Key result
The IOTA-ADNEX model effectively discriminated between benign and malignant adnexal masses (AUC 0.865 at 10% cut-off), exhibiting superior sensitivity and specificity compared to all four Risk of Malignancy Index models.
Why the study?
To externally validate the IOTA-ADNEX model in a tertiary center lacking a specific gynecologic oncology unit for oncology center referral, and compare its performance with RMI I-IV.
Does the IOTA-ADNEX model improve discrimination of malignant adnexal masses compared to RMI in women undergoing surgery in a non-gynecologic oncology center?
Observational (n=285)
No
Does the IOTA-ADNEX model improve discrimination of malignant adnexal masses compared to RMI in women undergoing surgery in a non-gynecologic oncology center?
Odds Ratio: 42 (95% CI 12–146.4)
p-value: p=< 0.001
The IOTA-ADNEX model provides superior discrimination of malignant adnexal masses compared to RMI in a non-gynecologic oncology setting, aiding in appropriate triage and referral to specialized oncology units.
IOTA-ADNEX may aid preoperative triage of adnexal masses; leaves open need for prospective validation before practice change.
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.
No takes yet. Share an insight, caveat, or question.
A 2020 study conducted an observational in Adnexal mass (n=285). IOTA-ADNEX model vs. Risk of Malignancy Index (RMI I-IV) was evaluated on Discrimination between benign and malignant adnexal masses (10% cut-off) (OR 42.0, 95% CI 12.0-146.4, p=< 0.001). The IOTA-ADNEX model effectively discriminated between benign and malignant adnexal masses (AUC 0.865 at 10% cut-off), exhibiting superior sensitivity and specificity compared to all four Risk of Malignancy Index models.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: