J Y Verbakel1,2, F Mascilini3, L Wynants4,5, D Fischerova6, A C Testa7, D Franchi8, F Frühauf6, D Cibula6, P G Lindqvist9, R Fruscio10, L A Haak11, G Opolskiene12, J L Alcazar13, V Mais14, J W Carlson15, P Sladkevicius16, D Timmerman4, L Valentin16, T Van Den Bosch4, E Epstein9. 1. Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium. 2. Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK. 3. Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli-IRCSS, Rome, Italy. 4. Department of Development and Regeneration, KU Leuven, Leuven, Belgium. 5. Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands. 6. Department of Obstetrics and Gynecology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic. 7. Department of Woman and Child Health, Università Cattolica del Sacro Cuore, Division of Gynecologic Oncology, Rome, Italy. 8. Department of Gynecological Oncology, Milan, Italy. 9. Department of Clinical Science and Education, Karolinska Institutet, and Department of Obstetrics and Gynecology, Södersjukhuset, Stockholm, Sweden. 10. Clinic of Obstetrics and Gynecology, University of Milan Bicocca, San Gerardo Hospital, Monza, Italy. 11. Institute for the Care of Mother and Child, Third Faculty of Medicine, Charles University, Prague, Czech Republic. 12. Center of Obstetrics and Gynecology, Vilnius University Hospital Santaros Klinikos, Vilnius University, Lithuania. 13. Department of Obstetrics and Gynecology, Clinica Universidad de Navarra, Pamplona, Spain. 14. Department of Obstetrics and Gynecology, University of Cagliari, Policlinico Universitario Duilio Casula, Monserrato, Cagliari, Italy. 15. Department of Pathology, Karolinska University Hospital, Stockholm, Sweden. 16. Department of Obstetrics and Gynecology, Skåne University Hospital, Malmö, Lund University, Sweden.
Abstract
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%.
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%.
Authors: Marco Ambrosio; Antonio Raffone; Andrea Alletto; Chiara Cini; Francesco Filipponi; Daniele Neola; Matilde Fabbri; Alessandro Arena; Diego Raimondo; Paolo Salucci; Manuela Guerrini; Antonio Travaglino; Roberto Paradisi; Antonio Mollo; Renato Seracchioli; Paolo Casadio Journal: Front Oncol Date: 2022-09-23 Impact factor: 5.738
Authors: Norbert Stachowicz; Agata Smoleń; Michał Ciebiera; Tomasz Łoziński; Paweł Poziemski; Dariusz Borowski; Artur Czekierdowski Journal: Diagnostics (Basel) Date: 2021-03-04