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An ultrasound-based risk model to predict lymph node metastases before surgery in women with endometrial cancer: a model development study.
File | Description | Size | Format | |
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LN Risk Prediction UOG 2019.docx | Accepted version | 98.12 kB | Microsoft Word | View/Open |
Title: | An ultrasound-based risk model to predict lymph node metastases before surgery in women with endometrial cancer: a model development study. |
Authors: | Eriksson, LSE Epstein, E Testa, AC Fischerova, D Valentin, L Sladkevicius, P Franchi, D Frühauf, F Fruscio, R Haak, LA Opolskiene, G Mascilini, F Alcazar, JL Van Holsbeke, C Chiappa, V Bourne, T Lindqvist, PG Van Calster, B Timmerman, D Verbakel, JY Van den Bosch, T Wynants, L |
Item Type: | Journal Article |
Abstract: | OBJECTIVES: To develop a pre-operative risk model using endometrial biopsy results, 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 was developed on 1501 prospectively included women with endometrial cancer subjected to transvaginal ultrasound examination before surgery. Missing data, including missing lymph node status, was imputed. Discrimination, calibration and clinical utility were evaluated using leave-center-out cross-validation. The predictive performance was compared with risk classification from endometrial biopsy alone (high-risk = endometrioid cancer grade 3/non-endometrioid cancer) or combined endometrial biopsy and ultrasound (high-risk = endometrioid cancer grade 3/non-endometrioid cancer/deep myometrial invasion/cervical stromal invasion/extrauterine spread). RESULTS: Lymphadenectomy was performed in 691 women, of which 127 had lymph node metastases. The model 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 AUC was 0.73 (95% CI 0.68 to 0.78), calibration slope 1.06 (95% CI 0.79 to 1.34) and calibration intercept 0.06 (95% CI 0.15 to 0.27). Using risk thresholds for lymph node metastases 5% vs. 20% the model had sensitivity 98% vs. 48% and specificity 11% vs. 80%. The model had higher sensitivity and specificity than high-risk according to endometrial biopsy alone (50% vs. 35% and 80% vs. 77%) or combined endometrial biopsy and ultrasound (80% vs. 75% and 53% vs. 52%). 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, clinical and ultrasound characteristics, the individual risk of lymph node metastases in women with endometrial cancer can be reliably estimated before surgery. The model is superior to risk classification by endometrial biopsy alone or in combination with ultrasound. This article is protected by copyright. All rights reserved. |
Issue Date: | 1-Sep-2020 |
Date of Acceptance: | 7-Dec-2019 |
URI: | http://hdl.handle.net/10044/1/76397 |
DOI: | 10.1002/uog.21950 |
ISSN: | 0960-7692 |
Publisher: | Wiley |
Start Page: | 443 |
End Page: | 452 |
Journal / Book Title: | Ultrasound in Obstetrics and Gynecology |
Volume: | 56 |
Issue: | 3 |
Copyright Statement: | © 2019 ISUOG. Published by John Wiley & Sons Ltd. . This is the peer reviewed version of the following article, which has been published in final form at https://obgyn.onlinelibrary.wiley.com/doi/full/10.1002/uog.21950. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. |
Keywords: | decision support model diagnostic imaging endometrial neoplasm lymphatic metastasis neoplasm staging ultrasonography decision support model diagnostic imaging endometrial neoplasm lymphatic metastasis neoplasm staging ultrasonography Obstetrics & Reproductive Medicine 1114 Paediatrics and Reproductive Medicine |
Publication Status: | Published |
Conference Place: | England |
Online Publication Date: | 2019-12-16 |
Appears in Collections: | Department of Metabolism, Digestion and Reproduction Faculty of Medicine |