimal (13.3) 85.7% 93.1% 92.6% 0.951 ± 0.025 < 0.001 81.5 (406.8 - 16.3)
RMI type
(Standard cut-off) 1 (200) 28.6% 89.7% 85.2% 0.591 ± 0.086 0.255 3.5 (12.3 - 1.0)
2 (200) 35.7% 86.9% 83.1% 0.613 ± 0.086 0.160 3.7 (11.9 - 1.1)
3 (200) 28.6% 87.4% 83.1% 0.580 ± 0.086 0.320 2.8 (9.6 - 0.8)
4 (450) 35.7% 92.0% 87.8% 0.639 ± 0.088 0.085 6.4 (21.7 - 1.9)
Frozen section 83.3% 100.0% 97.8% 0.917 ± 0.064 < 0.001 -
Total
ADNEX 3% 92.3% 68.3% 70.5% < 0.001 25.9 (112.2 - 6.0)
5% 92.3% 78.4% 79.6% < 0.001 43.5 (189.7 - 10.0)
10% 88.5% 84.6% 84.9% < 0.001 42.0 (146.4 - 12.0)
15% 84.6% 90.0% 89.5% < 0.001 49.3 (154.1 - 15.8)
Optimal (14.05) 88.5% 89.2% 89.1% 0.949 ± 0.020 < 0.001 63.3 (224.2 - 17.8)
RMI type
(Standard cut-off) 1 (200)
26.9%

89.6%

83.9%

0.582 ± 0.064

0.166

3.2 (8.2 - 1.2)
2 (200) 42.3% 84.2% 80.4% 0.632 ± 0.063 0.026 3.9 (9.1 - 1.7)
3 (200) 26.9% 87.3% 81.8% 0.571 ± 0.063 0.233 2.5 (6.5 - 1.0)
4 (450) 34.6% 90.7% 85.6% 0.627 ± 0.064 0.033 5.2 (12.9 - 2.1)
Frozen section 82.6% 99.3% 97.0% 0.910 ± 0.047 < 0.001 674.5 (71.6 / 6.354.8)
Table 4  — Polytomous discrimination performance of IOTA ADNEX model.
Types of discrimination AUC ± SE.
Benign vs. Malignant 0.941 ± 0.042
Benign vs. BOT 0.905 ± 0.049
Benign vs. Stage I OC 0.934 ± 0.034
Benign vs. Stage II-IV OC 0.997 ± 0.003
BOT vs. Stage I OC 0.576 ± 0.152
BOT vs. Stage II-IV OC 0.861 ± 0.110
Stage I vs. Stage II-IV OC 0.742 ± 0.125
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