Publications by authors named "Andrea Mariani"

Objective: To investigate whether molecular classification could support individualized selection of patients with grade II endometrioid endometrial cancer for fertility-sparing approaches.

Methods: This is a retrospective multi-institutional study. Data of patients undergoing fertility-sparing treatment with a levonorgestrel intrauterine device (with or without oral hormonal therapy) were retrieved.

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Background: Literature is inconsistent with respect to clinical value of lymphovascular space invasion (LVSI) semiquantitative assessment. We aim to investigate the prognostic role of LVSI extent in stage I endometrioid endometrial carcinomas (ECs) classified by immunohistochemistry (IHC) analysis.

Methods: Patients with stage I endometrioid EC undergone primary surgery were retrospectively included.

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YEATS4 resides within the 12q13-15 chromosomal region, where it is frequently co-amplified with MDM2 and CDK4 in liposarcomas (LPS). However, its independent role in LPS progression and dedifferentiation remains poorly defined. In this study, YEATS4 expression was analyzed in 57 formalin-fixed paraffin-embedded (FFPE) LPS samples using quantitative real-time PCR and compared across histological subtypes.

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The NCCN Guidelines for Uterine Neoplasms provide recommendations for diagnostic workup, clinical staging, and treatment options for patients with endometrial cancer and uterine sarcoma. The NCCN Cervical Uterine Panel meets at least annually to review comments from reviewers within their institutions; examine relevant new data from publications, abstracts, and recent FDA approvals; and reevaluate and update recommendations. These NCCN Guidelines Insights summarize the panel's deliberations on the new FIGO 2023 staging system and updates on the new systemic therapy recommendations for the management of endometrial cancer.

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Uterine leiomyosarcoma is a rare and heterogeneous gynecological malignancy that poses a significant clinical challenge due to its aggressive nature and limited treatment options. Its multifactorial etiopathogenesis involves complex cytogenetic and molecular aberrations, including TP53, RB1, and chromothripsis-associated gene alterations. The non-specific clinical presentation, resembling other benign conditions, complicates early and accurate diagnosis, alongside intricate radiological and pathological patterns.

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Objective: Uterine carcinosarcoma without myoinvasion, limited to the endometrial lining/polyp or with no residual uterine disease at the time of hysterectomy, is extremely uncommon, with unknown oncologic outcomes. Thus, this study aimed to evaluate the long-term outcomes of patients with carcinosarcoma without myoinvasion.

Methods: Patients with International Federation of Gynecology and Obstetrics 2009 stage IA carcinosarcoma without myoinvasion who underwent surgery from December 1998 to January 2023 were identified from 11 centers worldwide.

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Objective: Textbook Oncologic Outcome (TOO) is a composite quality measure in surgical oncology associated with improved overall survival (OS). This study evaluated the prognostic impact of TOO and identified factors associated with achieving TOO in endometrial cancer (EC).

Methods: Patients undergoing surgery for presumed early-stage EC between 2018 and 2020 were identified in the National Cancer Database.

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High copy-number endometrial cancers (HCNECs) are dominated by excessive duplications scattered across the genome, termed here as the hyperduplication genomophenotype (HDGP). We identified locations and sizes of duplications in 171 endometrial cancer cases and designated 71 HCNEC cases as HDGP. We also investigated the response to the pan-ERBB inhibitor afatinib in a subset of HDGP-EC cases with duplications using a patient-derived three-dimensional culture model.

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Introduction: Endometrial cancer is one of the most common gynecologic malignancies, with increasing incidence, in developed countries. Advances in minimally invasive surgery, particularly laparoscopic with or without the use of computer-assisted ('robotic') platforms, have transformed its management, improving surgical outcomes and patient recovery.

Areas Covered: This review explores recent innovations in laparoscopic management of endometrial cancer, including robotic-assisted laparoscopic surgery, sentinel lymph node mapping, and the integration of artificial intelligence in surgical navigation.

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Background: In recent years, there has been a significant increase in the use of mechanical circulatory support devices, including the Impella device (Abiomed, Danvers, MA, USA), as hemodynamic support during high-risk percutaneous coronary intervention (PCI) and in acute management of cardiogenic shock.

Results: In this case series, we present two patients with non-ST-elevation myocardial infarction complicated by cardiogenic shock treated with Impella CP-protected PCI. After the revascularization, for both patients, a clinically relevant, access-site bleeding occurred, challenging the Impella CP maintenance.

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Objective: The prognosis and optimal management of patients with endometrial cancer with low-volume lymph node metastases remains unclear, particularly, regarding the role of molecular classification. This study investigates the distribution and prognostic role of molecular classes in this cohort of patients, while reviewing existing literature on this topic.

Methods: A multi-center, retrospective cohort study involving 8 institutions evaluated 134 patients with endometrial cancer and low-volume metastasis (isolated tumor cells: ≤0.

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Objective: This study assessed oncologic outcomes of patients with intermediate-risk endometrioid endometrial cancer and isolated tumor cells (ITC) (≤0.2 mm or ≤200 cells) in sentinel lymph nodes (SLNs).

Methods: Patients with SLN-ITC diagnosed between 2012 and 2019 were identified from 19 centers worldwide, while SLN-negative patients were identified at Mayo Clinic, Rochester between 2014 and 2018.

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In August 2023, the International Federation of Gynecology and Obstetrics introduced an updated staging system for endometrial cancer that integrates histopathologic and molecular characteristics (optional) of the tumor alongside with anatomic extent of the disease. This innovative approach aims to improve the prognostication of the system and the identification of treatment-relevant patient populations by more accurately stratifying patients based on tumor biology, representing a significant advancement toward personalized medicine. However, its implementation poses challenges, including the heterogeneous availability of molecular testing worldwide, and the need for further standardization and prospective validation of some of the newly introduced histopathological parameters.

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Artificial intelligence (AI), a branch of computer science focused on developing algorithms that replicate intelligent behaviour, has recently been used in patients management by enhancing diagnostic and prognostic capabilities of various resources such as hospital datasets, electrocardiograms and echocardiographic acquisitions. Machine learning (ML) and deep learning (DL) models, both key subsets of AI, have demonstrated robust applications across several cardiovascular diseases, from the most diffuse like hypertension and ischemic heart disease to the rare infiltrative cardiomyopathies, as well as to estimation of LDL cholesterol which can be achieved with better accuracy through AI. Additional emerging applications are encountered when unsupervised ML methodology shows promising results in identifying distinct clusters or phenotypes of patients with atrial fibrillation that may have different risks of stroke and response to therapy.

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Objective: Positive peritoneal cytology in endometrial cancer is a known risk factor for worse oncologic outcomes but is not used for staging purposes or to guide adjuvant treatment. Additionally, its prognostic impact on low-risk patients remains unclear. Therefore, we investigated the role of positive peritoneal cytology in patients with endometrial cancer and focused on low-risk disease.

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Acute coronary syndrome (ACS) is a global health concern that requires rapid and accurate diagnosis for timely intervention and better patient outcomes. With the emergence of Artificial Intelligence (AI), significant advancements have been made in improving diagnostic accuracy, efficiency, and risk stratification in ACS management. This narrative review examines the current landscape of AI applications in ACS diagnosis and risk stratification, emphasizing key methodologies, technical and clinical implementation challenges, and also possible future research directions.

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The multi-center, international consortium on endometrial cancer held in January 2025 at Mayo Clinic in Rochester, Minnesota brought together leading experts in gynecologic oncology to explore the latest advancements in the understanding, diagnosis, and treatment of endometrial cancer. Discussions centered on key topics, including updates in molecular testing and disease staging, emerging treatment strategies for advanced and recurrent disease, fertility-sparing management, and critical pathology challenges, particularly, the assessment of lympho-vascular space invasion. Each topic was examined in dedicated working group sessions, fostering in-depth exchanges to identify research priorities and develop actionable strategies.

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Background: It is unclear whether isolated tumor cells (ITCs) in sentinel lymph nodes (SLNs) adversely affect prognosis, especially in low-risk endometrial cancer. In a retrospective study, we showed a worse recurrence-free survival for low-risk endometrial cancer with ITCs than the node-negative group.

Primary Objective: Our aim is to evaluate whether the likelihood of disease recurrence differs between a prospective cohort of patients with low-risk endometrial cancer with ITCs and an historical cohort with negative SLNs.

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Objective: To compare the performance of four commonly used algorithms to differentiate benign from malignant adnexal masses when used by a novice operator.

Methods: Women with adnexal masses treated at Mayo Clinic, Rochester, Minnesota, in 2019 were identified retrospectively. Patients were included if they underwent surgery within 3 months of diagnosis or had at least 10 months of follow-up.

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Introduction: The 2023 FIGO staging of endometrial cancer integrates tumor grade and histology along with molecular features that recognize the prognostic significance of p53 and POLE mutations, accounting for potential conflicts such as lymphovascular space invasion and subserosal invasion.

Materials And Methods: In this single-institution retrospective study, data were collected on 229 endometrial cancer patients from January 2020 to September 2024 and re-stage them according to FIGO 2023 criteria.

Results: From FIGO stage 2009 IA, 70 patients do not cross stage (21 are FIGO 2023 IA1 and 49 IA2), 8 patients are upgraded to FIGO IC because of aggressive histotype; 1 is upstaged because of substantial LVSI, and 12 because of aggressive myoinfiltrating tumors (23 % of upstaging).

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Circulating tumor DNA (ctDNA) is a promising non-invasive tool that has been demonstrated to be a clinically useful biomarker in several tumor types for risk stratification, prognosis, and early detection of recurrence. However, there are limited data on the clinical utility of ctDNA in endometrial cancer (EC) compared with other solid tumors. The evolution of EC management through the integration of molecular characterization into the treatment algorithm has intensified the need to develop more effective predictive biomarkers to optimize treatment and reduce clinical toxicities.

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Background And Objectives: Robotic-assisted laparoscopy (RS) has been widely adopted for the management of endometrial cancer (EC) due to favorable perioperative outcomes, especially in the context of obesity, which is an established risk factor for EC. This study retrospectively evaluated the perioperative outcomes of RS versus conventional laparoscopy (LS) in treating EC and atypical endometrial hyperplasia (AH).

Methods: Between November 2021 and October 2023, 138 patients with AH or EC underwent surgery at the Clinic of Obstetric and Gynecological-Azienda Sanitaria Universitaria Friuli Centrale, Udine.

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Objective: The optimal treatment for patients with cervical stromal invasion (CSI) in endometrial cancer (EC) remains unclear. We aimed to test the prognostic role of molecular classification in EC patients with CSI.

Methods: A retrospective, multicenter review of EC patients with CSI was performed.

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Purpose: The prognostic significance of noninvasive myocardial work (MW) indices in patients undergoing transcatheter aortic valve implantation (TAVI) has not been adequately examined.

Methods: We retrospectively selected 88 consecutive patients (mean age 79.9 ± 6.

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