Endometrial cancer is the most common gynaecological cancer in high income countries and its incidence is rising globally. Although an ageing population and fewer benign hysterectomies have contributed to this trend, the growing prevalence of obesity is the major underlying cause. Obesity poses challenges for diagnosis and treatment and more research is needed to offer primary prevention to high-risk women and to optimise endometrial cancer survivorship. Early presentation with postmenopausal bleeding ensures most endometrial cancers are cured by hysterectomy but those with advanced disease have a poor prognosis. Minimally invasive surgical staging and sentinel-lymph-node biopsy provides a low morbidity alternative to historical surgical management without compromising oncological outcomes. Adjuvant radiotherapy reduces loco-regional recurrence in intermediate-risk and high-risk cases. Advances in our understanding of the molecular biology of endometrial cancer have paved the way for targeted chemotherapeutic strategies, and clinical trials will establish their benefit in adjuvant, advanced, and recurrent disease settings in the coming years.Copyright © 2022 Elsevier Ltd. All rights reserved.

Lymphovascular space invasion (LVSI) is an independent risk factor for recurrence and poor survival in early-stage endometrioid endometrial cancer (EEC), but optimal adjuvant treatment is unknown. We aimed to compare the survival of women with early-stage EEC with LVSI treated postoperatively with observation (OBS), radiation (RAD, external beam and/or vaginal brachytherapy), or chemotherapy (CHEMO)+/-RAD.This was a multi-institutional, retrospective cohort study of women with stage I or II EEC with LVSI who underwent hysterectomy+/-lymphadenectomy from 2005 to 2015 and received OBS, RAD, or CHEMO+/-RAD postoperatively. Progression-free survival and overall survival were evaluated using Kaplan-Meier estimates and Cox proportional hazards models.In total, 478 women were included; median age was 64 years, median follow-up was 50.3 months. After surgery, 143 (30%) underwent OBS, 232 (48.5%) received RAD, and 103(21.5%) received CHEMO+/-RAD (95% of whom received RAD). Demographics were similar among groups, but those undergoing OBS had lower stage and grade. A total of 101 (21%) women recurred. Progression-free survival (PFS) was improved in both CHEMO+/-RAD (HR = 0.18, 95% CI: 0.09-0.39) and RAD (HR = 0.31, 95% CI: 0.18-0.54) groups compared to OBS, though neither adjuvant therapy was superior to the other. However, in grade 3 tumors, the CHEMO+/-RAD group had superior PFS compared to both RAD (HR 0.25; 95% CI: 0.12-0.52) and OBS cohorts (HR = 0.10, 95% CI: 0.03-0.32). Overall survival did not differ by treatment.In early-stage EEC with LVSI, adjuvant therapy improved PFS compared to observation alone. In those with grade 3 EEC, adjuvant chemotherapy with or without radiation improved PFS compared to observation or radiation alone.Copyright © 2020 Elsevier Inc. All rights reserved.

The aim of the study was to present a comprehensive analysis of disease recurrence in a large Danish cohort of women with early-stage endometrial cancer treated according to national guidelines.All women diagnosed with stage I or II endometrial cancer in 2005-2009 were included in a population-based historical cohort derived from the Danish Gynaecological Cancer Database. Disease recurrence up to 3 years after the primary diagnosis was identified using national registers and hospital charts. Follow-up on survival ended on 31st December 2014. We evaluated the predictive value of clinico-pathological and sociodemographic variables using multivariate logistic regression.Recurrence within 3 years of the primary treatment was diagnosed in 183 (7%) of the included 2612 women. Site of recurrence significantly impacted on overall survival as the 5-year survival rate was 64.8% for women with vaginal recurrence and 17.5% in women with distant recurrence. Factors predictive of recurrence included the International Federation of Gynaecology and Obstetrics (FIGO) stage (OR: IB = 1.91, stage II = 3.91), Charlson comorbidity index of 3 (OR 1.86), non-endometrioid histology (OR 1.81) and being outside of the workforce (OR 1.81). Vaginal recurrence was predicted by FIGO stage only (OR: IB = 1.88, II = 2.79), while extra-vaginal recurrence was predicted by FIGO stage (OR: IB = 2.12, II = 3.31), Charlson comorbidity index of 3 (OR 1.88) and non-endometrioid histology (OR 2.51).Future research should seek to understand the underlying mechanisms of the identified predictive factors to improve recurrence prediction and to reduce morbidity and mortality.Copyright © 2016 Elsevier Ltd. All rights reserved.

Although endometrial cancer management remains challenging, a deeper understanding of the genetic diversity as well as the drivers of the various pathogenic states of this disease has led to development of divergent management approaches in an effort to improve therapeutic precision in this complex malignancy. This comprehensive review provides an update on the epidemiology, pathophysiology, diagnosis and molecular classification, recent advancements in disease management, as well as important patient quality-of-life considerations and emerging developments in the rapidly evolving therapeutic landscape of endometrial cancers.© 2021. Springer Nature Limited.

Adenocarcinoma of the endometrium (also known as endometrial cancer, or more broadly as uterine cancer or carcinoma of the uterine corpus) is the most common malignancy of the female genital tract in the United States. It is estimated that 65,950 new uterine cancer cases will have occurred in 2022, with 12,550 deaths resulting from the disease. Endometrial carcinoma includes pure endometrioid cancer and carcinomas with high-risk endometrial histology (including uterine serous carcinoma, clear cell carcinoma, carcinosarcoma [also known as malignant mixed Müllerian tumor], and undifferentiated/dedifferentiated carcinoma). Stromal or mesenchymal sarcomas are uncommon subtypes accounting for approximately 3% of all uterine cancers. This selection from the NCCN Guidelines for Uterine Neoplasms focuses on the diagnosis, staging, and management of pure endometrioid carcinoma. The complete version of the NCCN Guidelines for Uterine Neoplasms is available online at NCCN.org.

A European consensus conference on endometrial carcinoma was held in 2014 to produce multi-disciplinary evidence-based guidelines on selected questions. Given the large body of literature on the management of endometrial carcinoma published since 2014, the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy and Oncology (ESTRO), and the European Society of Pathology (ESP) jointly decided to update these evidence-based guidelines and to cover new topics in order to improve the quality of care for women with endometrial carcinoma across Europe and worldwide.© IGCS and ESGO 2021. No commercial re-use. See rights and permissions. Published by BMJ.

Predicting distant recurrence of endometrial cancer (EC) is crucial for personalized adjuvant treatment. The current gold standard of combined pathological and molecular profiling is costly, hampering implementation. Here we developed HECTOR (histopathology-based endometrial cancer tailored outcome risk), a multimodal deep learning prognostic model using hematoxylin and eosin-stained, whole-slide images and tumor stage as input, on 2,072 patients from eight EC cohorts including the PORTEC-1/-2/-3 randomized trials. HECTOR demonstrated C-indices in internal (n = 353) and two external (n = 160 and n = 151) test sets of 0.789, 0.828 and 0.815, respectively, outperforming the current gold standard, and identified patients with markedly different outcomes (10-year distant recurrence-free probabilities of 97.0%, 77.7% and 58.1% for HECTOR low-, intermediate- and high-risk groups, respectively, by Kaplan-Meier analysis). HECTOR also predicted adjuvant chemotherapy benefit better than current methods. Morphological and genomic feature extraction identified correlates of HECTOR risk groups, some with therapeutic potential. HECTOR improves on the current gold standard and may help delivery of personalized treatment in EC.© 2024. The Author(s).

Postoperative radiotherapy for International Federation of Gynaecology and Obstetrics (FIGO) stage-1 endometrial carcinoma is a subject of controversy due to the low relapse rate and the lack of data from randomised trials. We did a multicentre prospective randomised trial to find whether postoperative pelvic radiotherapy improves locoregional control and survival for patients with stage-1 endometrial carcinoma.Patients with stage-1 endometrial carcinoma (grade 1 with deep [> or =50%] myometrial invasion, grade 2 with any invasion, or grade 3 with superficial [<50%] invasion) were enrolled. After total abdominal hysterectomy and bilateral salpingo-oophorectomy, without lymphadenectomy, 715 patients from 19 radiation oncology centres were randomised to pelvic radiotherapy (46 Gy) or no further treatment. The primary study endpoints were locoregional recurrence and death, with treatment-related morbidity and survival after relapse as secondary endpoints.Analysis was done according to the intention-to-treat principle. Of the 715 patients, 714 could be evaluated. The median duration of follow-up was 52 months. 5-year actuarial locoregional recurrence rates were 4% in the radiotherapy group and 14% in the control group (p<0.001). Actuarial 5-year overall survival rates were similar in the two groups: 81% (radiotherapy) and 85% (controls), p=0.31. Endometrial-cancer-related death rates were 9% in the radiotherapy group and 6% in the control group (p=0.37). Treatment-related complications occurred in 25% of radiotherapy patients, and in 6% of the controls (p<0.0001). Two-thirds of the complications were grade 1. Grade 3-4 complications were seen in eight patients, of which seven were in the radiotherapy group (2%). 2-year survival after vaginal recurrence was 79%, in contrast to 21% after pelvic recurrence or distant metastases. Survival after relapse was significantly (p=0.02) better for patients in the control group. Multivariate analysis showed that for locoregional recurrence, radiotherapy and age below 60 years were significant favourable prognostic factors.Postoperative radiotherapy in stage-1 endometrial carcinoma reduces locoregional recurrence but has no impact on overall survival. Radiotherapy increases treatment-related morbidity. Postoperative radiotherapy is not indicated in patients with stage-1 endometrial carcinoma below 60 years and patients with grade-2 tumours with superficial invasion.

After surgery for intermediate-risk endometrial carcinoma, the vagina is the most frequent site of recurrence. This study established whether vaginal brachytherapy (VBT) is as effective as pelvic external beam radiotherapy (EBRT) in prevention of vaginal recurrence, with fewer adverse effects and improved quality of life.In this open-label, non-inferiority, randomised trial undertaken in 19 Dutch radiation oncology centres, 427 patients with stage I or IIA endometrial carcinoma with features of high-intermediate risk were randomly assigned by a computer-generated, biased coin minimisation procedure to pelvic EBRT (46 Gy in 23 fractions; n=214) or VBT (21 Gy high-dose rate in three fractions, or 30 Gy low-dose rate; n=213). All investigators were masked to the assignment of treatment group. The primary endpoint was vaginal recurrence. The predefined non-inferiority margin was an absolute difference of 6% in vaginal recurrence. Analysis was by intention to treat, with competing risk methods. The study is registered, number ISRCTN16228756.At median follow-up of 45 months (range 18-78), three vaginal recurrences had been diagnosed after VBT and four after EBRT. Estimated 5-year rates of vaginal recurrence were 1.8% (95% CI 0.6-5.9) for VBT and 1.6% (0.5-4.9) for EBRT (hazard ratio [HR] 0.78, 95% CI 0.17-3.49; p=0.74). 5-year rates of locoregional relapse (vaginal or pelvic recurrence, or both) were 5.1% (2.8-9.6) for VBT and 2.1% (0.8-5.8) for EBRT (HR 2.08, 0.71-6.09; p=0.17). 1.5% (0.5-4.5) versus 0.5% (0.1-3.4) of patients presented with isolated pelvic recurrence (HR 3.10, 0.32-29.9; p=0.30), and rates of distant metastases were similar (8.3% [5.1-13.4] vs 5.7% [3.3-9.9]; HR 1.32, 0.63-2.74; p=0.46). We recorded no differences in overall (84.8% [95% CI 79.3-90.3] vs 79.6% [71.2-88.0]; HR 1.17, 0.69-1.98; p=0.57) or disease-free survival (82.7% [76.9-88.6] vs 78.1% [69.7-86.5]; HR 1.09, 0.66-1.78; p=0.74). Rates of acute grade 1-2 gastrointestinal toxicity were significantly lower in the VBT group than in the EBRT group at completion of radiotherapy (12.6% [27/215] vs 53.8% [112/208]).VBT is effective in ensuring vaginal control, with fewer gastrointestinal toxic effects than with EBRT. VBT should be the adjuvant treatment of choice for patients with endometrial carcinoma of high-intermediate risk.Dutch Cancer Society.Copyright 2010 Elsevier Ltd. All rights reserved.

Preoperative thrombocytosis has been implicated as a negative prognostic marker for epithelial ovarian cancer (EOC). We assessed whether thrombocytosis is an independent risk factor for EOC recurrence and death.Perioperative patient characteristics and process-of-care variables (National Surgical Quality Improvement Program (NSQIP)-defined) were retrospectively abstracted from 587 women who underwent EOC staging between 1/2/03-12/29/08. Thrombocytosis was defined as platelet count > 450 × 10(9)/L. Disease-free survival (DFS) and overall survival (OS) were determined using Kaplan-Meier methods. Associations were evaluated with Cox proportional hazards regression and hazard ratios (HR).The incidence of preoperative thrombocytosis was 22.3%. DFS was 70.8% and 36.0% at 1 and 3 years. OS was 83.3% and 54.3% at 1 and 3 years. Ascites, lower hemoglobin, advanced disease, and receipt of perioperative packed red blood cell transfusion were independently associated with thrombocytosis. Older age and the presence of coronary artery disease were associated with lower likelihood of thrombocytosis. Overall, thrombocytosis was an independent predictor of increased risk of recurrence. Among early stage (I/II) cases, there was a 5-fold increase in the risk of death and nearly 8-fold risk of disease recurrence independently associated with thrombocytosis.Preoperative thrombocytosis portends worse DFS in EOC. In early stage disease, thrombocytosis is a potent predictor of worse DFS and OS and further assessment of the impact of circulating platelet-derived factors on EOC survival is warranted. Thrombocytosis is also associated with extensive initial disease burden, measurable residual disease, and postoperative sequelae. Preoperative platelet levels may have value in primary cytoreduction counseling.Copyright © 2013 Elsevier Inc. All rights reserved.

To identify preoperative platelet indexes with prognostic value and to develop and validate nomograms for predicting the survival of endometrial cancer (EC) patients.A total of 1198 women who received primary surgical treatment between January 2008 and January 2017 were included in the study. Data were randomly divided into a training set (70%, N = 840) and an external validation set (30%, n = 358). Cox regression analysis was performed in the training cohort to identify independent prognostic factors and develop nomograms for survival rate prediction.High platelet count (PLT ≥350), high mean platelet volume (MPV ≥8.8) and low platelet distribution width (PDW <12.1) were independently associated with poor RFS and OS. PLT, MPV and PDW were thus incorporated in an innovative score called the platelet index score (PIS). The PIS was also an independent indicator, which was related to histology, lymph-vascular space invasion, lymph node involvement and FIGO stage (P = 0.007, P = 0.042, P < 0.001 and P < 0.001, respectively). Furthermore, we developed and validated two nomograms based on Cox regression models. The discriminative ability and calibration of the nomograms revealed good predictive ability, as indicated by the C-indexes and calibration plots. Moreover, both the IDI and NRI were improved.Nomograms based on the PIS and clinicopathological features accurately predict recurrence-free survival and overall survival for EC patients.Copyright © 2020 Elsevier Inc. All rights reserved.

Recurrence is the main cause of death in patients with endometrial cancer (EC). This study aimed to construct and validate a nomogram to predict the recurrence-free survival of patients with EC. This was a multicenter retrospective study. A total of 812 patients from Wuhan Tongji Hospital were divided into training and validation cohorts, and 347 and 580 patients from People’s Hospital of Peking University and Qilu Hospital of Shandong, respectively, were used for validation. Univariate and multivariate Cox regression analyses were used to construct a nomogram for predicting recurrence-free survival of EC. Calibration curves, receiver operating characteristic (ROC) curves, and consistency indexes (C-indexes) were used to estimate the performance of the model. Decision curve analysis (DCA) curves were used to assess the clinical utility of the model. Age (P = 0.013), cancer antigen 125 level (P = 0.014), lymphovascular space invasion (P = 0.004), International Federation of Gynecology and Obstetrics stage (P = 0.034), and P53 (P < 0.001) were independently associated with recurrence, and we constructed a nomogram based on these variables. The C-indexes of the validation cohorts were 0.880, 0.835, and 0.875, respectively. The calibration, ROC, and DCA curves revealed that this model had excellent performance and clinical utility. Combining clinical data, clinicopathological factors, serological indicators, and immunohistochemical marks, a multicenter externally verified nomogram with robust performance was constructed to predict the recurrence of patients with EC.

The purpose of this study was to establish a predictive model for endometrial cancer (EC) recurrence based on commonly used molecular markers and clinicopathologic parameters.

The purpose of this study was to investigate the prognostic value of the inflammation-immunity-nutrition score (IINS) in patients with stage I-III endometrial cancer (EC) and establish a nomogram model to predict the recurrence of EC by combining IINS and traditional classical predictors.Seven hundred and seventy-five patients with stage I-III EC who underwent initial surgical treatment at the First Affiliated Hospital of Chongqing Medical University were included in this study as the training cohort. In the training cohort, IINS (0-3) was constructed based on preoperative C-reactive protein (CRP), lymphocytes (LYM), and albumin (ALB). Univariate and multivariate Cox regression analysis were used to screen independent predictors associated with recurrence of EC for developing the nomogram model. Internal validation of the model was performed in the training cohort by using the C-index and calibration curve, while external validation of the model was performed in another cohort (validation cohort) of 491 patients from the Second Affiliated Hospital of Chongqing Medical University.IINS was successfully constructed, and survival analysis showed that patients with high IINS had a worse prognosis. Multivariate analysis showed that IINS, age, FIGO stage, pathological type, myometrial invasion, lymphatic vessel space invasion (LVSI), Ki67 expression, estrogen receptor (ER) expression, and P53 expression were significantly associated with shorter recurrence-free survival, and then a nomogram model for predicting the recurrence of EC was successfully established. The internal and external calibration curves of the model showed that the model fit well, and the C-index (0.887 in training cohort and 0.883 in validation cohort) showed that the model proposed in this study had better prediction accuracy than other prediction models.IINS may be a strong predictor of prognosis in patients with EC. The nomogram model incorporated into the IINS can better predict the recurrence of EC than the traditional models.© 2022 Jiang et al.

The significant global burden of endometrial cancer (EC) and the challenges associated with predicting EC recurrence indicate the need for a dynamic prediction model. This study aimed to propose nomograms based on clinicopathological variables to predict recurrence-free survival (RFS) and overall survival (OS) after surgical resection for EC.

Endometrial cancer (EC) is a common gynecological malignancy that typically requires prompt surgical intervention; however, the advantage of surgical management is limited by the high postoperative recurrence rates and adverse outcomes. Previous studies have highlighted the prognostic potential of circulating tumor DNA (ctDNA) monitoring for minimal residual disease in patients with EC.To develop and validate an optimized ctDNA-based model for predicting short-term postoperative EC recurrence.We retrospectively analyzed 294 EC patients treated surgically from 2015-2019 to devise a short-term recurrence prediction model, which was validated on 143 EC patients operated between 2020 and 2021. Prognostic factors were identified using univariate Cox, Lasso, and multivariate Cox regressions. A nomogram was created to predict the 1, 1.5, and 2-year recurrence-free survival (RFS). Model performance was assessed receiver operating characteristic (ROC), calibration, and decision curve analyses (DCA), leading to a recurrence risk stratification system.Based on the regression analysis and the nomogram created, patients with postoperative ctDNA-negativity, postoperative carcinoembryonic antigen 125 (CA125) levels of < 19 U/mL, and grade G1 tumors had improved RFS after surgery. The nomogram's efficacy for recurrence prediction was confirmed through ROC analysis, calibration curves, and DCA methods, highlighting its high accuracy and clinical utility. Furthermore, using the nomogram, the patients were successfully classified into three risk subgroups.The nomogram accurately predicted RFS after EC surgery at 1, 1.5, and 2 years. This model will help clinicians personalize treatments, stratify risks, and enhance clinical outcomes for patients with EC.©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.

Predicting recurrence in low-grade, early-stage endometrial cancer (EC) is both challenging and clinically relevant. We present a weakly-supervised deep learning framework, NaroNet, that can learn, without manual expert annotation, the complex tumor-immune interrelations at three levels: local phenotypes, cellular neighborhoods, and tissue areas. It uses multiplexed immunofluorescence for the simultaneous visualization and quantification of CD68 + macrophages, CD8 + T cells, FOXP3 + regulatory T cells, PD-L1/PD-1 protein expression, and tumor cells. We used 489 tumor cores from 250 patients to train a multilevel deep-learning model to predict tumor recurrence. Using a tenfold cross-validation strategy, our model achieved an area under the curve of 0.90 with a 95% confidence interval of 0.83-0.95. Our model predictions resulted in concordance for 96,8% of cases (κ = 0.88). This method could accurately assess the risk of recurrence in EC, outperforming current prognostic factors, including molecular subtyping.© 2023. The Author(s).

Gynecologic malignancies are among the most common cancers in women worldwide and account for significant morbidity and mortality. Management and consequently overall patient survival is reliant upon early detection, accurate staging and early detection of any recurrence. Ultrasound, Computed Tomography (CT), Magnetic resonance imaging (MRI) and Positron Emission Tomography-Computed Tomography (PET-CT) play an essential role in the detection, characterization, staging and restaging of the most common gynecologic malignancies, namely the cervical, endometrial and ovarian malignancies. Recent advances in imaging including functional MRI, hybrid imaging with Positron Emission Tomography (PET/MRI) contribute even more to lesion specification and overall role of imaging in gynecologic malignancies. Radiomics is a neoteric approach which aspires to enhance decision support by extracting quantitative information from radiological imaging.

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.

To identify predictive value of apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI)-based radiomics for all recurrences in patients with endometrial carcinoma (EC).

Determination of survival time in women with endometrial cancer using clinical features remains imprecise. Features from MRI may improve the survival estimation allowing improved treatment planning.

Purpose: To predict deep myometrial infiltration (DMI), clinical risk category, histological type, and lymphovascular space invasion (LVSI) in women with endometrial cancer using machine learning classification methods based on clinical and image signatures from T2-weighted MR images. Methods: A training dataset containing 413 patients and an independent testing dataset consisting of 82 cases were employed in this retrospective study. Manual segmentation of the whole tumor volume on sagittal T2-weighted MRI was performed. Clinical and radiomic features were extracted to predict: (i) DMI of endometrial cancer patients, (ii) endometrial cancer clinical high-risk level, (iii) histological subtype of tumor, and (iv) presence of LVSI. A classification model with different automatically selected hyperparameter values was created. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, F1 score, average recall, and average precision were calculated to evaluate different models. Results: Based on the independent external testing dataset, the AUCs for DMI, high-risk endometrial cancer, endometrial histological type, and LVSI classification were 0.79, 0.82, 0.91, and 0.85, respectively. The corresponding 95% confidence intervals (CI) of the AUCs were [0.69, 0.89], [0.75, 0.91], [0.83, 0.97], and [0.77, 0.93], respectively. Conclusion: It is possible to classify endometrial cancer DMI, risk, histology type, and LVSI using different machine learning methods.

Radiomics is an emerging field of research that aims to find associations between quantitative information extracted from imaging examinations and clinical data to support the best clinical decision. In the last few years, some papers have been evaluating the role of radiomics in gynecological malignancies, mainly focusing on ovarian cancer. Nonetheless, cervical cancer is the most frequent gynecological malignancy in developing countries and endometrial cancer is the most common in western countries. The purpose of this narrative review is to give an overview of the latest published papers evaluating the role of radiomics in cervical and endometrial cancer, mostly evaluating association with tumor prognostic factors, with response to therapy and with prediction of recurrence and distant metastasis.