H Chen1, L Qian1, M Jiang1, Q Du1, F Yuan2, W Feng1. 1. Department of Obstetrics and Gynecology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, P.R. China. 2. Department of Pathology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, P.R. China.
Abstract
OBJECTIVE: To evaluate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) Assessment of Different NEoplasias in the adneXa (ADNEX) model in the preoperative diagnosis of adnexal masses using data from a gynecological oncology center in China. METHODS: This was a single-center, retrospective diagnostic accuracy study based on ultrasound data collected prospectively, between May and December 2017, from 278 patients with at least one adnexal (ovarian, paraovarian or tubal) mass. Clinical and pathologic information, serum CA 125 level and ultrasonographic findings were collected. All patients underwent surgery and the histopathological diagnosis was used as reference standard. The final diagnosis was classified into five tumor types according to the ADNEX model: benign ovarian tumor, borderline ovarian tumor (BOT), Stage-I ovarian cancer (OC), Stages-II-IV OC and ovarian metastasis. Receiver-operating characteristics (ROC) curve analysis was used to evaluate the diagnostic accuracy of the ADNEX model, with and without inclusion of CA 125 level in the model. RESULTS: Of the 278 women included, 203 (73.0%) had a benign ovarian tumor and 75 (27.0%) had a malignant ovarian tumor, including 18 (6.5%) with BOT, 17 (6.1%) with Stage-I OC, 32 (11.5%) with Stages-II-IV OC and eight (2.9%) with ovarian metastasis. The performance of the IOTA ADNEX model was good for discriminating between benign and malignant tumors, with an area under the ROC curve (AUC) of 0.94 (95% CI, 0.91-0.97) when CA 125 was included in the model and AUC of 0.93 (95% CI, 0.90-0.96) without CA 125. The AUC values of the model including CA 125 ranged between 0.61 and 0.99 for distinguishing between the different types of tumor, and it showed excellent performance in discriminating between a benign ovarian tumor and Stages-II-IV OC, with an AUC of 0.99 (95% CI, 0.97-1.00). The performance of the model was less effective at distinguishing between BOT and Stage-I OC and between Stages-II-IV OC and ovarian metastasis, with AUC values of 0.61 (95% CI, 0.43-0.77) and 0.78 (95% CI, 0.62-0.90), respectively. Although inclusion of CA 125 did not alter the performance of the ADNEX model in discriminating between benign and malignant lesions (AUC of 0.94 and 0.93 with and without CA 125 level, respectively; P = 0.54), the inclusion of CA 125 in the model improved its performance in discriminating between Stage-I OC and Stages-II-IV OC (AUC increased from 0.81 to 0.92; P = 0.04) and between Stages-II-IV OC and metastatic cancer (AUC increased from 0.58 to 0.78; P = 0.01). CONCLUSIONS: The IOTA ADNEX model showed good to excellent performance in distinguishing between benign and malignant adnexal masses and between the different types of ovarian tumor in a Chinese setting. Based on our findings, the ADNEX model has high value in clinical practice and can aid in the preoperative diagnosis of patients with an adnexal mass.
OBJECTIVE: To evaluate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) Assessment of Different NEoplasias in the adneXa (ADNEX) model in the preoperative diagnosis of adnexal masses using data from a gynecological oncology center in China. METHODS: This was a single-center, retrospective diagnostic accuracy study based on ultrasound data collected prospectively, between May and December 2017, from 278 patients with at least one adnexal (ovarian, paraovarian or tubal) mass. Clinical and pathologic information, serum CA 125 level and ultrasonographic findings were collected. All patients underwent surgery and the histopathological diagnosis was used as reference standard. The final diagnosis was classified into five tumor types according to the ADNEX model: benign ovarian tumor, borderline ovarian tumor (BOT), Stage-I ovarian cancer (OC), Stages-II-IV OC and ovarian metastasis. Receiver-operating characteristics (ROC) curve analysis was used to evaluate the diagnostic accuracy of the ADNEX model, with and without inclusion of CA 125 level in the model. RESULTS: Of the 278 women included, 203 (73.0%) had a benign ovarian tumor and 75 (27.0%) had a malignant ovarian tumor, including 18 (6.5%) with BOT, 17 (6.1%) with Stage-I OC, 32 (11.5%) with Stages-II-IV OC and eight (2.9%) with ovarian metastasis. The performance of the IOTA ADNEX model was good for discriminating between benign and malignant tumors, with an area under the ROC curve (AUC) of 0.94 (95% CI, 0.91-0.97) when CA 125 was included in the model and AUC of 0.93 (95% CI, 0.90-0.96) without CA 125. The AUC values of the model including CA 125 ranged between 0.61 and 0.99 for distinguishing between the different types of tumor, and it showed excellent performance in discriminating between a benign ovarian tumor and Stages-II-IV OC, with an AUC of 0.99 (95% CI, 0.97-1.00). The performance of the model was less effective at distinguishing between BOT and Stage-I OC and between Stages-II-IV OC and ovarian metastasis, with AUC values of 0.61 (95% CI, 0.43-0.77) and 0.78 (95% CI, 0.62-0.90), respectively. Although inclusion of CA 125 did not alter the performance of the ADNEX model in discriminating between benign and malignant lesions (AUC of 0.94 and 0.93 with and without CA 125 level, respectively; P = 0.54), the inclusion of CA 125 in the model improved its performance in discriminating between Stage-I OC and Stages-II-IV OC (AUC increased from 0.81 to 0.92; P = 0.04) and between Stages-II-IV OC and metastatic cancer (AUC increased from 0.58 to 0.78; P = 0.01). CONCLUSIONS: The IOTA ADNEX model showed good to excellent performance in distinguishing between benign and malignant adnexal masses and between the different types of ovarian tumor in a Chinese setting. Based on our findings, the ADNEX model has high value in clinical practice and can aid in the preoperative diagnosis of patients with an adnexal mass.
Authors: Artur Czekierdowski; Norbert Stachowicz; Agata Smoleń; Tomasz Kluz; Tomasz Łoziński; Andrzej Miturski; Janusz Kraczkowski Journal: Diagnostics (Basel) Date: 2021-02-28
Authors: Ben Van Calster; Lil Valentin; Wouter Froyman; Chiara Landolfo; Jolien Ceusters; Antonia C Testa; Laure Wynants; Povilas Sladkevicius; Caroline Van Holsbeke; Ekaterini Domali; Robert Fruscio; Elisabeth Epstein; Dorella Franchi; Marek J Kudla; Valentina Chiappa; Juan L Alcazar; Francesco P G Leone; Francesca Buonomo; Maria Elisabetta Coccia; Stefano Guerriero; Nandita Deo; Ligita Jokubkiene; Luca Savelli; Daniela Fischerová; Artur Czekierdowski; Jeroen Kaijser; An Coosemans; Giovanni Scambia; Ignace Vergote; Tom Bourne; Dirk Timmerman Journal: BMJ Date: 2020-07-30