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


TUĞ N., Yassa M., SARĞIN M., Taymur B. D., Sandal K., Meg E.

European Journal of Gynaecological Oncology, cilt.41, sa.2, ss.200-207, 2020 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 41 Sayı: 2
  • Basım Tarihi: 2020
  • Doi Numarası: 10.31083/j.ejgo.2020.02.4971
  • Dergi Adı: European Journal of Gynaecological Oncology
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, EMBASE
  • Sayfa Sayıları: ss.200-207
  • Anahtar Kelimeler: Adnexal mass, Decision support techniques, Ovarian neoplasms, Sensitivity and specificity, Ultrasonography
  • Sağlık Bilimleri Üniversitesi Adresli: Evet

Özet

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.