P. G. Lindqvist

Combination of Proactive Molecular Risk Classifier for Endometrial cancer (ProMisE) with sonographic and demographic characteristics in preoperative prediction of recurrence or progression of endometrial cancer

ABSTRACTObjectiveTo evaluate the ability of demographic and sonographic variables and the Proactive Molecular Risk Classifier for Endometrial cancer (ProMisE) classification to predict preoperatively tumor recurrence or progression in women with endometrial cancer.MethodsThe study included 339 women with histologically confirmed endometrial cancer who underwent expert transvaginal ultrasound in a single center before surgery as part of the prospective International Endometrial Tumor Analysis 4 study or who were evaluated using the same protocol. The tumors were classified according to histotype, FIGO (International Federation of Gynecology and Obstetrics) grade and FIGO stage. In addition, molecular analysis was performed for classification into the four ProMisE subtypes: polymerase‐ϵ exonuclease domain mutations (POLE EDM), mismatch repair proteins deficiency (MMR‐D), protein 53 wild type (p53 wt) and protein 53 abnormal (p53 abn). Demographic and preoperative sonographic characteristics, tumor recurrence or progression and survival were compared between the ProMisE subgroups. Cox regression analysis was used to identify prognostic factors associated with recurrence or progression, using univariable models to study crude associations and multivariable models to study adjusted associations. Logistic regression and receiver‐operating‐characteristics (ROC)‐curve analysis were used to assess the predictive ability of the preoperative prognostic factors regarding recurrence or progression of cancer within 3 years after surgery, and to compare their predictive ability to that of the European Society for Medical Oncology (ESMO) preoperative (based on depth of myometrial invasion, histotype and grade) and postoperative (based on histotype, grade, surgical stage and lymphovascular space invasion) risk classifications. In a separate subanalysis, cases were stratified according to ProMisE p53 abn status (present vs absent) and sonographic tumor size (anteroposterior (AP) diameter < 2 cm vs ≥ 2 cm).ResultsMedian follow‐up time from surgery was 58 months (interquartile range, 48–71 months; range, 0–102 months). Recurrence or progression of cancer occurred in 51/339 (15%) women, comprising 14% of those with MMR‐D, 8% of those with POLE EDM, 9% of those with p53 wt and 45% of those with p53 abn ProMisE subtype. On multivariable analysis, age, waist circumference, ProMisE subtype and tumor extension and AP diameter on ultrasound were associated with tumor recurrence or progression. A multivariable model comprising ProMisE subtype, age, waist circumference and sonographic tumor extension and size (area under the ROC curve (AUC), 0.89 (95% CI, 0.85–0.93)) had comparable ability to predict tumor recurrence/progression to that of a multivariable model comprising histotype, grade, age, waist circumference and sonographic tumor extension and size (AUC, 0.88 (95% CI, 0.83–0.92)), and better predictive ability than both the preoperative (AUC, 0.74 (95% CI, 0.67–0.82); P < 0.01) and postoperative (AUC, 0.79 (95% CI, 0.72–0.86); P < 0.01) ESMO risk classifications. Women with a combination of non‐p53 abn subtype and tumor size < 2 cm (164/339 (48%)) had a very low risk (1.8%) of tumor recurrence or progression.ConclusionsThe combination of demographic characteristics, sonographic findings and ProMisE subtype had better preoperative predictive ability for tumor recurrence or progression than did the ESMO classification, supporting their use in the preoperative risk stratification of women with endometrial cancer. The combination of p53 status with ultrasound tumor size has the potential to identify preoperatively a large group of women with a very low risk of recurrence or progression. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. ‐ Legal Statement: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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

ABSTRACTObjectiveTo 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.MethodsA 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).ResultsLymphadenectomy 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.ConclusionsBased 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.

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

ABSTRACTObjectivesTo 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).MethodsThe 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.ResultsIn 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.ConclusionsIn 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.