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

Aim: This study aimed to externally validate the International Ovarian TumorAnalysis-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 ofADNEX 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.

Adnexal mass; Decision support techniques; Ovarian neoplasms; Sensitivity and specificity; Ultrasonography

[1] Woo YL, Kyrgiou M, Bryant A, Everett T, Dickinson HO.: “Centralisation of services for gynaecological cancers - a Cochrane systematic review”. Gynecol. Oncol., 2012, 126, 286.

[2] Committee Opinion No. 477.: “The role of the obstetrician-gynecologist in the early detection of epithelial ovarian cancer”. Obstet. Gynecol., 2011, 117, 742.

[3] Howlader N., Noone A.M., Krapcho M., Miller D., Bishop K., Altekruse S.F., et al.: “SEER Cancer Statistics Review, 1975-2012” Bethesda, MD: National Cancer Institute. Available at: http://seer. cancer gov/csr/1975_2012

[4] Bristow R.E., Chang J., Ziogas A., Anton-Culver H.: “Adherence to treatment guidelines for ovarian cancer as a measure of quality care”. Obstet. Gynecol. 2013, 121, 1226.

[5] Bristow R.E., Chang J., Ziogas A., Randall L.M., Anton-Culver H.: “High-volume ovarian cancer care:survival impact and disparities in access for advanced-stage disease”. Gynecol. Oncol., 2014, 132, 403.

[6] Meys E.M., Kaijser J., Kruitwagen R.F., Slangen B.F., Calster B Van, Aertgeerts B., et al.: “Subjective assessment versus ultrasound models to diagnose ovarian cancer: A systematic review and meta-analysis”. Eur. J. Cancer., 2016, 58, 17.

[7] Nunes N., Ambler G., Foo X., Naftalin J., Widschwendter M., Jurkovic D.: “Use of IOTA simple rules for diagnosis of ovarian cancer: meta-analysis”. Ultrasound. Obstet. Gynecol., 2014, 44, 503.

[8] Sayasneh, Kaijser, Preisler, Smith, Raslan, Johnson, et al.: “Accuracy of ultrasonography performed by examiners with varied training and experience in predicting specific pathology of adnexal masses”. Ultrasound. Obstet. Gynecol., 2015, 45, 605.

[9] Manegold-Brauer G., Buechel J.: “Improved detection rate of ovarian cancer using a 2-step triage model of the risk of malignancy index and expert sonography in an outpatient screening setting”. Int. J. Gynecol. Cancer, 2016, 26, 1062.

[10] Håkansson F, Høgdall E.: “Risk of malignancy index used as a diagnostic tool in a tertiary centre for patients with a pelvic mass”. Acta Obstet. Gynecol. Scand., 2012, 91, 496.

[11] Calster B Van, Hoorde K Van, Valentin L, Testa AC, Fischerova D, Holsbeke C Van, et al.: “Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumors: prospective multicentre diagnostic study”. BMJ, 2014, 349, 5920.

[12] Sayasneh A., Ferrara L., Cock B., De Saso S., Al-Memar M., Johnson S., et al.: “Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study”. Br. J. Cancer, 2016, 115, 542.

[13] Chan J., Kapp D., Shin J., Husain A., Teng N., Berek J., et al.: “Influence of the Gynecologic Oncologist on the Survival of Ovarian Cancer Patients”. Obstet. Gynecol., 2007, 109, 1342.

[14] Meys E., Jeelof L.S., Achten N.: “Estimating risk of malignancy in adnexal masses: external validation of the ADNEX model and comparison with other frequently used ultrasound methods.” Ultrasound Obstet. Gynecol., 2017, 49, 784.

[15] Szubert S., Wojtowicz A., Moszynski R., Zywica P.: “External validation of the IOTA ADNEX model performed by two independent gynecologic centers”. Gynecol. Oncol. 2016, 142, 490.

[16] Araujo K.G., Jales R.M., Pereira P.N., Yoshida A., de Angelo Andrade L., Sarian L.O., Derchain S.: “Performance of the IOTA ADNEX model in preoperative discrimination of adnexal masses in a gynecological oncology center”. Ultrasound Obstet. Gynecol., 2017, 49, 778.

[17] Van Calster B., Van Hoorde K., Froyman W., Kaijser J., Wynants L., Landolfo C., et al.: “Practical guidance for applying the ADNEX model from the IOTA group to discriminate between different subtypes of adnexal tumors”. Facts. Views. Vis. Obgyn., 2015, 7, 32.

[18] Kurman R.J.: “WHO classification of tumors of female reproductive organs”. 4th ed. Lyon: International Agency for Research on Cancer, 2014.

[19] Timmerman D., Valentin L., Bourne T.H., Collins W.P., Verrelst H., Vergote I.: “Terms, definitions and measurements to describe the ultrasonographic features of adnexal tumors: a consensus opinion from the International Ovarian Tumor Analysis (IOTA) Group.” Ultrasound Obstet. Gynecol., 2000, 16, 500.

[20] Jacobs I., Oram D., Fairbanks J., Turner J.: “A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer.“ Br. J. Obstet. Gynaecol., 1990, 97, 922.

[21] Tingulstad S., Hagen B., Skjeldestad F., Onsrud M., Kiserud T., Halvorsen T., et al.: “Evaluation of a risk of malignancy index based on serum CA125, ultrasound findings and menopausal status in the pre-operative diagnosis of pelvic masses”. BJOG, 1996, 103, 826.

[22] Tingulstad, Hagen, Skjeldestad, Halvorsen, Nustad, Onsrud.: “The risk-of-malignancy index to evaluate potential ovarian cancers in local hospitals.” Obstet. Gynecol., 1999, 93, 448.

[23] Yamamoto Y, Yamada R, Oguri H, Maeda N, Fukaya T.: “Comparison of four malignancy risk indices in the preoperative evaluation of patients with pelvic masses“. Eur. J. Obstet. Gynecol. Reprod. Biol., 2009, 144, 163.

[24] Akker P van den, Zusterzeel P, Aalders A, Snijders M, Samlal R, Vollebergh J, et al.: “Use of risk of malignancy index to indicate frozen section analysis in the surgical care of women with ovarian tumors”. Int. J. Gynecol. Obstet., 2016, 133, 355.

[25] Geomini P, Bremer G, Kruitwagen R, Mol B.: “Diagnostic accuracy of frozen section diagnosis of the adnexal mass: a metaanalysis”. Gynecol. Oncol., 2005, 96, 1.

[26] Yamamoto Y., Tsuchida A., Ushiwaka T., Nagai R.: “Comparison of 4 Risk-of-Malignancy Indexes in the Preoperative Evaluation of Patients With Pelvic Masses: A Prospective Study“. Clin.Ovarian Other Gynecol. Cancer., 2014, 7, 8.

[27] Dodge J., Covens A., Lacchetti C., Elit L., Le T., Devries-Aboud M.,et al.: “Preoperative identification of a suspicious adnexal mass: A systematic review and meta-analysis“. Gynecol. Oncol., 2012, 126, 157.