Neoadjuvant radiotherapy followed by hysterectomy in locally advanced endometrial cancer: Outcomes from a tertiary government hospital in the Philippines

Objective

Managing endometrial cancer with suspected or gross cervical involvement lacks a standard approach. This study evaluated outcomes in patients with cervical and/or parametrial involvement treated with neoadjuvant radiation followed by hysterectomy.

Methods

Fourteen patients from 2007 to 2022 with locally advanced endometrial cancer and cervical and/or parametrial involvement were retrospectively analyzed. They received neoadjuvant external beam radiotherapy (45-50.4 Gy in 25-30 fractions) and high-dose rate brachytherapy (5.5-7.0 Gy per fraction in 3-4 fractions), followed by extrafascial hysterectomy. Clinical data, pathologic response, and survival outcomes were assessed, along with factors associated with pathologic response.

Results

Most patients (86%) had stage III disease with cervical extension, 93% had parametrial involvement, and 14% had nodal involvement. Chemotherapy was given to 86% either concurrently or adjuvantly. Post-surgery, 86% had no pathologic cervical involvement, and 93% had negative surgical margins. Pathologic complete response was seen in 43%. Locoregional recurrence occurred in 14%. Median follow-up was 30 months, with recurrence-free survival and overall survival rates of 86% and 100%, respectively. Lower grade tumors significantly correlated with pathologic complete response (Φ = 0.72, p = 0.026). No significant correlation was found between pathologic complete response and other factors. No late grade 3-4 toxicities were reported.

Conclusion

Neoadjuvant radiation followed by hysterectomy, with or without chemotherapy, is a viable strategy for managing endometrial cancer with cervical and/or parametrial involvement. This approach enhances resectability, yielding high rates of pathologic complete response and negative resection margins, showing promise for this challenging patient group.

Magnetic resonance imaging-based radiomics model for preoperative assessment of risk stratification in endometrial cancer

BACKGROUND

Preoperative risk stratification is significant for the management of endometrial cancer (EC) patients. Radiomics based on magnetic resonance imaging (MRI) in combination with clinical features may be useful to predict the risk grade of EC.

AIM

To construct machine learning models to predict preoperative risk stratification of patients with EC based on radiomics features extracted from MRI.

METHODS

The study comprised 112 EC patients. The participants were randomly separated into training and validation groups with a 7:3 ratio. Logistic regression analysis was applied to uncover independent clinical predictors. These predictors were then used to create a clinical nomogram. Extracted radiomics features from the T2-weighted imaging and diffusion weighted imaging sequences of MRI images, the Mann-Whitney U test, Pearson test, and least absolute shrinkage and selection operator analysis were employed to evaluate the relevant radiomic features, which were subsequently utilized to generate a radiomic signature. Seven machine learning strategies were used to construct radiomic models that relied on the screening features. The logistic regression method was used to construct a composite nomogram that incorporated both the radiomic signature and clinical independent risk indicators.

RESULTS

Having an accuracy of 0.82 along with an area under the curve (AUC) of 0.915 [95% confidence interval (CI): 0.806-0.986], the random forest method trained on radiomics characteristics performed better than expected. The predictive accuracy of radiomics prediction models surpassed that of both the clinical nomogram (AUC: 0.75, 95%CI: 0.611-0.899) and the combined nomogram (AUC: 0.869, 95%CI: 0.702-0.986) that integrated clinical parameters and radiomic signature.

CONCLUSION

The MRI-based radiomics model may be an effective tool for preoperative risk grade prediction in EC patients.

PErsonalized TReatment for Endometrial Carcinoma (PETREC): study design and methods of a prospective Finnish multicenter trial

BACKGROUND

Endometrial carcinomas can be classified into four molecular subgroups - mismatch repair deficient (MMRd), p53 abnormal (p53abn), polymerase-ϵ (POLE) ultramutated, and 'no specific molecular profile' (NSMP). Retrospective data imply that the response to adjuvant therapies may depend on the molecular subgroup. These findings emphasize the need for adjuvant therapy trials where patients are randomized to treatment arms separately within each molecular subgroup.

PRIMARY OBJECTIVE

The PErsonalized TReatment for Endometrial Carcinoma (PETREC) trial clarifies the value of molecular classification in the determination of adjuvant therapies of high-intermediate risk and early-stage high-risk endometrial carcinoma.

STUDY HYPOTHESIS

Compared with vaginal brachytherapy, the utilization of whole pelvic radiotherapy may result in improved outcomes for either MMRd or NSMP high-intermediate risk carcinomas. Early-stage high-risk p53abn and nonendometrioid carcinomas are postulated to gain benefits from chemoradiotherapy, as opposed to chemotherapy alone. POLE ultramutated carcinomas harboring high-intermediate or high-risk clinicopathologic features are speculated to have favorable prognosis without any adjuvant therapy.

TRIAL DESIGN

This prospective, multicenter, phase 3 trial compares the efficacy of vaginal brachytherapy vs whole pelvic radiotherapy in high-intermediate risk MMRd and NSMP molecular subgroups, and chemotherapy vs chemoradiotherapy in early-stage high-risk p53abn subtype and nonendometrioid carcinomas. Eligible women who consent to participation in the trial are randomly allocated (1:1) to treatment arms.

MAJOR INCLUSION/EXCLUSION CRITERIA

Women with stages I-II molecular integrated high-intermediate risk or high-risk endometrial carcinoma will be included.

PRIMARY ENDPOINT

The primary endpoint is the 5 year cumulative incidence of disease recurrence.

SAMPLE SIZE

A total sample size of 294 patients (49 subjects in each treatment arm of the three subgroups intended for randomization) was estimated to be sufficient.

ESTIMATED DATES FOR COMPLETING ACCRUAL AND PRESENTING RESULTS

Patient recruitment will be completed in 2025, and follow-up will be completed in 2030.

TRIAL REGISTRATION

NCT05655260.

Radiomics feature as a preoperative predictive of lymphovascular invasion in early-stage endometrial cancer: A multicenter study

Background

The presence of lymphovascular space invasion (LVSI) has been demonstrated to be significantly associated with poor outcome in endometrial cancer (EC). No effective clinical tools could be used for the prediction of LVSI preoperatively in early-stage EC. A radiomics nomogram based on MRI was established to predict LVSI in patients with early-stage EC.

Methods

This retrospective study included 339 consecutive patients with early-stage EC with or without LVSI from five centers. According to the ratio of 2:1, 226 and 113 patients were randomly assigned to a training group and a test group, respectively. Radiomics features were extracted from T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), contrast-enhanced (CE), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. The radiomics signatures were constructed by using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm in the training group. The radiomics nomogram was developed using multivariable logistic regression analysis by incorporating radiomics signatures and clinical risk factors. The sensitivity, specificity, and AUC of the radiomics signatures, clinical risk factors, and radiomics nomogram were also calculated.

Results

The individualized prediction nomogram was constructed by incorporating the radiomics signatures with the clinical risk factors (age and cancer antigen 125). The radiomics nomogram exhibited a good performance in discriminating between negative and positive LVSI patients with AUC of 0.89 (95% CI: 0.83–0.95) in the training group and of 0.85 (95% CI: 0.75–0.94) in the test group. The decision curve analysis indicated that clinicians could be benefit from the using of radiomics nomogram to predict the presence of LVSI preoperatively.

Conclusion

The radiomics nomogram could individually predict LVSI in early-stage EC patients. The nomogram could be conveniently used to facilitate the treatment decision for clinicians.

Multimodal MRI-Based Radiomics-Clinical Model for Preoperatively Differentiating Concurrent Endometrial Carcinoma From Atypical Endometrial Hyperplasia

Objectives

To develop and validate a radiomics model based on multimodal MRI combining clinical information for preoperative distinguishing concurrent endometrial carcinoma (CEC) from atypical endometrial hyperplasia (AEH).

Materials and Methods

A total of 122 patients (78 AEH and 44 CEC) who underwent preoperative MRI were enrolled in this retrospective study. Radiomics features were extracted based on T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. After feature reduction by minimum redundancy maximum relevance and least absolute shrinkage and selection operator algorithm, single-modal and multimodal radiomics signatures, clinical model, and radiomics-clinical model were constructed using logistic regression. Receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis were used to assess the models.

Results

The combined radiomics signature of T2WI, DWI, and ADC maps showed better discrimination ability than either alone. The radiomics-clinical model consisting of multimodal radiomics features, endometrial thickness >11mm, and nulliparity status achieved the highest area under the ROC curve (AUC) of 0.932 (95% confidential interval [CI]: 0.880-0.984), bootstrap corrected AUC of 0.922 in the training set, and AUC of 0.942 (95% CI: 0.852-1.000) in the validation set. Subgroup analysis further revealed that this model performed well for patients with preoperative endometrial biopsy consistent and inconsistent with postoperative pathologic data (consistent group, F1-score = 0.865; inconsistent group, F1-score = 0.900).

Conclusions

The radiomics model, which incorporates multimodal MRI and clinical information, might be used to preoperatively differentiate CEC from AEH, especially for patients with under- or over-estimated preoperative endometrial biopsy.

Molecular classification of endometrial carcinoma: a clinically oriented review

The Cancer Genome Atlas research network performed a genome-wide analysis of endometrial carcinomas in 2013 and classified tumours into four distinct subgroups: polymerase-ϵ ultramutated, microsatellite unstable hypermutated, copy-number low and copy-number high. These molecular alterations are mostly mutually exclusive as only about 3% of tumours exhibit more than one molecular signature. Apart from the polymerase-ϵ ultramutated subgroup, molecular classification can be reproduced by using surrogate markers. This has facilitated the implementation of molecular diagnostics into routine patient care. Molecular subgroups are associated with different prognoses; thus, improved risk assessment is their most obvious clinical application. However, based on their unique molecular architectures, molecular subgroups should not be regarded simply as risk groups but rather as distinct diseases. This has prompted us and others to examine the role of molecular subgroups in modifying the prognostic effect of traditional risk factors, including clinical factors, uterine factors and tissue biomarkers, and in predicting the response to adjuvant therapies. In the following review, we summarise the current knowledge of molecularly classified endometrial carcinoma and present, based on our own experience, a proposal for implementing molecular classification into daily practice in pathology laboratories.

Preoperative Assessment for High-Risk Endometrial Cancer by Developing an MRI- and Clinical-Based Radiomics Nomogram: A Multicenter Study

BACKGROUND

High- and low-risk endometrial cancer (EC) differ in whether lymphadenectomy is performed. Assessment of high-risk EC is essential for planning surgery appropriately.

PURPOSE

To develop a radiomics nomogram for high-risk EC prediction preoperatively.

STUDY TYPE

Retrospective.

POPULATION

In all, 717 histopathologically confirmed EC patients (mean age, 56 years ± 9) divided into a primary group (394 patients from Center A), validation groups 1 and 2 (146 patients from Center B and 177 patients from Centers C-E).

FIELD STRENGTH/SEQUENCE

1.5/3T scanners; T₂ -weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, and contrast enhancement sequences.

ASSESSMENT

A radiomics nomogram was generated by combining the selected radiomics features and clinical parameters (metabolic syndrome, cancer antigen 125, age, tumor grade following curettage, and tumor size). The area under the curve (AUC) of the receiver operator characteristic was used to evaluate the predictive performance of the radiomics nomogram for high-risk EC. The surgical procedure suggested by the nomogram was compared with the actual procedure performed for the patients. Net benefit of the radiomics nomogram was evaluated by a clinical decision curve (CDC), net reclassification index (NRI), and integrated discrimination improvement (IDI).

STATISTICAL TESTS

Binary least absolute shrinkage and selection operator (LASSO) logistic regression, linear regression, and multivariate binary logistic regression were used to select radiomics features and clinical parameters.

RESULTS

The AUC for prediction of high-risk EC for the radiomics nomogram in the primary group, validation groups 1 and 2 were 0.896 (95% confidence interval [CI]: 0.866-0.926), 0.877 (95% CI: 0.825-0.930), and 0.919 (95% CI: 0.879-0.960), respectively. The nomogram achieved good net benefit by CDC analysis for high-risk EC. NRIs were 1.17, 1.28, and 1.51, and IDIs were 0.41, 0.60, and 0.61 in the primary group, validation groups 1 and 2, respectively.

DATA CONCLUSION

The radiomics nomogram exhibited good performance in the individual prediction of high-risk EC, and might be used for surgical management of EC.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1872-1882.

Upfront radiotherapy with brachytherapy for medically inoperable and unresectable patients with high-risk endometrial cancer

OBJECTIVES

Comprehensive surgery with adjuvant therapy is standard of care for high-risk endometrial cancers, whereas upfront radiotherapy with brachytherapy is indicated for inoperable/unresectable patients, irrespective of risk. We evaluated outcomes for inoperable/unresectable patients with high-risk endometrial cancer (HREC: stage III and/or grade 3) and low-risk endometrial cancer (LREC: stage I/II and grade 1/2) treated with upfront radiotherapy.

METHODS

Twenty-nine patients with inoperable/unresectable endometrial cancer were treated with upfront radiotherapy at an academic medical center from 2012 to 2019. Cancer-specific survival (CSS), overall survival (OS), and recurrence rates between patients with HREC and LREC were compared.

RESULTS

Median follow-up was 17.0 months (range 3.7-54.0). Twenty cancers were stage I + II and nine were stage III. Twenty-one cancers were grade 1 + 2 and eight were grade 3. Thirteen patients (45%) had HREC. Twenty-five patients received radiotherapy/chemoradiotherapy for primary treatment, while 4 patients received chemoradiotherapy before surgery. All patients underwent high dose rate brachytherapy (HDR) with 7 receiving HDR alone and 22 receiving external beam radiation and HDR. Two-year CSS was 100% for both HREC and LREC patients (log-rank p = 0.32). There was no OS difference between HREC and LREC patients (2-year: 73% vs. 77%; log-rank p = 0.33). Four HREC and 1 LREC patients recurred with one local recurrence in each group. There were no acute grade ≥3 and two late grade ≥3 gastrointestinal/genitourinary toxicities.

CONCLUSIONS

Upfront radiotherapy for inoperable/unresectable HREC patients was well tolerated with high local control and CSS rates. Upfront radiotherapy with brachytherapy remains important even for high-risk inoperable and unresectable endometrial cancer patients.