Cancers (Dec 2023)
Concurrent Endometrial Cancer in Women with Atypical Endometrial Hyperplasia: What Is the Predictive Value of Patient Characteristics?
- Luca Giannella,
- Francesco Piva,
- Giovanni Delli Carpini,
- Jacopo Di Giuseppe,
- Camilla Grelloni,
- Matteo Giulietti,
- Francesco Sopracordevole,
- Giorgio Giorda,
- Anna Del Fabro,
- Nicolò Clemente,
- Barbara Gardella,
- Giorgio Bogani,
- Orsola Brasile,
- Ruby Martinello,
- Marta Caretto,
- Alessandro Ghelardi,
- Gianluca Albanesi,
- Guido Stevenazzi,
- Paolo Venturini,
- Maria Papiccio,
- Marco Cannì,
- Maggiorino Barbero,
- Massimiliano Fambrini,
- Veronica Maggi,
- Stefano Uccella,
- Arsenio Spinillo,
- Francesco Raspagliesi,
- Pantaleo Greco,
- Tommaso Simoncini,
- Felice Petraglia,
- Andrea Ciavattini
Affiliations
- Luca Giannella
- Woman’s Health Sciences Department, Gynecologic Section, Polytechnic University of Marche, 60123 Ancona, Italy
- Francesco Piva
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
- Giovanni Delli Carpini
- Woman’s Health Sciences Department, Gynecologic Section, Polytechnic University of Marche, 60123 Ancona, Italy
- Jacopo Di Giuseppe
- Woman’s Health Sciences Department, Gynecologic Section, Polytechnic University of Marche, 60123 Ancona, Italy
- Camilla Grelloni
- Woman’s Health Sciences Department, Gynecologic Section, Polytechnic University of Marche, 60123 Ancona, Italy
- Matteo Giulietti
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
- Francesco Sopracordevole
- Gynecologic Oncology Unit, IRCCS—Centro di Riferimento Oncologico di Aviano, 33081 Aviano, Italy
- Giorgio Giorda
- Gynecologic Oncology Unit, IRCCS—Centro di Riferimento Oncologico di Aviano, 33081 Aviano, Italy
- Anna Del Fabro
- Gynecologic Oncology Unit, IRCCS—Centro di Riferimento Oncologico di Aviano, 33081 Aviano, Italy
- Nicolò Clemente
- Gynecologic Oncology Unit, IRCCS—Centro di Riferimento Oncologico di Aviano, 33081 Aviano, Italy
- Barbara Gardella
- Department of Obstetrics and Gynecology, Fondazione IRCCS Policlinico San Matteo, Università degli Studi di Pavia, 27100 Pavia, Italy
- Giorgio Bogani
- Gynecological Oncology Unit, Fondazione IRCCS—Istituto Nazionale Tumori, 20133 Milano, Italy
- Orsola Brasile
- Section of Obstetrics and Gynecology, Department of Medical Sciences, University of Ferrara, 44124 Ferrara, Italy
- Ruby Martinello
- Section of Obstetrics and Gynecology, Department of Medical Sciences, University of Ferrara, 44124 Ferrara, Italy
- Marta Caretto
- Division of Obstetrics and Gynecology, Department of Clinical and Experimental Medicine, University of Pisa, 56124 Pisa, Italy
- Alessandro Ghelardi
- UOC Ostetricia e Ginecologia, Ospedale Apuane, Azienda Usl Toscana Nord-Ovest, 54100 Massa, Italy
- Gianluca Albanesi
- UOC Ostetricia e Ginecologia, Ospedale Apuane, Azienda Usl Toscana Nord-Ovest, 54100 Massa, Italy
- Guido Stevenazzi
- Department of Obstetrics and Gynaecology, ASST Ovest MI, Legnano (Milan) Hospital, 20025 Legnano, Italy
- Paolo Venturini
- Division of Obstetrics and Gynecology, AUSL di Modena, 41012 Carpi, Italy
- Maria Papiccio
- Division of Obstetrics and Gynecology, AUSL di Modena, 41012 Carpi, Italy
- Marco Cannì
- Department of Obstetrics and Gynecology, Asti Community Hospital, 14100 Asti, Italy
- Maggiorino Barbero
- Department of Obstetrics and Gynecology, Asti Community Hospital, 14100 Asti, Italy
- Massimiliano Fambrini
- Obstetrics and Gynecology, Department of Experimental, Clinical, and Biomedical Sciences, Careggi University Hospital, University of Florence, 50121 Florence, Italy
- Veronica Maggi
- Department of Obstetrics and Gynecology, University of Verona, 37129 Verona, Italy
- Stefano Uccella
- Department of Obstetrics and Gynecology, University of Verona, 37129 Verona, Italy
- Arsenio Spinillo
- Department of Obstetrics and Gynecology, Fondazione IRCCS Policlinico San Matteo, Università degli Studi di Pavia, 27100 Pavia, Italy
- Francesco Raspagliesi
- Gynecological Oncology Unit, Fondazione IRCCS—Istituto Nazionale Tumori, 20133 Milano, Italy
- Pantaleo Greco
- Section of Obstetrics and Gynecology, Department of Medical Sciences, University of Ferrara, 44124 Ferrara, Italy
- Tommaso Simoncini
- Division of Obstetrics and Gynecology, Department of Clinical and Experimental Medicine, University of Pisa, 56124 Pisa, Italy
- Felice Petraglia
- Obstetrics and Gynecology, Department of Experimental, Clinical, and Biomedical Sciences, Careggi University Hospital, University of Florence, 50121 Florence, Italy
- Andrea Ciavattini
- Woman’s Health Sciences Department, Gynecologic Section, Polytechnic University of Marche, 60123 Ancona, Italy
- DOI
- https://doi.org/10.3390/cancers16010172
- Journal volume & issue
-
Vol. 16,
no. 1
p. 172
Abstract
Background: The rate of concurrent endometrial cancer (EC) in atypical endometrial hyperplasia (AEH) can be as high as 40%. Some patient characteristics showed associations with this occurrence. However, their real predictive power with related validation has yet to be discovered. The present study aimed to assess the performance of various models based on patient characteristics in predicting EC in women with AEH. Methods: This is a retrospective multi-institutional study including women with AEH undergoing definitive surgery. The women were divided according to the final histology (EC vs. no-EC). The available cases were divided into a training and validation set. Using k-fold cross-validation, we built many predictive models, including regressions and artificial neural networks (ANN). Results: A total of 193/629 women (30.7%) showed EC at hysterectomy. A total of 26/193 (13.4%) women showed high-risk EC. Regression and ANN models showed a prediction performance with a mean area under the curve of 0.65 and 0.75 on the validation set, respectively. Among the best prediction models, the most recurrent patient characteristics were age, body mass index, Lynch syndrome, diabetes, and previous breast cancer. None of these independent variables showed associations with high-risk diseases in women with EC. Conclusions: Patient characteristics did not show satisfactory performance in predicting EC in AEH. Risk stratification in AEH based mainly on patient characteristics may be clinically unsuitable.
Keywords
- atypical endometrial hyperplasia
- endometrial cancer
- artificial intelligence
- regression models
- prediction model
- patient characteristics