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Dinoi G, Garzon S, Weaver A, McGree M, Glaser G, Langstraat C, Kumar A, Weroha J, Garda AE, Shahi M, Palmieri E, Scambia G, Fanfani F, Mariani A. How deep is too deep? Assessing myometrial invasion as a predictor of distant recurrence in stage I endometrioid endometrial cancer. Int J Gynecol Cancer 2024; 34:1389-1398. [PMID: 38821549 DOI: 10.1136/ijgc-2023-005217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2024] Open
Abstract
OBJECTIVES The goal of this study was to evaluate the depth of myometrial invasion as a predictor of distant recurrence in patients with node-negative stage IB endometrioid endometrial cancer. METHODS A retrospective multicenter study, including surgically staged endometrial cancer patients at Mayo Clinic, Rochester (MN, USA) between January 1999 and December 2017, and Fondazione Policlinico Universitario A. Gemelli (Rome, Italy) between March 2002 and March 2017, was conducted. Patients without lymph node assessment were excluded. The follow-up was restricted to the first 5 years following surgery. Recurrence-free survival was estimated using the Kaplan-Meier method. Cox proportional hazards models were fit to evaluate the association of clinical and pathologic characteristics with the risk of recurrence. RESULTS Of 386 patients, the mean (SD) depth of myometrial invasion was 70.4 (13.2)%. We identified 51 recurrences (14 isolated vaginal, 37 non-vaginal); the median follow-up of the remaining patients was 4.5 (IQR 2.3-7.0) years. At univariate analysis, the risk of non-vaginal recurrence increased by 64% (95% CI 1.28 to 2.12) for every 10-unit increase in the depth of myometrial invasion. International Federation of Gynecology and Obstetrics (FIGO) grade and myometrial invasion were independent predictors of non-vaginal recurrence. The 5-year non-vaginal recurrence-free survival was 95.2% (95% CI 92.0% to 98.6%), 84.0% (95% CI 76.6% to 92.1%), and 67.1% (95% CI 54.2% to 83.0%) for subsets of patients with myometrial invasion <71% (n=207), myometrial invasion ≥71% and grade 1-2 (n=132), and myometrial invasion ≥71% and grade 3 (n=47), respectively. A total of 256 (66.3%) patients received either vaginal brachytherapy only or no adjuvant therapy. Patients who received adjuvant chemotherapy, regardless of receipt of external beam radiotherapy or vaginal brachytherapy, had an approximately 70% lower risk of any recurrence (HR adjusted for age, grade, myometrial invasion 0.31, 95% CI 0.12 to 0.85) and of non-vaginal recurrence (adjusted HR 0.32, 95% CI 0.10 to 0.99). CONCLUSION The invasion of the outer third of the myometrium and histologic grade were found to be independent predictors of distant recurrence among patients with endometrioid, node-negative stage IB endometrial cancer. Future studies should investigate if systemic adjuvant therapy for patients with myometrial invasion of the outer third would improve outcomes.
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Affiliation(s)
- Giorgia Dinoi
- UOC Ginecologia Oncologica, Dipartimento di Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy
| | - Simone Garzon
- Department of Obstetrics and Gynaecology, University of Verona, Verona, Italy
| | - Amy Weaver
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Michaela McGree
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Gretchen Glaser
- Division of Gynecologic Surgery, Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, Minnesota, USA
| | - Carrie Langstraat
- Division of Gynecologic Surgery, Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, Minnesota, USA
| | - Amanika Kumar
- Division of Gynecologic Surgery, Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, Minnesota, USA
| | - John Weroha
- Division of Medical Oncology, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Allison E Garda
- Department of Radiation Oncology, Mayo Clinic in Rochester, Rochester, Minnesota, USA
| | - Maryam Shahi
- Department of Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Emilia Palmieri
- Division of Gynecologic Surgery, Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, Minnesota, USA
- Università Cattolica del Sacro Cuore, Rome, Italy
| | - Giovanni Scambia
- UOC Ginecologia Oncologica, Dipartimento di Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy
- Università Cattolica del Sacro Cuore, Rome, Italy
| | - Francesco Fanfani
- UOC Ginecologia Oncologica, Dipartimento di Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy
- Università Cattolica del Sacro Cuore, Rome, Italy
| | - Andrea Mariani
- Division of Gynecologic Surgery, Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, Minnesota, USA
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Yasar S, Yagin FH, Melekoglu R, Ardigò LP. Integrating proteomics and explainable artificial intelligence: a comprehensive analysis of protein biomarkers for endometrial cancer diagnosis and prognosis. Front Mol Biosci 2024; 11:1389325. [PMID: 38894711 PMCID: PMC11184912 DOI: 10.3389/fmolb.2024.1389325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 05/16/2024] [Indexed: 06/21/2024] Open
Abstract
Endometrial cancer, which is the most common gynaecological cancer in women after breast, colorectal and lung cancer, can be diagnosed at an early stage. The first aim of this study is to classify age, tumor grade, myometrial invasion and tumor size, which play an important role in the diagnosis and prognosis of endometrial cancer, with machine learning methods combined with explainable artificial intelligence. 20 endometrial cancer patients proteomic data obtained from tumor biopsies taken from different regions of EC tissue were used. The data obtained were then classified according to age, tumor size, tumor grade and myometrial invasion. Then, by using three different machine learning methods, explainable artificial intelligence was applied to the model that best classifies these groups and possible protein biomarkers that can be used in endometrial prognosis were evaluated. The optimal model for age classification was XGBoost with AUC (98.8%), for tumor grade classification was XGBoost with AUC (98.6%), for myometrial invasion classification was LightGBM with AUC (95.1%), and finally for tumor size classification was XGBoost with AUC (94.8%). By combining the optimal models and the SHAP approach, possible protein biomarkers and their expressions were obtained for classification. Finally, EWRS1 protein was found to be common in three groups (age, myometrial invasion, tumor size). This article's findings indicate that models have been developed that can accurately classify factors including age, tumor grade, and myometrial invasion all of which are critical for determining the prognosis of endometrial cancer as well as potential protein biomarkers associated with these factors. Furthermore, we were able to provide an analysis of how the quantities of the proteins suggested as biomarkers varied throughout the classes by combining the SHAP values with these ideal models.
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Affiliation(s)
- Seyma Yasar
- Department of Biostatistics, and Medical Informatics, Medicine Faculty, Inonu University, Malatya, Türkiye
| | - Fatma Hilal Yagin
- Department of Biostatistics, and Medical Informatics, Medicine Faculty, Inonu University, Malatya, Türkiye
| | - Rauf Melekoglu
- Department of Obstetrics and Gynecology, Faculty of Medicine, Inonu University, Malatya, Türkiye
| | - Luca Paolo Ardigò
- Department of Teacher Education, NLA University College, Oslo, Norway
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Wang J, Fang Y, Chen T, Xin Z, Wu Y, Yang X. A Case Report of Consecutive Live Birth Twice Through in vitro Fertilization and Embryo Transfer After Endometrial Carcinoma Fertility Preservation Treatment. Int J Womens Health 2024; 16:395-400. [PMID: 38463685 PMCID: PMC10924884 DOI: 10.2147/ijwh.s441984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 02/25/2024] [Indexed: 03/12/2024] Open
Abstract
Preserving fertility is a vital concern for young women diagnosed with endometrial carcinoma. The clinical management of such patients is often disappointing. It is rare to have two consecutive successful pregnancies. We present a child-bearing-age woman who underwent fertility preservation therapy due to endometrial carcinoma. Following fertility preservation therapy, she underwent in vitro fertilization and embryo transfer. After receiving her first fresh embryo transfer, she successfully conceived and gave birth to a healthy child. Two years after the first embryo transfer and regular follow-up, she had another frozen embryo transfer of two cleavage embryos and successfully gave birth to another healthy baby. After the delivery of her second child, she underwent surgical treatment for endometrial carcinoma. For endometrial carcinoma patients who intend to preserve fertility, high-quality long-term follow-up and personalized treatment are necessary.
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Affiliation(s)
- Jingying Wang
- Department of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, People's Republic of China
- Department of Human Reproductive Medicine, Beijing Maternal and Child Health Care Hospital, Beijing, People's Republic of China
| | - Ying Fang
- Department of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, People's Republic of China
- Department of Human Reproductive Medicine, Beijing Maternal and Child Health Care Hospital, Beijing, People's Republic of China
| | - Tong Chen
- Department of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, People's Republic of China
- Department of Human Reproductive Medicine, Beijing Maternal and Child Health Care Hospital, Beijing, People's Republic of China
| | - Zhimin Xin
- Department of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, People's Republic of China
- Department of Human Reproductive Medicine, Beijing Maternal and Child Health Care Hospital, Beijing, People's Republic of China
| | - Yumei Wu
- Department of Gynecological Oncology, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, People's Republic of China
- Department of Gynecological Oncology, Beijing Maternal and Child Health Care Hospital, Beijing, People's Republic of China
| | - Xiaokui Yang
- Department of Human Reproductive Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, People's Republic of China
- Department of Human Reproductive Medicine, Beijing Maternal and Child Health Care Hospital, Beijing, People's Republic of China
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Pino I, Gozzini E, Radice D, Boveri S, Iacobone AD, Vidal Urbinati AM, Multinu F, Gullo G, Cucinella G, Franchi D. Advancing Tailored Treatments: A Predictive Nomogram, Based on Ultrasound and Laboratory Data, for Assessing Nodal Involvement in Endometrial Cancer Patients. J Clin Med 2024; 13:496. [PMID: 38256630 PMCID: PMC10816430 DOI: 10.3390/jcm13020496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/12/2024] [Accepted: 01/13/2024] [Indexed: 01/24/2024] Open
Abstract
Assessing lymph node metastasis is crucial in determining the optimal therapeutic approach for endometrial cancer (EC). Considering the impact of lymphadenectomy, there is an urgent need for a cost-effective and easily applicable method to evaluate the risk of lymph node metastasis in cases of sentinel lymph node (SLN) biopsy failure. This retrospective monocentric study enrolled EC patients, who underwent surgical staging with nodal assessment. Data concerning demographic, clinicopathological, ultrasound, and surgical characteristics were collected from medical records. Ultrasound examinations were conducted in accordance with the IETA statement. We identified 425 patients, and, after applying exclusion criteria, the analysis included 313 women. Parameters incorporated into the nomogram were selected via univariate and multivariable analyses, including platelet count, myometrial infiltration, minimal tumor-free margin, and CA 125. The nomogram exhibited good accuracy in predicting lymph node involvement, with an AUC of 0.88. Using a cutoff of 10% likelihood of nodal involvement, the nomogram displayed a low false-negative rate of 0.04 (95% CI 0.00-0.19) in the training set. The adaptability of this straightforward model renders it suitable for implementation across diverse clinical settings, aiding gynecological oncologists in preoperative patient evaluations and facilitating the design of personalized treatments. However, external validation is mandatory for confirming diagnostic accuracy.
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Affiliation(s)
- Ida Pino
- Preventive Gynecology Unit, European Institute of Oncology IRCCS, 20141 Milan, Italy; (A.D.I.); (A.M.V.U.); (D.F.)
| | - Elisa Gozzini
- Department of Clinical and Experimental Sciences, University of Brescia, 25123 Brescia, Italy;
| | - Davide Radice
- Division of Epidemiology and Biostatistics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy;
| | - Sara Boveri
- Laboratory of Biostatistics and Data Management, Scientific Directorate, IRCCS Policlinico San Donato, San Donato Milanese, 20097 Milan, Italy;
| | - Anna Daniela Iacobone
- Preventive Gynecology Unit, European Institute of Oncology IRCCS, 20141 Milan, Italy; (A.D.I.); (A.M.V.U.); (D.F.)
| | - Ailyn Mariela Vidal Urbinati
- Preventive Gynecology Unit, European Institute of Oncology IRCCS, 20141 Milan, Italy; (A.D.I.); (A.M.V.U.); (D.F.)
- Department of Clinical and Experimental Sciences, University of Brescia, 25123 Brescia, Italy;
- Division of Epidemiology and Biostatistics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy;
- Laboratory of Biostatistics and Data Management, Scientific Directorate, IRCCS Policlinico San Donato, San Donato Milanese, 20097 Milan, Italy;
- Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
| | - Francesco Multinu
- Department of Gynecologic Surgery, IRCCS European Institute of Oncology, 20141 Milan, Italy;
| | - Giuseppe Gullo
- Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, University of Palermo, 90146 Palermo, Italy; (G.G.); (G.C.)
| | - Gaspare Cucinella
- Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, University of Palermo, 90146 Palermo, Italy; (G.G.); (G.C.)
| | - Dorella Franchi
- Preventive Gynecology Unit, European Institute of Oncology IRCCS, 20141 Milan, Italy; (A.D.I.); (A.M.V.U.); (D.F.)
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