Dataset Information

Estimating risk of malignancy in adnexal masses: external validation of the ADNEX model and comparison with other frequently used ultrasound methods.

ABSTRACT:

Objectives

To validate externally the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model and compare this model with other frequently used models in the differentiation between benign and malignant adnexal masses.

Methods

In this retrospective diagnostic accuracy study, we assessed data collected prospectively from patients with adnexal pathology who underwent real-time transvaginal or transrectal ultrasound by a single expert ultrasonographer in a tertiary care hospital between July 2011 and July 2015. The presence of a malignancy was determined by subjective assessment and use of four prediction models: the ADNEX model, simple ultrasound-based rules (simple rules), Logistic Regression model 2 (LR2) and the Risk of Malignancy Index (RMI), of which three different variants were assessed. Pathology was the clinical reference standard.

Results

In total, 851 consecutive patients underwent ultrasound examination for an adnexal mass. For 326 patients (128 premenopausal and 198 postmenopausal), pathology results were available (211 (64.7%) benign; 115 (35.3%) malignant) and these were included in the analysis. The area under the receiver-operating characteristics curve (AUC) of the ADNEX model for the discrimination between benign and malignant tumors was 0.93 (95% CI, 0.89-0.95). AUCs for the subtypes of malignancy (i.e. borderline, Stage I-IV and metastatic adnexal tumors) ranged between 0.60 and 0.90. Only subjective assessment (AUC, 0.96 (95% CI, 0.93-0.98)) was superior to the ADNEX model (P?=?0.01) in differentiating malignant from benign tumors. AUCs for the other models were 0.92 (95% CI, 0.89-0.95) for LR2, 0.85 (95% CI, 0.81-0.89) for RMI-I, 0.82 (95% CI, 0.77-0.86) for RMI-II and 0.84 (95% CI, 0.80-0.88) for RMI-III. At the proposed cut-off of ??10%, the ADNEX model had the highest sensitivity (0.98 (95% CI, 0.93-1.00)) but the lowest specificity (0.62 (95% CI, 0.55-0.68)) compared with the other models. Both subjective assessment (sensitivity, 0.90 (95% CI, 0.83-0.95); specificity 0.91 (95% CI, 0.86-0.94)) and the simple rules model with inconclusive cases classified by subjective assessment (sensitivity, 0.89 (95% CI, 0.81-0.94); specificity, 0.90 (95% CI, 0.85-0.94)) had lower sensitivity, but their sensitivity and specificity were better balanced.

Conclusions

Although the test performance of subjective assessment by an expert remains superior, the ADNEX model can help in the differentiation between benign and malignant ovarian tumors. The advantage of the ADNEX model as a polytomous model remains to be shown. © 2016 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

SUBMITTER: Meys EMJ

PROVIDER: S-EPMC5488216 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Estimating risk of malignancy in adnexal masses: external validation of the ADNEX model and comparison with other frequently used ultrasound methods.

Meys E M J EMJ Jeelof L S LS Achten N M J NMJ Slangen B F M BFM Lambrechts S S Kruitwagen R F P M RFPM Van Gorp T T

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology 20170601 6

<h4>Objectives</h4>To validate externally the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model and compare this model with other frequently used models in the differentiation between benign and malignant adnexal masses.<h4>Methods</h4>In this retrospective diagnostic accuracy study, we assessed data collected prospectively from patients with adnexal pathology who underwent real-time transvaginal or transrectal ultrasound by a single expert ultrasonographer in a t ...[more]

PMID: 27514486

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Project description:BackgroundBased on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology.MethodsIn a multicenter retrospective study, a total of 430 subjects with masses were collected in the adnexal region through an electronic medical record system at the Fourth Hospital of Harbin Medical University during the period of January 2019-April 2023. A total of 157 subjects were included in the exception validation cohort from Harbin Medical University Tumor Hospital. The pathological tumor findings were invoked as the gold standard to classify the subjects into benign and malignant groups. All patients were randomly allocated to the validation set and training set in a ratio of 7:3. A stepwise regression analysis was utilized for filtering variables. Logistic regression was conducted to construct a nomogram prediction model, which was further validated in the training set. The forest plot, C-index, calibration curve, and clinical decision curve were utilized to verify the model and assess its accuracy and validity, which were further compared with existing adnexal lesion models (O-RADS US) and assessments of different types of neoplasia in the adnexa (ADNEX).ResultsFour predictors as independent risk factors for malignancy were followed in the preparation of the diagnostic model: O-RADS classification, HE4 level, acoustic shadow, and protrusion blood flow score (all p < 0.05). The model showed moderate predictive power in the training set with a C-index of 0.959 (95%CI: 0.940-0.977), 0.929 (95%CI: 0.884-0.974) in the validation set, and 0.892 (95%CI: 0.843-0.940) in the external validation set. It showed that the predicted consequences of the nomogram agreed well with the actual results of the calibration curve, and the novel nomogram was clinically beneficial in decision curve analysis.ConclusionThe risk of the nomogram of adnexal masses with complex ultrasound morphology contained four characteristics that showed a suitable predictive ability and provided better risk stratification. Its diagnostic performance significantly exceeded that of the ADNEX model and O-RADS US, and its screening performance was essentially equivalent to that of the ADNEX model and O-RADS US classification.

Project description:BackgroundPre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA) method and previously described models.MethodsThis prospective, single-center observational study included consecutive patients. We collected systematic ultrasound and clinical data, including cancer antigen 125, D-dimer (DD) levels and platelet count. Histological examinations served as the reference standard. We performed univariate and multivariate regressions, and Bayesian information criterion (BIC) to assess the optimal model. Data were split into 2 subsets: training, for model development (190 observations) and testing, for model validation (n = 100).ResultsAmong 290 patients, 52% had malignant disease, including epithelial ovarian cancer (72.8%), metastatic disease (14.5%), borderline tumors (6.6%), and non-epithelial malignancies (4.6%). Significant variables were included into a multivariate analysis. The optimal model, included three independent factors: solid areas, the color score, and the DD level. Malignant and benign lesions had mean DD values of 2.837 and 0.354 μg/ml, respectively. We transformed established formulae into a web-based calculator ( http://gin-onc-calculators.com/gynonc.php ) for calculating the adnexal mass malignancy risk. The areas under the curve (AUCs) for models compared in the testing set were: our model (0.977), Simple Rules risk calculation (0.976), Assessment of Different NEoplasias in the adneXa (ADNEX) (0.972), Logistic Regression 2 (LR2) (0.969), Risk of Malignancy Index (RMI) 4 (0.932), SUA (0.930), and RMI3 (0.912).ConclusionsTwo simple ultrasound predictors and the DD level (also included in a mathematical model), when used by gynecologist oncologist, discriminated malignant from benign ovarian lesions as well or better than other more complex models and the SUA method. These parameters (and the model) may be clinically useful for planning adequate management in the cancer center. The model needs substantial validation.

Project description:To evaluate the accuracy of subjective assessment (SA), the International Ovarian Tumor Analysis (IOTA) group Simple Rules Risk (SRR) and the Assessment of Different NEoplasias in the adneXa (ADNEX) model for the preoperative differentiation of adnexal masses in pregnant women. The study population comprised 36 pregnant women (median age: 28.5 years old, range: 20-42 years old) with a mean gestation age of 13.5 (range: 8-31) weeks at diagnosis. Tumors were prospectively classified by local sonographers as probably benign or probably malignant using SA. Final tumor histological diagnosis was used as the reference standard in all cases. Logistic regression SRR and ADNEX models were used to obtain a risk score for every case. Serum CA125 and human epidydimis protein 4 (HE4) concentrations were also retrieved and the Risk of Ovarian Malignancy Algorithm (ROMA) value was calculated. The calculated predictive values included positive and negative likelihood ratios of ultrasound and biochemical tests. Final histology confirmed 27 benign and 9 malignant (including 2 borderline) masses. The highest sensitivity (89%) and specificity (70%) were found for the subjective tumor assessment. Although no malignancy was classified as benign using the SRR criteria (sensitivity = 100%), the specificity of this scoring system was only 37%. At the cut-off risk level of >20%, the ADNEX model had a sensitivity of 78% and a specificity of 70%. Serum levels of CA125, HE4 and the ROMA risk model correctly identified adnexal malignant tumors with a sensitivity of 67%, 25% and 25%, respectively. Corresponding specificities were 72%, 100% and 100%, respectively. The highest positive and negative likelihood ratios were found for SA (LR+ = 3.0 and LR- = 0.16, respectively). Overall diagnostic accuracy of all predictive methods used in this study were similar (range: 70-75%) except for SRR (53%). Subjective assessment remains the best predictive method in complex adnexal masses found at prenatal ultrasound in pregnant women. For less experienced sonographers, both the SRR and ADNEX scoring systems may be also used for the characterization of such tumors, while serum tumor markers CA125 and HE4, along with the ROMA algorithm appear to be less accurate.

Project description:ObjectiveTo determine the accuracy of interpretation of a non-contrast MRI protocol in characterizing adnexal masses.Methods and materialsTwo hundred ninety-one patients (350 adnexal masses) who underwent gynecological MRI at our institution between the 1st of January 2008 and the 31st of December 2018 were reviewed. A random subset (102 patients with 121 masses) was chosen to evaluate the reproducibility and repeatability of readers' assessments. Readers evaluated non-contrast MRI scans retrospectively, assigned a 5-point score for the risk of malignancy and gave a specific diagnosis. The reference standard for the diagnosis was histopathology or at least one-year imaging follow-up. Diagnostic accuracy of the non-contrast MRI score was calculated. Inter- and intra-reader agreement was analyzed with Cohen's kappa statistics.ResultsThere were 53/350 (15.1%) malignant lesions in the whole cohort and 20/121 (16.5%) malignant lesions in the random subset. Good agreement between readers was found for the non-contrast MRI score (к = 0.73, 95% confidence interval [CI] 0.58-0.86) whilst the intra-reader agreement was excellent (к = 0.81, 95% CI 0.70-0.88). The non-contrast MRI score value of ≥ 4 was associated with malignancy with a sensitivity of 84.9%, a specificity of 95.9%, an accuracy of 94.2% and a positive likelihood ratio of 21 (area under the receiver operating curve 0.93, 95% CI 0.90-0.96).ConclusionAdnexal mass characterization on MRI without the administration of contrast medium has a high accuracy and excellent inter- and intra-reader agreement. Our results suggest that non-contrast studies may offer a reasonable diagnostic alternative when the administration of intravenous contrast medium is not possible.Key points• A non-contrast pelvic MRI protocol may allow the characterization of adnexal masses with high accuracy. • The non-contrast MRI score may be used in clinical practice for differentiating benign from malignant adnexal lesions when the lack of intravenous contrast medium precludes analysis with the O-RADS MRI score.

Dataset Information

Estimating risk of malignancy in adnexal masses: external validation of the ADNEX model and comparison with other frequently used ultrasound methods.

Objectives

Methods

Results

Conclusions

Publications

Estimating risk of malignancy in adnexal masses: external validation of the ADNEX model and comparison with other frequently used ultrasound methods.

Similar Datasets

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