Response to letter to the editor concerning validation of IOTA ADNEX model

Szubert, Sebastian; Wójtowicz, Andrzej; Żywica, Patryk

doi:10.1016/j.gore.2016.10.009

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…In a practical guide for applying the ADNEX model [15], the authors suggested using adopted cut-off values, specific for individual centers, to define malignancy. The higher value might be preferable in tertiary centers [15][16][17]. In our study, the highest accuracy of 87.1% was reached at a 35% cut-off for malignancy.…”

Section: Discussionmentioning

confidence: 51%

Accuracy of IOTA Simple Rules, IOTA ADNEX Model, RMI, and Subjective Assessment for Preoperative Adnexal Mass Evaluation: The Experience of a Tertiary Care Referral Hospital

Vilendecic

Radojević

Stefanović

et al. 2023

Gynecol Obstet Invest

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Objectives: The aim of this study was to evaluate the accuracy of IOTA Simple Rules (SR), IOTA ADNEX model, Risk of Malignancy Index (RMI), and subjective assessment (SA) which is used for adnexal mass assessment in our institution. Design: Prospective observational study. Participants/Materials, Setting, Methods: We included patients with at least one adnexal mass who needed elective surgical evaluation based on clinical and laboratory findings. Patients admitted to Clinic for Gynecology and Obstetrics, University Clinical Center of Serbia were recruited for the study between January 2019 and June 2021. Level II ultrasonographers performed a gray-scale and Doppler exam for each patient. Preoperative classification of adnexal masses (benign or malignant) was performed by subjective assessment (SA), the International Ovarian Analysis Group (IOTA) Simple Rules (SR), IOTA ADNEX model and Risk of Malignancy Index (RMI). Postoperatively obtained histological findings were used as a reference. Results During the study period, we enrolled 179 premenopausal and 217 postmenopausal patients, representing 396 patients in our sample. Prevalence of malignant disease in pre and postmenopausal groups was 16.2% (29/179) and 41% (89/217), respectively. Malignant disease was diagnosed in 29.8% (118/396) of patients. SA achieved the highest discrimination accuracy between benign and malignant tumors (AUC of 0.928, 95% CI (0.898-0.952)). For SA, the overall diagnostic accuracy, sensitivity, specificity, positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were 91.4%, 88.1%, 92.8%, 12.25, and 0.13. The AUC for SR+SA was 0.912 (95% CI (0.880-0.938)). Regarding SR+SA, diagnostic accuracy, sensitivity, specificity, LR+, and LR - were 92.4%, 88.1%, 94.2%, 15.31, and 0.13. The ADNEX model had the AUC of 0.914 (95% CI (0.882-0.940)). Binary classification using the ADNEX model at a cut-off value of 10% for malignancy, had the sensitivity, specificity, LR+ and LR- of 92.4%, 73.0%, 3.42, and 0.10. This resulted in the lowest overall accuracy of 78.8%. The AUC for RMI was 0.854 (95% CI (0.815-0.887)), with overall accuracy, sensitivity, specificity, LR+ and LR- of 82.3%, 73.7%, 86.0%, 5.26, and 0.31. There was no difference in the AUCs of the SA and IOTA models for the whole group, premenopausal, and postmenopausal groups. RMI performed worse compared to SA and the IOTA models. The ADNEX model achieved the highest accuracy at the cut-off value of 35%. Limitations The data generalizability is limited by a single institution-dependent sampling. Conclusions The IOTA Simple Rules and ADNEX model were reliable and comparable with the subjective assessment and performed better than the RMI. The IOTA SR model offers the potential for immediate and reliable diagnosis, even in the hands of less experienced ultrasonographers. Both IOTA models studied can be a valuable adjunct to a clinician’s decision-making process.

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Section: Discussionmentioning

confidence: 51%

Accuracy of IOTA Simple Rules, IOTA ADNEX Model, RMI, and Subjective Assessment for Preoperative Adnexal Mass Evaluation: The Experience of a Tertiary Care Referral Hospital

Vilendecic

Radojević

Stefanović

et al. 2023

Gynecol Obstet Invest

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“…The AUC for benign vs malignant tumours in operated patients was reported in 12 studies (6309 tumours, 31 centres, 13 countries) for ADNEX without CA125 (Table S4 and [18,19,23,26,30,35,37,40,41,[44][45][46]49,51,52,55,56,58,60,61,100] (Table S4 and S6) and the summary AUC was 0.93 (CI 95% 0.92-0.94, 95% PI 0.85-0.98) (Table 2, Figure 5). Sensitivity and specificity at the 10% risk of malignancy threshold in operated patients were reported in ten studies for ADNEX without CA125 (Tables S4 and S7).…”

Section: Meta-analysismentioning

confidence: 96%

The ADNEX risk prediction model for ovarian cancer diagnosis: A systematic review and meta-analysis of external validation studies

Barrenada

Ledger

Dhiman

et al. 2023

Preprint

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Objectives: To conduct a systematic review of studies externally validating the ADNEX model for ovarian cancer diagnosis and perform a meta-analysis of its performance. Design: Systematic review, meta-analysis Data sources: Medline, EMBASE, WOS, Scopus, and EuropePMC up to 15/05/2023. Review methods: We included external validation studies of the performance of ADNEX using any study design and any study population comprising patients with an adnexal mass. Two independent reviewers extracted data. Disagreements were resolved through discussion. Reporting quality of the studies was scored using the TRIPOD reporting guideline and methodological conduct and risk of bias using the PROBAST tool. We performed random effects meta-analysis of the AUC, sensitivity and specificity at the 10% risk of malignancy threshold, and Net Benefit and Relative Utility at the 10% risk of malignancy threshold. Results: We included 47 studies (17,007 tumours) with median study sample size 261 (range 24-4905). On average, 61% of TRIPOD items were reported. Handling of missing data, sample size justification, and model calibration were rarely described. 91% of validations were at high risk of bias, mainly due to the unexplained exclusion of incomplete cases, low sample size, or absent calibration assessment. The summary AUC to distinguish benign from malignant tumours in operated patients was 0.93 (95% CI 0.92-0.94, 95% prediction interval 0.85-0.98) for ADNEX with CA125 as a predictor (9202 tumours, 43 centres, 18 countries, 21 studies) and 0.93 (95% CI 0.91-0.94, 95% prediction interval 0.85-0.98) for ADNEX without CA125 (6309 tumours, 31 centres, 13 countries, 12 studies). The estimated probability that the model has clinical utility in a new centre was 95% (with CA125) and 91% (without CA125). When restricting analysis to studies at low risk of bias, summary AUCs were 0.93 (with CA125) and 0.91 (without CA125), and estimated probabilities that the model has clinical utility were 89% (with CA125) and 87% (without CA125). Discussion: ADNEX performed well to distinguish benign from malignant tumours in populations from different countries and settings regardless of whether CA125 was used or not. A key limitation is that calibration was rarely assessed. Review registration: PROSPERO, CRD42022373182

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Validation of the IOTA ADNEX Model Among Japanese Women Performed by Gynecology Trainees and Ultrasound Specialists

Kadooka,

Suemitsu,

Ashimoto

et al. 2024

J of Ultrasound Medicine

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ObjectivesThis study aimed to validate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) Assessment of Different NEoplasias in the adneXa (ADNEX) model in Japanese women, population with a distinct adnexal mass distribution compared with European women, and to evaluate the model's utility by gynecology trainees and ultrasound specialists.MethodsThis single‐center, retrospective study analyzed ultrasound data from January 2017 to March 2020 of 206 women with adnexal masses. Patients who underwent ultrasonography and serum CA‐125 measurement and received postsurgery histological diagnosis were included. The ADNEX model's diagnostic performance was evaluated by two trainees and two specialists using the area under the receiver operating characteristic curve (AUC) and measures of accuracy, sensitivity, specificity, and predictive values for overall performance and each examiner.ResultsOf the 206 included Japanese women, the prevalence of malignancy was 30.1%, including borderline cases. The overall AUC for distinguishing malignancy was 0.848 (95% confidence interval [CI]: 0.817–0.880). The AUC for each examiner ranged from 0.791 to 0.898, with Specialist 2 showing the highest accuracy and sensitivity varying between 0.677 and 0.839. A moderate degree of agreement was noted among the four examiners (Fleiss' kappa was 0.586). The performance of trainees and specialists differed significantly in evaluating the solid tissue and the papillary projections in both malignant and benign groups (P < .001).ConclusionsThe IOTA ADNEX model effectively differentiates benign and malignant adnexal masses in Japanese women. Although the accuracy matched up moderately among the four examiners, better accuracy is expected with training in evaluating solid tissue and papillary projections.

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Response to letter to the editor concerning validation of IOTA ADNEX model

Cited by 3 publications

References 7 publications

Accuracy of IOTA Simple Rules, IOTA ADNEX Model, RMI, and Subjective Assessment for Preoperative Adnexal Mass Evaluation: The Experience of a Tertiary Care Referral Hospital

Accuracy of IOTA Simple Rules, IOTA ADNEX Model, RMI, and Subjective Assessment for Preoperative Adnexal Mass Evaluation: The Experience of a Tertiary Care Referral Hospital

The ADNEX risk prediction model for ovarian cancer diagnosis: A systematic review and meta-analysis of external validation studies

Validation of the IOTA ADNEX Model Among Japanese Women Performed by Gynecology Trainees and Ultrasound Specialists

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