A Web-based nomogram predicting para-aortic nodal metastasis in incompletely staged patients with endometrial cancer: a Korean Multicenter Study

The value of machine learning in preoperative identification of lymph node metastasis status in endometrial cancer: a systematic review and meta-analysis

Background

The early identification of lymph node metastasis status in endometrial cancer (EC) is a serious challenge in clinical practice. Some investigators have introduced machine learning into the early identification of lymph node metastasis in EC patients. However, the predictive value of machine learning is controversial due to the diversity of models and modeling variables. To this end, we carried out this systematic review and meta-analysis to systematically discuss the value of machine learning for the early identification of lymph node metastasis in EC patients.

Methods

A systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science until March 12, 2023. PROBAST was used to assess the risk of bias in the included studies. In the process of meta-analysis, subgroup analysis was performed according to modeling variables (clinical features, radiomic features, and radiomic features combined with clinical features) and different types of models in various variables.

Results

This systematic review included 50 primary studies with a total of 103,752 EC patients, 12,579 of whom had positive lymph node metastasis. Meta-analysis showed that among the machine learning models constructed by the three categories of modeling variables, the best model was constructed by combining radiomic features with clinical features, with a pooled c-index of 0.907 (95%CI: 0.886-0.928) in the training set and 0.823 (95%CI: 0.757-0.890) in the validation set, and good sensitivity and specificity. The c-index of the machine learning model constructed based on clinical features alone was not inferior to that based on radiomic features only. In addition, logistic regression was found to be the main modeling method and has ideal predictive performance with different categories of modeling variables.

Conclusion

Although the model based on radiomic features combined with clinical features has the best predictive efficiency, there is no recognized specification for the application of radiomics at present. In addition, the logistic regression constructed by clinical features shows good sensitivity and specificity. In this context, large-sample studies covering different races are warranted to develop predictive nomograms based on clinical features, which can be widely applied in clinical practice.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023420774.

Factor affecting lymph node metastasis in uterine papillary serous carcinomas: a retrospective analysis

The aim of this study was to investigate the risk factors for lymph node metastasis (LNM) in patients with uterine serous cancer (USC) who underwent systematic staging surgery. Eighty patients who were operated on for pure uterine serous papillary carcinoma between 2008 and 2020 in our clinic were retrospectively analysed. The effects of demographic information and clinicohistopathological characteristics of the included patients on LNM were examined. The median age of the patients included in the study was 64.3 and the tumour diameter was 3.8 cm. At the time of diagnosis, 65.8% of the cases were in the advanced stage, while 34.2% were in the early stage. There was no LNM in 42 (52.5%) of the cases, only pelvic in six (7.5%), only paraaortic LNM in four (5%) patients, and both pelvic and paraaortic LNM in 24 (30%) patients. When factors that may affect LNM were evaluated with multivariate analysis, lymphovascular space invasion (LVSI) and cytology positivity were found to be independent risk factors (p < 0.05). In addition, the rate of isolated paraaortic lymph node involvement in LNM positive patients is 5%, which is 100% associated with LVSI.Impact StatementWhat is already known on this subject? Uterine papillary serous carcinomas (UPSC) are an uncommon and aggressive histological subtype of endometrial cancer. The high risk of recurrence and tendency to migrate into the abdomen of these tumours is not always connected with lymph node and distant organ metastasis, tumour size, LVSI positive and depth of myometrial invasion.What do the results of this study add? Most patients with UPSC are diagnosed at an advanced stage. In this study, in which 80 patients with pure serous histology were evaluated retrospectively, and LVSI and peritoneal cytology positivity were found to be two important prognostic factors for lymph node metastasis.What are the implications of these findings for clinical practice and/or further research? In this study, cytology and LVSI positivity were identified as two predictive markers for LNM, and it is seen that cytology positivity still maintains its importance in these tumours with peritoneal spread. Furthermore, patients with isolated paraaortic lymph node involvement were shown to be LVSI positive, and isolated paraaortic LNM should be investigated in patients with LVSI positivity.

Association of Myometrial Invasion With Lymphovascular Space Invasion, Lymph Node Metastasis, Recurrence, and Overall Survival in Endometrial Cancer: A Meta-Analysis of 79 Studies With 68,870 Patients

Background

Myometrial invasion has been demonstrated to correlate to clinicopathological characteristics and prognosis in endometrial cancer. However, not all the studies have the consistent results and no meta-analysis has investigated the association of myometrial invasion with lymphovascular space invasion (LVSI), lymph node metastasis (LNM), recurrence, and overall survival (OS). Therefore, a meta-analysis was performed to evaluate the relationship between myometrial invasion and clinicopathological characteristics or overall survival in endometrial cancer.

Materials and Methods

A search of Pubmed, Embase, and Web of Science was carried out to collect relevant studies from their inception until June 30, 2021. The quality of each included study was evaluated using Newcastle–Ottawa scale (NOS) scale. Review Manager version 5.4 was employed to conduct the meta-analysis.

Results

A total of 79 articles with 68,870 endometrial cancer patients were eligible including 9 articles for LVSI, 29 articles for LNM, 8 for recurrence, and 37 for OS in this meta-analysis. Myometrial invasion was associated with LVSI (RR 3.07; 95% CI 2.17–4.35; p < 0.00001), lymph node metastasis (LNM) (RR 4.45; 95% CI 3.29–6.01; p < 0.00001), and recurrence (RR 2.06; 95% CI 1.58–2.69; p < 0.00001). Deep myometrial invasion was also significantly related with poor OS via meta-synthesis of HRs in both univariate survival (HR 3.36, 95% CI 2.35–4.79, p < 0.00001) and multivariate survival (HR 2.00, 95% CI 1.59–2.53, p < 0.00001). Funnel plot suggested that there was no significant publication bias in this study.

Conclusion

Deep myometrial invasion correlated to positive LVSI, positive LNM, cancer recurrence, and poor OS for endometrial cancer patients, indicating that myometrial invasion was a useful evaluation criterion to associate with clinical outcomes and prognosis of endometrial cancer since depth of myometrial invasion can be assessed before surgery. The large scale and comprehensive meta-analysis suggested that we should pay more attention to myometrial invasion in clinical practice, and its underlying mechanism also deserves further investigation.

PET Parameters are Useful in Predicting Endometrial Cancer Risk Classes and Prognosis

AIM

 We investigate the role of preoperative PET parameters to determine risk classes and prognosis of endometrial cancer (EC).

METHODS

 We enrolled 81 patients with EC who underwent preoperative F-18 FDG PET/CT. PET parameters (SUV_max, SUV_mean, MTV, TLG), grade, histology and size of the primary tumor, stage of the disease, the degree of myometrial invasion (MI), and the presence of lymphovascular invasion (LVI), cervical invasion (CI), distant metastasis (DM) and lymph node metastasis (LNM) were recorded. The relationship between PET parameters, clinicopathological risk factors and overall survival (OS) was evaluated.

RESULTS

 The present study included 81 patients with EC (mean age 60). Of the total sample, 21 patients were considered low risk (endometrioid histology, stage 1A, grade 1 or 2, tumor diameter < 4 cm, and LVI negative) and 60 were deemed high risk. All of the PET parameters were higher in the presence of a high-risk state, greater tumor size, deep MI, LVI and stage 1B-4B. MTV and TLG values were higher in the patients with non-endometrioid histology, CI, grade 3 and LNM. The optimum cut-off levels for differentiating between the high and low risk patients were: 11.1 for SUV_max (AUC = 0.757), 6 for SUV_mean (AUC = 0.750), 6.6 for MTV(AUC = 0.838) and 56.2 for TLG(AUC = 0.835). MTV and TLG values were found as independent prognostic factors for OS, whereas SUV_max and SUV_mean values were not predictive.

CONCLUSIONS

 The PET parameters are useful in noninvasively differentiating between risk groups of EC. Furthermore, volumetric PET parameters can be predictive for OS of EC.

American Brachytherapy Task Group Report: Adjuvant vaginal brachytherapy for early-stage endometrial cancer: A comprehensive review

This article aims to review the risk stratification of endometrial cancer, treatment rationale, outcomes, treatment planning, and treatment recommendations of vaginal brachytherapy (VBT) in the postoperative management of endometrial cancer patients. The authors performed a thorough review of the literature and reference pertinent articles pertaining to the aims of this review. Adjuvant VBT for early-stage endometrial cancer patients results in very low rates of vaginal recurrence (0-3.1%) with low rates of late toxicity which are primarily vaginal in nature. Post-Operative Radiation Therapy in Endometrial Cancer 2 (PORTEC-2) supports that VBT results in noninferior rates of vaginal recurrence compared to external beam radiotherapy for the treatment of high-intermediate risk patients. VBT as a boost after external beam radiotherapy, in combination with chemotherapy, and for high-risk histologies have shown excellent results as well though randomized data do not exist supporting VBT boost. There are many different applicators, dose-fractionation schedules, and treatment planning techniques which all result in favorable clinical outcomes and low rates of toxicity. Recommendations have been published by the American Brachytherapy Society and the American Society of Radiation Oncology to help guide practitioners in the use of VBT. Data support that patients and physicians prefer joint decision making regarding the use of VBT, and patients often desire additional treatment for a marginal benefit in risk of recurrence. Discussions regarding adjuvant therapy for endometrial cancer are best performed in a multidisciplinary setting, and patients should be counseled properly regarding the risks and benefits of adjuvant therapy.

New classification of endometrial cancers: the development and potential applications of genomic-based classification in research and clinical care

Endometrial carcinoma (EC) is the fourth most common cancer in women in the developed world. Classification of ECs by histomorphologic criteria has limited reproducibility and better tools are needed to distinguish these tumors and enable a subtype-specific approach to research and clinical care. Based on the Cancer Genome Atlas, two research teams have developed pragmatic molecular classifiers that identify four prognostically distinct molecular subgroups. These methods can be applied to diagnostic specimens (e.g., endometrial biopsy) with the potential to completely change the current risk stratification systems and enable earlier informed decision making. The evolution of genomic classification in ECs is shared herein, as well as potential applications and discussion of the essential research still needed in order to optimally integrate molecular classification in to current standard of care.

Predictive Modeling: A New Paradigm for Managing Endometrial Cancer

With the abundance of new options in diagnostic and treatment modalities, a shift in the medical decision process for endometrial cancer (EC) has been observed. The emergence of individualized medicine and the increasing complexity of available medical data has lead to the development of several prediction models. In EC, those clinical models (algorithms, nomograms, and risk scoring systems) have been reported, especially for stratifying and subgrouping patients, with various unanswered questions regarding such things as the optimal surgical staging for lymph node metastasis as well as the assessment of recurrence and survival outcomes. In this review, we highlight existing prognostic and predictive models in EC, with a specific focus on their clinical applicability. We also discuss the methodologic aspects of the development of such predictive models and the steps that are required to integrate these tools into clinical decision making. In the future, the emerging field of molecular or biochemical markers research may substantially improve predictive and treatment approaches.

Associations between etiologic factors and mortality after endometrial cancer diagnosis: the NRG Oncology/Gynecologic Oncology Group 210 trial

BACKGROUND

Few studies have analyzed relationships between risk factors for endometrial cancer, especially with regard to aggressive (non-endometrioid) histologic subtypes, and prognosis. We examined these relationships in the prospective NRG Oncology/Gynecologic Oncology Group 210 trial.

METHODS

Prior to surgery, participants completed a questionnaire assessing risk factors for gynecologic cancers. Pathology data were derived from clinical reports and central review. We used the Fine and Gray subdistribution hazards model to estimate subhazard ratios (HRs) and 95% confidence intervals (CIs) for associations between etiologic factors and cause-specific subhazards in the presence of competing risks. These models were stratified by tumor subtype and adjusted for stage and socioeconomic status indicators.

RESULTS

Median follow-up was 60months after enrollment (range: 1day-118months). Among 4609 participants, a total of 854 deaths occurred, of which, 582 deaths were attributed to endometrial carcinoma. Among low-grade endometrioid cases, endometrial carcinoma-specific subhazards were significantly associated with age at diagnosis (HR=1.04, 95% CI=1.01-1.06 per year, P-trend) and BMI (class II obesity vs. normal BMI: HR=2.29, 95% CI=1.06-4.98, P-trend=0.01). Among high-grade endometrioid cases, endometrial carcinoma-specific subhazards were associated with age at diagnosis (HR=1.05, 95% CI=1.02-1.07 per year, P-trend<0.001). Among non-endometrioid cases, endometrial carcinoma-specific subhazards were associated with parity relative to nulliparity among serous (HR=0.55, 95% CI=0.36-0.82) and carcinosarcoma cases (HR=2.01, 95% CI=1.00-4.05).

DISCUSSION

Several endometrial carcinoma risk factors are associated with prognosis, which occurs in a tumor-subtype specific context. If confirmed, these results would suggest that factors beyond histopathologic features and stage are related to prognosis. ClinicalTrials.gov Identifier: NCT00340808.