Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine

Chinese guidelines on the management of endometrial hyperplasia

• Endometrial hyperplasia can be classified as either hyperplasia without atypia or atypical hyperplasia. • Abnormal uterine bleeding is the most common symptom of endometrial hyperplasia. Transvaginal ultrasound is recommended for initial imaging to evaluate endometrial hyperplasia (evidence level 2+), while transrectal ultrasound is recommended for virgo patients (evidence level 3). • Endometrial biopsy should be used to confirm diagnosis in patients where endometrial lesions are suspected. Effective histological approaches to make definite diagnoses include diagnostic curettage (evidence level 2++), hysteroscopic-guided biopsy (evidence level 2+) and endometrial aspiration biopsy (evidence level 2-). • Progesterone is the preferred medication for the treatment of endometrial hyperplasia without atypia. Compared to oral progestins, placement of a levonorgestrel-releasing intrauterine system (LNG-IUS) has been associated with higher regression rates, lower recurrence rates and fewer adverse events which can be the initial treatment method. (Meta evidence level 1-, RCT evidence level 2+). Ultrasound and endometrial biopsies should be performed every 6 months during treatment to evaluate its effect and treatment should continue until no pathological changes are observed in two consecutive endometrial biopsies. Hysterectomy is not the preferred choice of treatment for patients with endometrial hyperplasia without atypia. • Minimally invasive hysterectomy is indicated for patients with endometrial atypical hyperplasia (evidence level 1+), bilateral fallopian tubes should also be removed (evidence level 2+). In cases where surgery cannot be tolerated, fertility is desired or the patient is younger than 45 years old, medical therapy is recommended (evidence level 3). LNG-IUS is the preferred medical therapy method (evidence level 2+). Endometrial pathologic evaluation should be performed every 3 months during conservative treatments, with adjustments made to dosages or approaches based on observed response to medication. Treatment should continue until no pathological changes are detected in two consecutive endometrial biopsies (evidence level 2++). There is no indication of sentinel lymph nodes biopsy and/or lymphadenectomy for hyperplasia with or without atypia. • Total hysterectomy is recommended to treat patients with recurrent endometrial atypical hyperplasia (evidence level 3); however, medical conservative therapy may be considered for patients hoping to become pregnant in the future. • Patients with fully regressed disease who would like to become pregnant should be advised to seek assistance through assisted reproductive technologies (evidence level 3). • Long-term follow-up is suggested for patients after endometrial hyperplasia treatment (evidence level 2+). Patient education is imperative for improving medication adherence, increasing regression rates and lowering recurrence rates (evidence level 3).

Proficiency-based progression training in robot-assisted laparoscopy for endometrial cancer: peri-operative and survival outcomes from an observational cohort study

Introduction

Over the last decade there has been a transition from traditional laparoscopy to robotic surgery for the treatment of endometrial cancer. A number of gynecological oncology surgical fellowship programmes have adopted robot-assisted laparoscopy, but the effect of training on complications and survival has not been evaluated. Our aim was to assess the impact of a proficiency-based progression training curriculum in robot-assisted laparoscopy on peri-operative and survival outcomes for endometrial cancer.

Methods

This is an observational cohort study performed in a tertiary referral and subspecialty training center. Women with primary endometrial cancer treated with robot-assisted laparoscopic surgery between 2015 and 2022 were included. Surgery would normally include a hysterectomy and salpingo-oophorectomy with some form of pelvic lymph node dissection (sentinel lymph nodes or lymphadenectomy). Training was provided according to a training curriculum which involves step-wise progression of the trainee based on proficiency to perform a certain surgical technique. Training cases were identified pre-operatively by consultant surgeons based on clinical factors. Case complexity matched the experience of the trainee. Main outcome measures were intra- and post-operative complications, blood transfusions, readmissions < 30 days, return to theater rates and 5-year disease-free and disease-specific survival for training versus non-training cases. Mann-Witney U, Pearson's chi-squared, multivariable regression, Kaplan-Meier and Cox proportional hazard analyses were performed to assess the effect of proficiency-based progression training on peri-operative and survival outcomes.

Results

Training cases had a lower BMI than non-training cases (30 versus 32 kg/m2, p = 0.013), but were comparable in age, performance status and comorbidities. Training had no influence on intra- and post-operative complications, blood transfusions, readmissions < 30 days, return to theater rates and median 5-year disease-free and disease-specific survival. Operating time was longer in training cases (161 versus 137 min, p = < 0.001). The range of estimated blood loss was smaller in training cases. Conversion rates, critical care unit-admissions and lymphoedema rates were comparable.

Discussion

Proficiency-based progression training can be used safely to teach robot-assisted laparoscopic surgery for women with endometrial cancer. Prospective trails are needed to further investigate the influence of distinct parts of robot-assisted laparoscopic surgery performed by a trainee on endometrial cancer outcomes.

Is it safe to operate selected low-risk endometrial cancer patients in secondary hospitals?

INTRODUCTION

The aim of this study was to assess the accuracy of a preoperative screening algorithm in identifying low-risk endometrial cancer (EC) patients to ensure optimal care.

METHODS

A total of 277 patients with primary EC confirmed through biopsy underwent magnetic resonance imaging (MRI). Patients with risk factors for advanced high-risk EC, such as non-endometrioid histology, high-grade differentiation status, deep myometrial invasion, or spread beyond the uterine corpus, were systematically excluded. The remaining preoperatively screened patients with stage IA low-grade endometrioid EC (EEC) (n = 93) underwent surgery in a tertiary hospital. The accuracy of the preoperative diagnosis was evaluated by comparing the findings with the postoperative histopathological results. Disease-free survival (DFS) and overall survival (OS) were analyzed using 8-year follow-up data.

RESULTS

Postoperative histopathological analysis revealed that all patients had grade 1-2 EEC localized to the corpus uteri. Only three patients had deep myometrial invasion (stage IB), but they remained disease-free after 6-9 years of follow-up. The median follow-up time for all patients was 8.7 years. The DFS was 7.6 years, and the OS was 8.6 years. Two patients with stage IA grade 1 EEC experienced relapse and, despite treatment, died of EC. No other EC-related deaths occurred.

CONCLUSIONS

The screening algorithm accurately identified low-risk EC patients without compromising survival. Therefore, the algorithm appears to be feasible for selecting patients for surgery in secondary hospitals.

Upregulation of ESPL1 is associated with poor prognostic outcomes in endometrial cancer

BACKGROUND

Extra spindle pole bodies-like 1 (ESPL1) is known to play a crucial role in the segregation of sister chromatids during mitosis. Overexpression of ESPL1 is considered to have oncogenic effects in various human cancers. However, the specific biological function of ESPL1 in endometrial cancer (EC) remains unclear.

METHODS

The TCGA and GEO databases were utilized to assess the expression of ESPL1 in EC. Immunohistochemistry was utilized to detect separase expression in EC samples. Kaplan-Meier survival analysis and Cox regression analysis were performed to evaluate the diagnostic and prognostic significance of ESPL1 in EC. Gene Set Enrichment Analysis (GSEA) was employed to explore the potential signaling pathway of ESPL1 in EC. Cell proliferation and colony formation ability were analyzed using CCK-8 and colony formation assay.

RESULTS

Our analysis revealed that ESPL1 is significantly upregulated in EC, and its overexpression is associated with advanced clinical characteristics and unfavourable prognostic outcomes. Suppression of ESPL1 attenuated proliferation of EC cell line.

CONCLUSION

The upregulation of ESPL1 is associated with advanced disease and poor prognosis in EC patients. These findings suggest that ESPL1 has the potential to serve as a diagnostic and prognostic biomarker in EC, highlighting its significance in the management of EC patients.

The Analysis of in vitro Fertilization Outcomes after Fertility-Preserving Therapy for Endometrial Hyperplasia or Carcinoma

OBJECTIVES

This study aimed to evaluate the clinical efficacy of fertility-preserving therapy through in vitro fertilization (IVF) procedures in women who were pathologically diagnosed with endometrial hyperplasia or carcinoma.

DESIGN

A retrospective cohort study on fertility-preserving therapy was conducted. Participants/Materials, Setting: A total of 82 women were enrolled who had simple endometrial hyperplasia (SH), complex hyperplasia (CH), complex atypical hyperplasia (CAH), and endometrioid endometrial carcinoma stage IA (EC IA) and underwent IVF at Gangnam CHA fertility center between January 2008 and December 2020.

METHODS

The primary endpoints were oncologic outcomes and subsequent reproductive outcomes of patients who underwent fertility-preserving treatments analyzed by χ2 test or Fisher's exact test.

RESULTS

Of the 82 patients, 33 had a cumulative clinical pregnancy (40.2%), and 25 had a cumulative live birth (30.5%) through IVF procedures following pathologic confirmation of complete remission or non-progressive status. The cumulative clinical pregnancy rates and live birth rates for SH were 50.0% and 30.0%, for CH were 37.8% and 28.9%, for CAH were 25.0% and 25.0%, and for EC were 38.5% and 38.5%, respectively. There were no significant differences in cumulative clinical pregnancy rates or live birth rates when comparing the four groups. There was a difference in endometrial thickness between medroxyprogesterone acetate (MPA) treatment group and intrauterine device (IUD) group (p = 0.036); however, there were no significant differences in clinical pregnancy rates among MPA, IUD, and MPA+IUD groups.

LIMITATIONS

Because of the retrospective nature of the study, many factors relevant to the treatment decision were not strictly controlled.

CONCLUSIONS

All endometrial hyperplasia and carcinoma groups had competent cumulative live birth rates by IVF procedures. There may be differences in endometrial thickness depending on the treatment methods, but this does not affect clinical pregnancy rates. Therefore, the fertility-preserving treatment for endometrial hyperplasia and carcinoma is a safe and feasible method that results in good IVF outcomes.

FIGO 2023 endometrial staging: a leap of faith into the new "prognostic based' rather than "anatomical based" staging-too fast too furious??

BACKGROUND

In 2023 FIGO revised the endometrial cancer staging system after 13 years. There is a lacuna of data regarding the performance and practicality of the revised 2023 FIGO staging schema for endometrial cancer from Low Middle-Income Countries (LMIC).

OBJECTIVE

To estimate the shift of stage and adjuvant management of endometrial cancer based on the FIGO 2023 system compared to the FIGO 2009 system and assess the predictive potential of the FIGO 2023 system.

MATERIAL AND METHODS

A retrospective study was conducted from 1st January 2017 to 31st December 2022. All patients with endometrial cancer were staged according to the FIGO 2023 and FIGO 2009 staging system. Follow-up of patients was done to determine recurrence.

RESULTS

A total of 152 patients were included. Aggressive histology was seen in 66 (45%) patients. Eighteen (11%) had subserosal involvement. Substantial LVSI was noted in 23 (15%) of patients. Twenty-four (47%) patients of FIGO 2009 Stage IA and 26 patients (63%) of FIGO 2009 Stage IB were upstaged. Eleven (50%) patients of FIGO 2009 Stage IIIA were down staged to IA3. Overall 23 patients (15%) had a shift of stage. Fifteen out of 152 patients (15%) would have had a possible risk stratification change which would imply 23 patients (15%) would have needed a more radical treatment. Molecular classification was done in 32 patients; however, only 2 patients could afford POLE testing. Kaplan-Meier curves showed significant PFS differences in FIGO 2009 Stage IB and Stage IIIA when restaged according to the FIGO 2023 system.

CONCLUSION

The FIGO 2023 endometrial staging is a more robust prognosticator; however, the practicality of molecular classification in LMICs is still a distant dream.

Validating the 2023 FIGO staging system: A nomogram for endometrioid endometrial cancer and adenocarcinoma

BACKGROUND

To find the factors impacting overall survival (OS) prognosis in patients with endometrioid endometrial carcinoma (EEC) and adenocarcinoma and to establish a nomogram model to validate the 2023 International Federation of Obstetrics and Gynecology (FIGO) staging system for endometrial cancer.

METHODS

Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) training cohort. An independent validation cohort was obtained from the First Affiliated Hospital of Anhui Medical University between 2008 and 2023. Cox regression analysis identified independent prognostic factors for OS in EEC and adenocarcinoma patients. A nomogram predicting OS was developed and validated utilizing the C-index, calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). The relationship between the tumor grade and prognosis of EEC and adenocarcinoma was quantified using net reclassification improvement (NRI), propensity score matching (PSM), and Kaplan-Meier curves.

RESULTS

Cox regression analysis identified age, race, marital status, tumor grade, tumor stage, tumor size, and chemotherapy as independent prognostic factors for OS. A nomogram for predicting OS was developed based on these factors. The C-indexes for the OS nomogram was 0.743 and 0.720 for the SEER training set and external validation set, respectively. The area under the ROC (AUC) for the OS nomogram was 0.755, 0.757, and 0.741 for the SEER data subsets and 0.844, 0.719, and 0.743 for the external validation subsets. Calibration plots showed high concordance between the nomogram-predicted and observed OS. DCA also demonstrated the clinical utility of the OS nomogram. NRI, PSM, and survival analyses revealed that tumor grade was the most important histopathological factor for EEC and adenocarcinoma prognosis.

CONCLUSION

Seven independent prognostic variables for the OS of patients with EEC and adenocarcinoma were identified. The established OS nomogram has good predictive ability and clinical utility and validates the 2023 endometrial cancer FIGO staging system.

Impact of adjuvant treatment on survival in patients with 2023 FIGO stage IIC endometrial cancer: a retrospective analysis from two tertiary centers in Korea and Taiwan

OBJECTIVE

In early-stage endometrial cancer, aggressive histologic types (grade 3 endometrioid, serous, clear cell, carcinosarcomas, undifferentiated, mixed, and other unusual types) are associated with an increased risk of distant metastases and worse survival. However, the optimal adjuvant treatment for these patients remains controversial. The present study investigated the outcomes of different adjuvant treatments in patients with 2023 FIGO stage IIC endometrial cancer.

METHODS

We retrospectively identified patients with 2023 FIGO stage IIC endometrial cancer who underwent surgery followed by either adjuvant treatment or observation from 2000 to 2020 at two tertiary centers in Korea and Taiwan. Recurrence-free survival (RFS) and overall survival (OS) were evaluated using Kaplan-Meier estimates and Cox proportional-hazards models. We also analyzed recurrence patterns after different adjuvant treatments.

RESULTS

A total of 272 patients were identified; 204 received adjuvant treatment postoperatively, whereas 68 only underwent observation. Adjuvant treatment was not associated with improved RFS or OS. Non-endometrioid histologic types (p=0.003) and presence of lymphovascular space invasion (LVSI, p=0.002) were associated with worse RFS, whereas only non-endometrioid histologic types impacted OS (p=0.004). In subgroup analyses, adjuvant treatment improved OS in patients with LVSI (p=0.020) and in patients with both LVSI and grade 3 endometrioid histologic type (p=0.007). We found no difference in locoregional and distant recurrence between patients undergoing adjuvant treatment or observation.

CONCLUSION

In this study, the addition of adjuvant treatment was associated with an OS benefit for patients with LVSI, especially those with grade 3 endometrioid tumors.

Cost-effectiveness of pembrolizumab plus chemotherapy for advanced endometrial cancer

OBJECTIVE

To assess the cost-effectiveness of pembrolizumab in combination with chemotherapy compared to chemotherapy alone, based on the results of the NRG-GY018 trial, in patients with advanced or recurrent endometrial cancer (EC), stratified by mismatch repair-deficient (dMMR) and mismatch repair-proficient (pMMR) subgroups.

METHODS

A Markov model was used to simulate patients receiving either pembrolizumab plus chemotherapy or chemotherapy alone. Lifetime costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) were calculated using a willingness-to-pay (WTP) threshold of $150,000/QALY. Univariate and probabilistic sensitivity analyses were conducted to assess the robustness of our findings.

RESULTS

The addition of pembrolizumab to chemotherapy led to an incremental gain of 4.05 QALYs at an additional cost of $167,224, resulting in an ICER of $41,305.09/QALY compared to chemotherapy alone in dMMR EC. Additionally, there were 0.93 additional QALYs at an additional cost of $83,661, which resulted in an ICER of $90,284.80/QALY in pMMR EC. Sensitivity analyses indicated that the cost of pembrolizumab, utility of progressed disease, and utility of progression-free survival had the greatest impact on the results. Probabilistic sensitivity analysis showed that pembrolizumab was considered cost-effective at a 100% probability at a WTP threshold of $150,000 per QALY.

CONCLUSION

Pembrolizumab, when combined with chemotherapy, was found to be cost-effective compared to chemotherapy alone both for patients with advanced or recurrent dMMR and pMMR EC from the perspective of a payer in the United States.

Comparison of two 3D reconstruction models for understanding of complicated female pelvic tumors

OBJECTIVE

Three-dimensional (3D) reconstructed models have been shown to improve visualization in complex female pelvic tumors. Cinematic rendering (CR) is a 3D imaging technique for computed tomography (CT) images, which creates more realistic images with the ability to enhance imaging of anatomical features for diagnosis. This study was set up to compare two types of 3D models and to validate the use of 3D anatomical techniques for the diagnosis of complex female pelvic tumors.

METHODS

The preclinical, randomized, two-sequence crossover investigation was performed from December 2022 to January 2023 at First Affiliated Hospital of Chongqing Medical University. Sixteen residents and 10 attending surgeons assessed the cases of 23 patients with two types of 3D model images. The surgeons were randomly assigned to two assessment sequences (CR-3D model group and CT-3D model group). For each case, participants selected one question that probed fundamental questions about the tumor's genesis throughout each assessment period. Following a 4-week washout period, case assessments were transferred to the other image modality.

RESULTS

The main result assessment was the accuracy of the answers. The time to answer the questions and the case assessment questionnaire was added as a secondary outcome. The mean scores in the CR-3D models (19.35 ± 1.87) varied significantly from those in the CT-CR group (16.77 ± 1.8) (P < 0.001), and solving the questions in the CT-3D model sequence (41.96 ± 6.31 s) varied significantly from that in the CR-3D model sequence (52.88 ± 5.95 s) (P < 0.001). Subgroup analysis revealed that there were statistically significant variations in the scores of female reproductive tumors, pelvic tumors other than the reproductive system, and retroperitoneal tumors (P = 0.005). Analysis of the assessment questionnaire showed that more surgeons choose CR 3D reconstruction (8.31 ± 0.76 vs 7.15 ± 1.19, P < 0.001).

CONCLUSIONS

The results suggest that each 3D reconstruction method has its own advantages. Surgeons feel that CR reconstruction models are a useful technique that can improve their comprehension of complex pelvic tumors, while traditional 3D models have an advantage in terms of speed to diagnosis.

Predictive Value of Magnetic Resonance Imaging in Risk Stratification and Molecular Classification of Endometrial Cancer

This study evaluated the magnetic resonance imaging (MRI) findings of endometrial cancer (EC) patients and identified differences based on risk group and molecular classification. The study involved a total of 175 EC patients. The MRI data were retrospectively reviewed and compared based on the risk of recurrence. Additionally, the associations between imaging phenotypes and genomic signatures were assessed. The low-risk and non-low-risk groups (intermediate, high-intermediate, high, metastatic) showed significant differences in tumor diameter (p < 0.001), signal intensity and heterogeneity on diffusion-weighted imaging (DWI) (p = 0.003), deep myometrial invasion (involvement of more than 50% of the myometrium), cervical invasion (p < 0.001), extrauterine extension (p = 0.002), and lymphadenopathy (p = 0.003). Greater diffusion restriction and more heterogeneity on DWI were exhibited in the non-low-risk group than in the low-risk group. Deep myometrial invasion, cervical invasion, extrauterine extension, lymphadenopathy, recurrence, and stage discrepancy were more common in the non-low-risk group (p < 0.001). A significant difference in microsatellite stability status was observed in the heterogeneity of the contrast-enhanced T1-weighted images (p = 0.027). However, no significant differences were found in MRI parameters related to TP53 mutation. MRI features can be valuable predictors for differentiating risk groups in patients with EC. However, further investigations are needed to explore the imaging markers based on molecular classification.

Tumor polo-like kinase 4 protein expression reflects lymphovascular invasion, higher Federation of Gynecology and Obstetrics stage, and shortened survival in endometrial cancer patients who undergo surgical resection

BACKGROUND

Polo-like kinase 4 (PLK4) serves as a marker for tumor features and poor outcomes in cancers. This study aimed to explore the associations of tumor PLK4 protein expression with tumor characteristics and survival in endometrial cancer (EC) patients who underwent surgical resection.

METHODS

This study included 142 EC patients who underwent surgical resection. Tumor tissue samples were obtained for tumor PLK4 protein expression detection via immunohistochemistry (IHC).

RESULTS

Among EC patients, 26.1% had a PLK4 IHC score of 0, 24.6% had a score of 1-3, 27.5% had a score of 4-6, and 21.8% had a score of 7-12. Tumor PLK4 protein expression positively associated with lymphovascular invasion (P = 0.008) and Federation of Gynecology and Obstetrics (FIGO) stage (P = 0.005). Disease-free survival (DFS) was not different between patients with tumor PLK4 IHC scores > 0 and ≤ 0 (P = 0.154) but was reduced in patients with scores > 3 vs. ≤ 3 (P = 0.009) and > 6 vs. ≤ 6 (P < 0.001). Similarly, overall survival (OS) was not different between patients with scores > 0 and ≤ 0 (P = 0.322) but was shorter in patients with scores > 3 vs. ≤ 3 (P = 0.011) and > 6 vs. ≤ 6 (P = 0.006). After adjustment, a tumor PLK4 IHC score > 6 (vs. ≤ 6) (hazard ratio (HR): 3.156, P = 0.008) or > 3 (vs. ≤ 3) (HR: 3.918, P = 0.026) was independently associated with shortened DFS and OS.

CONCLUSION

A tumor PLK4 IHC score > 6 or > 3 associates with shortened DFS and OS in EC patients who undergo surgical resection.

SIM2: Its Prognostic Significance and Oncogenic Role in Endometrial Carcinoma

Background

Endometrial carcinoma ranks as the second most widespread malignancy affecting the reproductive system in females. Effective prognostic biomarkers are required to further improve survival rates for patients. Single-minded homolog 2 (SIM2) is known to participate in neurogenesis as a transcription factor. However, the potential role of SIM2 in endometrial carcinoma remains elusive.

Methods

Multiple public databases, including TIMER2.0, GEIPA2, UALCAN, LinkedOmics, BioGRID, DAVID and cBioPortal, were used to investigate SIM2 mRNA expression, SIM2-associated genes, PPI network, functional enrichment analysis, SIM2 gene alterations and methylation. The association between SIM2 expression and immune cell infiltrates was explored using GSVA. The effects of gene alterations and methylation on patient survival and CD8+T infiltration were examined using GSCA. Moreover, the prognostic potential of SIM2 was evaluated using COX regression, ROC curves and a nomogram model. Finally, the differential expression and function of SIM2 in UCEC were explored using qPCR, WB, CCK8 and Transwell assays.

Results

Our findings revealed the heightened expression of SIM2 in endometrial carcinoma, and that its DNA methylation and CNV alterations were correlated with immune infiltration and patients' prognosis. Additionally, functional enrichment revealed the involvement of SIM2 in transcription regulation and signal transduction. Moreover, we performed cell-based experiments to corroborate the oncogenic function of SIM2 in facilitating cell proliferation, migration and invasion.

Conclusion

Collectively, these results suggest that SIM2 holds promise as both a potential prognostic indicator and a viable treatment target for endometrial carcinoma.

Predictive models for lymph node metastasis in endometrial cancer: A systematic review and bibliometric analysis

BACKGROUND

Lymph node metastasis is associated with a poorer prognosis in endometrial cancer.

OBJECTIVE

The objective was to synthesize and critically appraise existing predictive models for lymph node metastasis risk stratification in endometrial cancer.

DESIGN

This study is a systematic review.

DATA SOURCES AND METHODS

We searched the Web of Science for articles reporting models predicting lymph node metastasis in endometrial cancer, with a systematic review and bibliometric analysis conducted based upon which. Risk of bias was assessed by the Prediction model Risk Of BiAS assessment Tool (PROBAST).

RESULTS

A total of 64 articles were included in the systematic review, published between 2010 and 2023. The most common articles were "development only." Traditional clinicopathological parameters remained the mainstream in models, for example, serum tumor marker, myometrial invasion and tumor grade. Also, models based upon gene-signatures, radiomics and digital histopathological images exhibited an acceptable self-reported performance. The most frequently validated models were the Mayo criteria, which reached a negative predictive value of 97.1%-98.2%. Substantial variability and inconsistency were observed through PROBAST, indicating significant between-study heterogeneity. A further bibliometric analysis revealed a relatively weak link between authors and organizations on models predicting lymph node metastasis in endometrial cancer.

CONCLUSION

A number of predictive models for lymph node metastasis in endometrial cancer have been developed. Although some exhibited promising performance as they demonstrated adequate to good discrimination, few models can currently be recommended for clinical practice due to lack of independent validation, high risk of bias and low consistency in measured predictors. Collaborations between authors, organizations and countries were weak. Model updating, external validation and collaborative research are urgently needed.

REGISTRATION

None.

Multi-parametric MRI-based radiomics for preoperative prediction of multiple biological characteristics in endometrial cancer

Purpose

To develop and validate multi-parametric MRI (MP-MRI)-based radiomics models for the prediction of biological characteristics in endometrial cancer (EC).

Methods

A total of 292 patients with EC were divided into LVSI (n = 208), DMI (n = 292), MSI (n = 95), and Her-2 (n = 198) subsets. Total 2316 radiomics features were extracted from MP-MRI (T2WI, DWI, and ADC) images, and clinical factors (age, FIGO stage, differentiation degree, pathological type, menopausal state, and irregular vaginal bleeding) were included. Intra-class correlation coefficient (ICC), spearman's rank correlation test, univariate logistic regression, and least absolute shrinkage and selection operator (LASSO) were used to select radiomics features; univariate and multivariate logistic regression were used to identify clinical independent risk factors. Five classifiers were applied (logistic regression, random forest, decision tree, K-nearest neighbor, and Bayes) to construct radiomics models for predicting biological characteristics. The clinical model was built based on the clinical independent risk factors. The combined model incorporating the radiomics score (radscore) and the clinical independent risk factors was constructed. The model was evaluated by ROC curve, calibration curve (H-L test), and decision curve analysis (DCA).

Results

In the training cohort, the RF radiomics model performed best among the five classifiers for the three subsets (MSI, LVSI, and DMI) according to AUC values (AUCMSI: 0.844; AUCLVSI: 0.952; AUCDMI: 0.840) except for Her-2 subset (Decision tree: AUC=0.714), and the combined model had higher AUC than the clinical model in each subset (MSI: AUCcombined =0.907, AUCclinical =0.755; LVSI: AUCcombined =0.959, AUCclinical =0.835; DMI: AUCcombined = 0.883, AUCclinical =0.796; Her-2: AUCcombined =0.812, AUCclinical =0.717; all P<0.05). Nevertheless, in the validation cohort, significant differences between the two models (combined vs. clinical model) were found only in the DMI and LVSI subsets (DMI: AUCcombined =0.803, AUCclinical =0.698; LVSI: AUCcombined =0.926, AUCclinical =0.796; all P<0.05).

Conclusion

The radiomics analysis based on MP-MRI and clinical independent risk factors can potentially predict multiple biological features of EC, including DMI, LVSI, MSI, and Her-2, and provide valuable guidance for clinical decision-making.

KLF2 transcription suppresses endometrial cancer cell proliferation, invasion, and migration through the inhibition of NPM1

Endometrial cancer (EC) is the most common gynaecologic malignancy. This study was to explore the role of kruppel-like factor 2 (KLF2) in EC cell behaviours. The expression of KLF2 in EC and its correlation with NPM1 were first predicted on the database. Levels of KLF2 and nucleophosmin 1 (NPM1) in EC cell lines were then determined. After transfection of the overexpression vector of KLF2 or NPM1, cell proliferation, invasion, and migration were evaluated. The binding relationship between KLF2 and the NPM1 promoter was analysed. KLF2 was downregulated while NPM1 was upregulated in EC cells. KLF2 overexpression reduced the proliferation potential of EC cells and the number of invaded and migrated cells. KLF2 was enriched in the NPM1 promoter and inhibited NPM1 transcriptional level. NPM1 overexpression neutralised the effects of KLF2 overexpression on suppressing EC cell growth. Collectively, KLF2 was decreased in EC cells and KLF2 overexpression increased the binding to the NPM1 promoter to inhibit NPM1 transcription, thus suppressing EC cell growth.

Molecular-based classification of endometrial carcinoma in Northern Thailand: impact on prognosis and potential for implementation in resource-limited settings

BACKGROUND

Endometrial carcinoma is molecularly categorized into four subgroups: polymerase-E exonuclease domain-mutant (POLE-mut), mismatch repair-deficient (MMR-d), p53-abnormal (p53-abn), and no specific molecular profile (NSMP). This classification scheme has been included into clinical recommendation for post-operative risk-based management, although there have been few Asian studies on this topic. The present study aimed to evaluate the prevalence and clinical outcomes of endometrial carcinoma using this classification in Northern Thailand and the feasibility of implementation in resource-limited settings.

METHODS

Endometrial carcinomas from hysterectomy specimens were classified using immunohistochemistry for MMR proteins and p53, as well as POLE mutation testing. Clinicopathological variables and outcomes were analyzed. The costs of the molecular information-based approach were compared to those incurred by the conventional approach (without molecular classification).

RESULTS

Of 138 patients, 52.9% in the NSMP subgroup, 28.2% were in the MMR-d, 13.8% in the p53-abn, and 5.1% in the POLE-mut. After adjusting for other variables, patients with POLE-mut showed the most favorable outcomes, while those with p53-abn had the poorest survival. When estimating the costs for post-operative management, the use of molecular classification resulted in a 10% increase over the conventional approach. However, the cost increased only by 1% if only POLE testing was used to identify patients for treatment omission.

CONCLUSION

In Northern Thailand, endometrial carcinoma had comparable subgroup distribution and prognostic implications to previous reports, supporting the implementation of management guidelines that incorporate molecular information. In resource-limited settings, at least POLE mutation testing in early-stage patients should be considered.

Comparison of progression-free survival outcome of sentinel node biopsy without ultrastaging versus lymphadenectomy in endometrial cancer: a propensity-matched analysis

OBJECTIVE

We aimed to investigate the oncologic outcomes of patients with endometrial cancer who underwent sentinel lymph node (SLN) biopsy without ultrastaging compared with that of those who underwent lymphadenectomy (LND).

METHODS

Patients with endometrial cancer who underwent staging with SLN biopsy or LND during 2006 - 2021 were analyzed using propensity score matching (PSM). SLN metastasis was examined using hematoxylin and eosin staining, without ultrastaging. Progression-free survival (PFS) was compared between the two groups before and after PSM using age, histology, and stage as covariates. Clinical variables such as recurrence patterns and lymphatic complications, were assessed.

RESULTS

After excluding 213 patients who underwent validation LND with SLN biopsy, 902 were identified. The demographics of the remaining patients differed according to histology, myometrial invasion depth, and stage. Lymph node metastasis was less frequent in the SLN group than in the LND group (9.4% vs. 3.8%, p=0.004). The recurrence rates within 2 years were lower in the SLN group. The SLN group exhibited significantly superior 2-year and overall PFS than the LND group. Among patients with uterus-confined disease, overall PFS was favorable for SLN biopsy. After matching, differences in PFS were no longer observed, although the lymphocele and lymphedema rates were significantly lower in the SLN group.

CONCLUSION

In patients with endometrial cancer, SLN biopsy without ultrastaging did not compromise survival outcomes and was associated with significantly reduced lymphatic complication rates compared with LND. Therefore, SLN biopsy can be recommended for patients with endometrial cancer without definitive preoperative evidence of distant metastasis.

Development and validation of a prognostic model based on metabolic risk score to predict overall survival of endometrial cancer in Chinese patients

OBJECTIVE

Metabolic syndrome (MetS) is closely related to the increased risk and poor prognosis of endometrial cancer (EC). The purpose of this study was to analyze the relationship between metabolic risk score (MRS) and EC, and establish a predictive model to predict the prognosis of EC.

METHODS

A retrospective study was designed of 834 patients admitted between January 2004 to December 2019. Univariate and multivariate Cox analysis were performed to screen independent prognostic factors for overall survival (OS). A predictive nomogram is built based on independent risk factors for OS. Consistency index (C-index), calibration plots and receiver operating characteristic curve were used to evaluate the predictive accuracy of the nomogram.

RESULTS

The patients were randomly divided into training cohort (n=556) and validation cohort (n=278). The MRS of EC patients, ranging from -8 to 15, was calculated. Univariate and multivariate Cox analysis indicated that age, MRS, FIGO stage, and tumor grade were independent risk factors for OS (p<0.05). The Kaplan-Meier analysis demonstrated that EC patients with low score showed a better prognosis in OS. Then, a nomogram was established and validated based on the above four variables. The C-index of nomogram were 0.819 and 0.829 in the training and validation cohorts, respectively. Patients with high-risk score had a worse OS according to the nomogram.

CONCLUSION

We constructed and validated a prognostic model based on MRS and clinical prognostic factors to predict the OS of EC patients accurately, which may help clinicians personalize prognostic assessments and effective clinical decisions.

Signatures of necroptosis-related genes as diagnostic markers of endometriosis and their correlation with immune infiltration

BACKGROUND

Endometriosis (EMS) occurs when normal uterine tissue grows outside the uterus and causes chronic pelvic pain and infertility. Endometriosis-associated infertility is thought to be caused by unknown mechanisms. In this study, using necroptosis-related genes, we developed and validated multigene joint signatures to diagnose EMS and explored their biological roles.

METHODS

We downloaded two databases (GSE7305 and GSE1169) from the Gene Expression Omnibus (GEO) database and 630 necroptosis-related genes from the GeneCards and GSEA databases. The limma package in Rsoftware was used to identify differentially expressed genes (DEGs). We interleaved common differentially expressed genes (co-DEGs) and necroptosis-related genes (NRDEGs) in the endometriosis dataset. The DEGs functions were reflected by gene ontology analysis (GO), pathway enrichment analysis, and gene set enrichment analysis (GSEA). We used CIBERSORT to analyze the immune microenvironment differences between EMS patients and controls. Furthermore, a correlation was found between necroptosis-related differentially expressed genes and infiltrating immune cells to better understand the molecular immune mechanism.

RESULTS

Compared with the control group, this study revealed that 10 NRDEGs were identified in EMS. There were two types of immune cell infiltration abundance (activated NK cells and M2 macrophages) in these two datasets, and the correlation between different groups of samples was statistically significant (P < 0.05). MYO6 consistently correlated with activated NK cells in the two datasets. HOOK1 consistently demonstrated a high correlation with M2 Macrophages in two datasets. The immunohistochemical result indicated that the protein levels of MYO6 and HOOK1 were increased in patients with endometriosis, further suggesting that MYO6 and HOOK1 can be used as potential biomarkers for endometriosis.

CONCLUSIONS

We identified ten necroptosis-related genes in EMS and assessed their relationship with the immune microenvironment. MYO6 and HOOK1 may serve as novel biomarkers and treatment targets in the future.

Using Radiomics and Machine Learning Applied to MRI to Predict Response to Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer

Neoadjuvant chemotherapy plus radical surgery could be a safe alternative to chemo-radiation in cervical cancer patients who are not willing to receive radiotherapy. The response to neoadjuvant chemotherapy is the main factor influencing the need for adjunctive treatments and survival. In the present paper we aim to develop a machine learning model based on cervix magnetic resonance imaging (MRI) images to stratify the single-subject risk of cervical cancer. We collected MRI images from 72 subjects. Among these subjects, 28 patients (38.9%) belonged to the "Not completely responding" class and 44 patients (61.1%) belonged to the 'Completely responding' class according to their response to treatment. This image set was used for the training and cross-validation of different machine learning models. A robust radiomic approach was applied, under the hypothesis that the radiomic features could be able to capture the disease heterogeneity among the two groups. Three models consisting of three ensembles of machine learning classifiers (random forests, support vector machines, and k-nearest neighbor classifiers) were developed for the binary classification task of interest ("Not completely responding" vs. "Completely responding"), based on supervised learning, using response to treatment as the reference standard. The best model showed an ROC-AUC (%) of 83 (majority vote), 82.3 (mean) [79.9-84.6], an accuracy (%) of 74, 74.1 [72.1-76.1], a sensitivity (%) of 71, 73.8 [68.7-78.9], and a specificity (%) of 75, 74.2 [71-77.5]. In conclusion, our preliminary data support the adoption of a radiomic-based approach to predict the response to neoadjuvant chemotherapy.

Radiomics optimizing the evaluation of endometrial receptivity for women with unexplained recurrent pregnancy loss

Background

The optimization of endometrial receptivity (ER) through individualized therapies has been shown to enhance the likelihood of successful gestation. However, current practice lacks comprehensive methods for evaluating the ER of patients with recurrent pregnancy loss (RPL). Radiomics, an emerging AI-based technique that enables the extraction of mineable information from medical images, holds potential to offer a more objective and quantitative approach to ER assessment. This innovative tool may facilitate a deeper understanding of the endometrial environment and enable clinicians to optimize ER evaluation in RPL patients.

Objective

This study aimed to identify ultrasound radiomics features associated with ER, with the purpose of predicting successful ongoing pregnancies in RPL patients, and to assess the predictive accuracy of these features against regular ER parameters.

Methods

This retrospective, controlled study involved 262 patients with unexplained RPL and 273 controls with a history of uncomplicated full-term pregnancies. Radiomics features were extracted from ultrasound endometrial segmentation images to derive a radiomics score (rad-score) for each participant. Associations between rad-scores, baseline clinical variables, and sonographic data were evaluated using univariate and multivariate logistic regression analyses to identify potential indicators of RPL. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive accuracy of the rad-score and other identified indicators in discriminating RPL cases. Furthermore, the relationships between age and these identified indicators were assessed via Pearson correlation analysis.

Results

From the 1312 extracted radiomics features, five non-zero coefficient radiomics signatures were identified as significantly associated with RPL, forming the basis of the rad-score. Following multivariate logistic regression analysis, age, spiral artery pulsatility index (SA-PI), vascularisation index (VI), and rad-score emerged as independent correlates of RPL (all P<0.05). ROC curve analyses revealed the superior discriminative capability of the rad-score (AUC=0.882) over age (AUC=0.778), SA-PI (AUC=0.771), and VI (AUC=0.595). There were notable correlations between age and rad-score (r=0.275), VI (r=-0.224), and SA-PI (r=0.211), indicating age-related variations in RPL predictors.

Conclusion

This study revealed a significant association between unexplained RPL and elevated endometrial rad-scores during the WOI. Furthermore, it demonstrated the potential of rad-scores as a promising predictive tool for successful ongoing pregnancies in RPL patients.

TMEM41A overexpression correlates with poor prognosis and immune alterations in patients with endometrial carcinoma

BACKGROUND

Expression levels of transmembrane protein 41A (TMEM41A) are related to the progression of malignant tumors. However, the association between TMEM41A expression and endometrial carcinoma (EC) remains unclear. This study aims to identify the roles of TMEM41A expression in the prognosis of patients with EC and its correlation with EC progression.

METHODS

The TMEM41A expression and its correlation with the survival of patients with EC were assessed. Cox regression analysis was used to identify the prognostic factors, while nomograms were used to examine the association between the prognostic factors and the survival of patients with EC. Finally, the link between TMEM41A level and immune microenvironment and RNA modifications was investigated in EC.

RESULTS

TMEM41A was overexpressed in EC. TMEM41A overexpression could diagnose the EC and evaluate the poor prognosis of patients. Overexpression of TMEM41A was associated with clinical stage, age, weight, histological subtype, tumor grade, and survival status of patients with EC. Clinical stage, age, tumor grade, radiotherapy, and TMEM41A overexpression were factors of poor prognosis in patients with EC. The nomograms revealed the correlation between the TMEM41A level and survival time of patients with EC at 1, 3, and 5 years. Furthermore, TMEM41A overexpression was significantly correlated with the level of the stromal score, immune score, estimate score, NK CD56 bright cells, iDC, NK cells, eosinophils, pDC, T cells, TReg, cytotoxic cells, mast cells, Th17 cells, neutrophils, aDC, NK CD56 dim cells, TFH, Th2 cells, CD8 T cells, macrophages, immune cell markers, and RNA modifications.

CONCLUSIONS

TMEM41A is overexpressed in EC tissues and is associated with the prognosis, immune microenvironment, and RNA modification. Our preliminary studies indicate that overexpression of TMEM41A can potentially serve as a biomarker for EC treatment.

Deep Learning for Medical Image-Based Cancer Diagnosis

(1) Background: The application of deep learning technology to realize cancer diagnosis based on medical images is one of the research hotspots in the field of artificial intelligence and computer vision. Due to the rapid development of deep learning methods, cancer diagnosis requires very high accuracy and timeliness as well as the inherent particularity and complexity of medical imaging. A comprehensive review of relevant studies is necessary to help readers better understand the current research status and ideas. (2) Methods: Five radiological images, including X-ray, ultrasound (US), computed tomography (CT), magnetic resonance imaging (MRI), positron emission computed tomography (PET), and histopathological images, are reviewed in this paper. The basic architecture of deep learning and classical pretrained models are comprehensively reviewed. In particular, advanced neural networks emerging in recent years, including transfer learning, ensemble learning (EL), graph neural network, and vision transformer (ViT), are introduced. Five overfitting prevention methods are summarized: batch normalization, dropout, weight initialization, and data augmentation. The application of deep learning technology in medical image-based cancer analysis is sorted out. (3) Results: Deep learning has achieved great success in medical image-based cancer diagnosis, showing good results in image classification, image reconstruction, image detection, image segmentation, image registration, and image synthesis. However, the lack of high-quality labeled datasets limits the role of deep learning and faces challenges in rare cancer diagnosis, multi-modal image fusion, model explainability, and generalization. (4) Conclusions: There is a need for more public standard databases for cancer. The pre-training model based on deep neural networks has the potential to be improved, and special attention should be paid to the research of multimodal data fusion and supervised paradigm. Technologies such as ViT, ensemble learning, and few-shot learning will bring surprises to cancer diagnosis based on medical images.

Clear cell endometrial carcinoma with high microsatellite instability in a complicated pregnancy: a case report

BACKGROUND

Endometrial carcinomas are the most common female genital malignancies. They are very rare in pregnancy and worldwide less than 60 cases associated with pregnancy are published. No clear cell carcinoma has been described in a pregnancy with a live birth.

CASE PRESENTATION

We present the course of a 43-year-old Uyghur female patient with the diagnosis of endometrial carcinoma with a deficiency in the DNA mismatch repair system in the pregnancy. The malignancy with clear cell histology was confirmed by biopsy following the delivery via caesarean section due to preterm birth of a fetus with sonographically suspected tetralogy of Fallot. Earlier whole exome sequencing after amniocentesis had shown a heterozygous mutation in the MSH2 gene, which was unlikely to be related to the fetal cardiac defect. The uterine mass was initially deemed an isthmocervical fibroid by ultrasound and was confirmed as stage II endometrial carcinoma. The patient was consequently treated with surgery, radiotherapy and chemotherapy. Six months after the adjuvant therapy, re-laparotomy was performed due to ileus symptoms and an ileum metastasis was found. The patient is currently undergoing immune checkpoint inhibitor therapy with pembrolizumab.

CONCLUSION

Rare endometrial carcinoma should be included in the differential diagnosis of uterine masses in pregnant women with risk factors.

The survival impact of adjuvant radiotherapy and chemotherapy in patients with non-endometrioid endometrial carcinomas: a PSM-IPTW analysis based on SEER database

PURPOSE

To investigate outcomes of adjuvant treatments for non-endometrioid endometrial carcinomas (NEEC), as previous studies are limited by its rarity and heterogeneity.

PATIENTS AND METHODS

Patients with endometrial serous carcinoma (SC), clear cell carcinoma (CCC) and carcinosarcoma were identified between 2004 and 2018 from SEER database. Propensity score matching (PSM) along with inverse probability treatment weighting (IPTW) technique were employed to balance confounding factors. Multivariate, exploratory subgroup and sensitivity analyses were conducted to evaluate the impact of adjuvant treatment on overall survival (OS) and cause-specific survival (CSS).

RESULTS

The cohort comprised 5577 serous, 977 clear cell, and 959 carcinosarcomas. Combined chemotherapy and radiotherapy (CRT), chemotherapy alone, and radiotherapy alone were respectively administered in 42.21%, 47.27% and 10.58% of the whole cohort. Prior to adjusting, chemotherapy plus brachytherapy yielded the most beneficial effect among various strategies. After PSM-IPTW adjustment, CRT still demonstrated beneficial effect on OS and CSS. Subgroup analysis indicated CRT improved survival among various TNM stages, particularly with uterine carcinosarcoma. In the sensitivity analyses for serous histology, brachytherapy with or without chemotherapy appeared to benefit stage I-II patients. In stage III-IV SC patients, chemotherapy plus brachytherapy was still associated with improved survival outcomes. When nodal metastases were identified, additional external beam radiotherapy (EBRT) to CT was more utilized with survival improvement.

CONCLUSION

In NEEC patients, combined CRT yielded beneficial effects than any single mode. Both chemotherapy and brachytherapy promoted survival in early stage SC patients. Late stage SC patients may benefit from chemotherapy plus either EBRT or brachytherapy.

Missing a chance to prevent: disparities in completion of genetic evaluation in high-risk patients with endometrial cancer

OBJECTIVE

The primary goal of this study is to examine disparities in high-risk endometrial cancer (EC) patients in relation to rates of genetic referrals (GR), testing (GT), and counseling (GC).

METHODS

This is a retrospective analysis of patients with newly diagnosed EC between January 1, 2014 and September 1, 2020 at a single institution. Patients were defined as high-risk EC patients when they were 1) diagnosed at 50 years or younger, 2) had a positive family history for cancer or 3) had evidence of loss of mismatch repair protein expression on tumor immunohistochemistry. Rates of GR, GT and GC were analyzed based on race, ethnicity, primary language and insurance status.

RESULTS

During the study period, 674 patients were diagnosed with EC and 249 (36.9%) were considered high-risk EC patients. Among high-risk patients, 128 (51.2%) were referred to GT and GC. Of those referred, 103 (80.5%) underwent GT and 85 (66.4%) completed GC. Out of all high-risk patients, 20 (18.4%) were positive for LS on GT and 29 (28.2%) had VUS results. In multivariate analysis, the odds of GT and GC referral were lower among patients who identified as Hispanic (OR=0.40; 95% CI=0.19-0.87; p=0.020). Patients who identified as black were less likely to receive GC when compared to patients of other races (p=0.030).

CONCLUSION

It is our hope that through this data we will increase awareness around existing disparities in genetic evaluation for patients with EC and ultimately create strategies to improve equitable access to care for all patients.

Impact of sentinel lymph node assessment on the outcomes of patients with advanced endometrial cancer: A meta-analysis

BACKGROUND

Sentinel lymph node (SLN) assessment is used to treat early endometrial cancer; however, its application in advanced endometrial cancer remains controversial. Therefore, we assessed the effects of SLN assessment and lymphadenectomy (LND) on the prognosis (survival rate and primary outcome) of patients with advanced endometrial cancer.

METHODS

Pertinent studies were selected from PubMed, Embase, Web of Science, and the Cochrane Library until March 19, 2022. Relevant studies were strictly screened according to the inclusion and exclusion criteria. Data from the included studies were extracted and their quality was evaluated. Then RevMan5.4 software was used for the meta-analysis.

RESULTS

Four retrospective studies were included, which enrolled 7181 patients; 492 were treated with SLN and 6689 with LND. In terms of overall survival, there was no significant difference between the 2 groups (odds ratio = 1.14, 95% confidence interval: 0.92-1.41, I2 = 0%, P = .39).

CONCLUSIONS

SLN assessment is an alternative to LND as a treatment modality for advanced endometrial cancer.

Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD) Is Associated with Cervical Stromal Involvement in Endometrial Cancer Patients: A Cross-Sectional Study in South China

BACKGROUND

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a significant health issue closely associated with multiple extrahepatic cancers. The association between MAFLD and clinical outcomes of endometrial cancer (EC) remains unknown.

METHODS

We retrospectively included 725 EC patients between January 2012 and December 2020. The odds ratios (ORs) were calculated using logistic regression analyses. Kaplan-Meier survival curves were used for survival analysis.

RESULTS

Among EC patients, the prevalence of MAFLD was 27.7% (201/725, 95% confidence interval (Cl) = 0.245-0.311). MAFLD was significantly associated with cervical stromal involvement (CSI) (OR = 1.974, 95% confidence interval (Cl) = 1.065-3.659, p = 0.031). There was a significant correlation between overall survival (OS) and CSI (HR = 0.31; 95%CI: 0.12-0.83; p = 0.020), while patients with MAFLD had a similar OS to those without MAFLD (p = 0.952). Moreover, MAFLD was significantly associated with CSI in the type I EC subgroup (OR = 2.092, 95% confidence interval (Cl) = 1.060-4.129, p = 0.033), but not in the type II EC subgroup (p = 0.838). Further logistic regression analysis suggested that the hepatic steatosis index (HSI) was significantly associated with CSI among type I EC patients without type 2 diabetes mellitus (T2DM) (OR = 1.079, 95% confidence interval (Cl) = 1.020-1.139, p = 0.012).

CONCLUSIONS

About one-quarter of our cohort had MAFLD. MAFLD was associated with the risk of CSI in EC patients, and this association existed in type I EC patients but not in type II EC patients. Furthermore, the HSI can help predict CSI in type I EC patients without T2DM.

Novel Insights into Molecular Mechanisms of Endometrial Diseases

Endometrial diseases are the most common gynecological pathologies in Western Countries [...].