Validation of ultrasound strategies to assess tumor extension and to predict high-risk endometrial cancer in women from the prospective IETA (International Endometrial Tumor Analysis)-4 cohort.

OBJECTIVES: To compare the performance of ultrasound measurements and subjective ultrasound assessment (SA) in detecting deep myometrial invasion (MI) and cervical stromal invasion (CSI) in women with endometrial cancer, overall and according to whether they had low- or high-grade disease separately, and to validate published measurement cut-offs and prediction models to identify MI, CSI and high-risk disease (Grade-3 endometrioid or non-endometrioid cancer and/or deep MI and/or CSI). METHODS: The study comprised 1538 patients with endometrial cancer from the International Endometrial Tumor Analysis (IETA)-4 prospective multicenter study, who underwent standardized expert transvaginal ultrasound examination. SA and ultrasound measurements were used to predict deep MI and CSI. We assessed the diagnostic accuracy of the tumor/uterine anteroposterior (AP) diameter ratio for detecting deep MI and that of the distance from the lower margin of the tumor to the outer cervical os (Dist-OCO) for detecting CSI. We also validated two two-step strategies for the prediction of high-risk cancer; in the first step, biopsy-confirmed Grade-3 endometrioid or mucinous or non-endometrioid cancers were classified as high-risk cancer, while the second step encompassed the application of a mathematical model to classify the remaining tumors. The 'subjective prediction model' included biopsy grade (Grade 1 vs Grade 2) and subjective assessment of deep MI or CSI (presence or absence) as variables, while the 'objective prediction model' included biopsy grade (Grade 1 vs Grade 2) and minimal tumor-free margin. The predictive performance of the two two-step strategies was compared with that of simply classifying patients as high risk if either deep MI or CSI was suspected based on SA or if biopsy showed Grade-3 endometrioid or mucinous or non-endometrioid histotype (i.e. combining SA with biopsy grade). Histological assessment from hysterectomy was considered the reference standard. RESULTS: In 1275 patients with measurable lesions, the sensitivity and specificity of SA for detecting deep MI was 70% and 80%, respectively, in patients with a Grade-1 or -2 endometrioid or mucinous tumor vs 76% and 64% in patients with a Grade-3 endometrioid or mucinous or a non-endometrioid tumor. The corresponding values for the detection of CSI were 51% and 94% vs 50% and 91%. Tumor AP diameter and tumor/uterine AP diameter ratio showed the best performance for predicting deep MI (area under the receiver-operating characteristics curve (AUC) of 0.76 and 0.77, respectively), and Dist-OCO had the best performance for predicting CSI (AUC, 0.72). The proportion of patients classified correctly as having high-risk cancer was 80% when simply combining SA with biopsy grade vs 80% and 74% when using the subjective and objective two-step strategies, respectively. The subjective and objective models had an AUC of 0.76 and 0.75, respectively, when applied to Grade-1 and -2 endometrioid tumors. CONCLUSIONS: In the hands of experienced ultrasound examiners, SA was superior to ultrasound measurements for the prediction of deep MI and CSI of endometrial cancer, especially in patients with a Grade-1 or -2 tumor. The mathematical models for the prediction of high-risk cancer performed as expected. The best strategies for predicting high-risk endometrial cancer were combining SA with biopsy grade and the subjective two-step strategy, both having an accuracy of 80%. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Ultrasound-based risk model for preoperative prediction of lymph-node metastases in women with endometrial cancer: model-development study.

OBJECTIVE: To develop a preoperative risk model, using endometrial biopsy results and clinical and ultrasound variables, to predict the individual risk of lymph-node metastases in women with endometrial cancer. METHODS: A mixed-effects logistic regression model for prediction of lymph-node metastases was developed in 1501 prospectively included women with endometrial cancer undergoing transvaginal ultrasound examination before surgery, from 16 European centers. Missing data, including missing lymph-node status, were imputed. Discrimination, calibration and clinical utility of the model were evaluated using leave-center-out cross validation. The predictive performance of the model was compared with that of risk classification from endometrial biopsy alone (high-risk defined as endometrioid cancer Grade 3/non-endometrioid cancer) or combined endometrial biopsy and ultrasound (high-risk defined as endometrioid cancer Grade 3/non-endometrioid cancer/deep myometrial invasion/cervical stromal invasion/extrauterine spread). RESULTS: Lymphadenectomy was performed in 691 women, of whom 127 had lymph-node metastases. The model for prediction of lymph-node metastases included the predictors age, duration of abnormal bleeding, endometrial biopsy result, tumor extension and tumor size according to ultrasound and undefined tumor with an unmeasurable endometrium. The model's area under the curve was 0.73 (95% CI, 0.68-0.78), the calibration slope was 1.06 (95% CI, 0.79-1.34) and the calibration intercept was 0.06 (95% CI, -0.15 to 0.27). Using a risk threshold for lymph-node metastases of 5% compared with 20%, the model had, respectively, a sensitivity of 98% vs 48% and specificity of 11% vs 80%. The model had higher sensitivity and specificity than did classification as high-risk, according to endometrial biopsy alone (50% vs 35% and 80% vs 77%, respectively) or combined endometrial biopsy and ultrasound (80% vs 75% and 53% vs 52%, respectively). The model's clinical utility was higher than that of endometrial biopsy alone or combined endometrial biopsy and ultrasound at any given risk threshold. CONCLUSIONS: Based on endometrial biopsy results and clinical and ultrasound characteristics, the individual risk of lymph-node metastases in women with endometrial cancer can be estimated reliably before surgery. The model is superior to risk classification by endometrial biopsy alone or in combination with ultrasound. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Ultrasound characteristics of endometrial cancer as defined by International Endometrial Tumor Analysis (IETA) consensus nomenclature: prospective multicenter study.

OBJECTIVE: To describe the sonographic features of endometrial cancer in relation to tumor stage, grade and histological type, using the International Endometrial Tumor Analysis (IETA) terminology. METHODS: This was a prospective multicenter study of 1714 women with biopsy-confirmed endometrial cancer undergoing standardized transvaginal grayscale and Doppler ultrasound examination according to the IETA study protocol, by experienced ultrasound examiners using high-end ultrasound equipment. Clinical and sonographic data were entered into a web-based database. We assessed how strongly sonographic characteristics, according to IETA, were associated with outcome at hysterectomy, i.e. tumor stage, grade and histological type, using univariable logistic regression and the c-statistic. RESULTS: In total, 1538 women were included in the final analysis. Median age was 65 (range, 27-98) years, median body mass index was 28.4 (range 16-67) kg/m2 , 1377 (89.5%) women were postmenopausal and 1296 (84.3%) reported abnormal vaginal bleeding. Grayscale and color Doppler features varied according to grade and stage of tumor. High-risk tumors, compared with low-risk tumors, were less likely to have regular endometrial-myometrial junction (difference of -23%; 95% CI, -27 to -18%), were larger (mean endometrial thickness; difference of +9%; 95% CI, +8 to +11%), and were more likely to have non-uniform echogenicity (difference of +7%; 95% CI, +1 to +13%), a multiple, multifocal vessel pattern (difference of +21%; 95% CI, +16 to +26%) and a moderate or high color score (difference of +22%; 95% CI, +18 to +27%). CONCLUSION: Grayscale and color Doppler sonographic features are associated with grade and stage of tumor, and differ between high- and low-risk endometrial cancer. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.