Association between Regular Vaginal Dilation and/or Sexual Activity and Long-Term Vaginal Morbidity in Cervical Cancer Survivors

PURPOSE/OBJECTIVE(S)

To evaluate the association between regular vaginal dilation and/or sexual activity and vaginal morbidity in locally advanced cervical cancer patients after definitive radiochemotherapy and image-guided adaptive brachytherapy from the EMBRACE I study.

MATERIALS/METHODS

Physician-assessed vaginal morbidity (CTCAE v.3), vaginal dilation and patient-reported sexual activity (EORTC QLQ CX24) were assessed at baseline, every 3 months in the 1st year, every 6 months in the 2nd and 3rd year and yearly thereafter. For this longitudinal analysis, a subgroup of patients was selected with at least 3 follow-ups with information on vaginal dilation and/or sexual activity. Vaginal penetration summarized either the use of vaginal dilators or sexual activity or both. Regular vaginal penetration was defined if reported in ≥50%, infrequent if reported in <50% and absent if reported in 0% of follow-ups. Actuarial estimates of vaginal morbidity were calculated with Kaplan-Meier method and included the individual symptoms: vaginal dryness, stenosis, mucositis and bleeding. Group comparisons were evaluated with the log-rank test.

RESULTS

The EMBRACE I study included 1416 patients overall (2008-2015); the subgroup of patients for this longitudinal evaluation consists of 882 patients, with a median follow-up of 60 months (IQR 47-77). Of those, 565 (64%) reported regular, 205 (23%) infrequent and 112 (13%) no penetration. Reporting regular penetration was associated with a significantly lower risk of vaginal stenosis G≥2 of 23% at 5 years, compared to reporting of infrequent (37%) and no penetration (36%, p≤0.001). However, reporting regular penetration was associated with a significantly higher risk for vaginal dryness G≥1 (72% vs. 69% vs. 62%, respectively, p = 0.038) and bleeding G≥1 (61% vs. 40% vs. 25%, respectively, p≤0.001). No associations were seen for G≥1 vaginal stenosis, G≥2 dryness, G≥2 bleeding and G≥1/G≥2 mucositis.

CONCLUSION

Regular penetration (defined as vaginal dilation and/or sexual activity) was associated with lower risk for vaginal stenosis G≥2, but higher risk for vaginal dryness G≥1 and bleeding G≥1. Mild vaginal dryness seems to become apparent in particular for patients experiencing vaginal penetration. Minor vaginal blood loss during dilation and/or sexual activity is commonly reported by patients, resulting from atrophy of the vaginal mucosa and/or telangiectasia. While both of these G≥1 symptoms can be managed with lubricants, moisturizer and/or hormonal replacement therapy, G≥2 vaginal stenosis represents an irreversible fibrotic adverse event that can cause dyspareunia in many cancer patients. These long-term data support clinical recommendations for dilation and/or sexual activity after radiotherapy.

Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts

BACKGROUND

Endometrial cancer can be molecularly classified into POLE^mut, mismatch repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) subgroups. We aimed to develop an interpretable deep learning pipeline for whole-slide-image-based prediction of the four molecular classes in endometrial cancer (im4MEC), to identify morpho-molecular correlates, and to refine prognostication.

METHODS

This combined analysis included diagnostic haematoxylin and eosin-stained slides and molecular and clinicopathological data from 2028 patients with intermediate-to-high-risk endometrial cancer from the PORTEC-1 (n=466), PORTEC-2 (n=375), and PORTEC-3 (n=393) randomised trials and the TransPORTEC pilot study (n=110), the Medisch Spectrum Twente cohort (n=242), a case series of patients with POLE^mut endometrial cancer in the Leiden Endometrial Cancer Repository (n=47), and The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma cohort (n=395). PORTEC-3 was held out as an independent test set and a four-fold cross validation was performed. Performance was measured with the macro and class-wise area under the receiver operating characteristic curve (AUROC). Whole-slide images were segmented into tiles of 360 μm resized to 224 × 224 pixels. im4MEC was trained to learn tile-level morphological features with self-supervised learning and to molecularly classify whole-slide images with an attention mechanism. The top 20 tiles with the highest attention scores were reviewed to identify morpho-molecular correlates. Predictions of a nuclear classification deep learning model serve to derive interpretable morphological features. We analysed 5-year recurrence-free survival and explored prognostic refinement by molecular class using the Kaplan-Meier method.

FINDINGS

im4MEC attained macro-average AUROCs of 0·874 (95% CI 0·856-0·893) on four-fold cross-validation and 0·876 on the independent test set. The class-wise AUROCs were 0·849 for POLE^mut (n=51), 0·844 for MMRd (n=134), 0·883 for NSMP (n=120), and 0·928 for p53abn (n=88). POLE^mut and MMRd tiles had a high density of lymphocytes, p53abn tiles had strong nuclear atypia, and the morphology of POLE^mut and MMRd endometrial cancer overlapped. im4MEC highlighted a low tumour-to-stroma ratio as a potentially novel characteristic feature of the NSMP class. 5-year recurrence-free survival was significantly different between im4MEC predicted molecular classes in PORTEC-3 (log-rank p<0·0001). The ten patients with aggressive p53abn endometrial cancer that was predicted as MMRd showed inflammatory morphology and appeared to have a better prognosis than patients with correctly predicted p53abn endometrial cancer (p=0·30). The four patients with NSMP endometrial cancer that was predicted as p53abn showed higher nuclear atypia and appeared to have a worse prognosis than patients with correctly predicted NSMP (p=0·13). Patients with MMRd endometrial cancer predicted as POLE^mut had an excellent prognosis, as do those with true POLE^mut endometrial cancer.

INTERPRETATION

We present the first interpretable deep learning model, im4MEC, for haematoxylin and eosin-based prediction of molecular endometrial cancer classification. im4MEC robustly identified morpho-molecular correlates and could enable further prognostic refinement of patients with endometrial cancer.

FUNDING

The Hanarth Foundation, the Promedica Foundation, and the Swiss Federal Institutes of Technology.

Brachytherapy training survey among radiation oncology residents in Europe

We aim to investigate the current state of brachytherapy (BT) training among the radiation oncology trainees in Europe.

MATERIAL AND METHODS

A 22-question online survey based on the one by the American Association of Radiation Oncology Residents (2017) with added queries pertinent to training in Europe was sent to 1450 residents in two iterations. These included site-specific training, volume of experience, barriers to training, institutional support, and preferences for further education. Responses to individual statements were given on a 1 to 5 Likert-type scale. The answers were reported by junior (≤3 years of training) and senior years of training (year of training 4/5/6 and junior staff). Descriptive statistics were used to describe frequencies.

RESULTS

Residents from 21 European countries participated, 445 (31%) responded. 205 (47%) were senior residents. 60% residents consider that performing BT independently at the end of residency is very or somewhat important. Confidence in joining a brachytherapy practice at the end of residency was high or somewhat high in 34% of senior residents. They reported as barriers to achieving independence in BT to be lack of appropriate didactic/procedural training from supervisors (47%) and decreased case load (31%). 68% reported their program lacks a formal BT curriculum and standardized training assessment.

CONCLUSIONS

Residents in Europe, feel independent BT practice is very or somewhat important, but do not feel confident they will achieve this goal. To address this gap, efforts are needed to develop and implement a formal and comprehensive BT curriculum with easy access to trained instructors.

Nomogram Predicting Overall Survival in Patients With Locally Advanced Cervical Cancer Treated With Radiochemotherapy Including Image-Guided Brachytherapy: A Retro-EMBRACE Study

PURPOSE

To present a nomogram for prediction of overall survival (OS) in patients with locally advanced cervical cancer (LACC) undergoing definitive radiochemotherapy including image-guided adaptive brachytherapy (IGABT).

METHODS AND MATERIALS

Seven hundred twenty patients with LACC treated with radiochemotherapy including IGABT in 12 institutions (median follow-up 56 months) were analyzed; 248 deaths occurred. Thirteen candidate predictors for OS were a priori chosen on the basis of the literature and expert knowledge. Missing data (7.2%) were imputed using multiple imputation and predictive mean matching. Univariate analysis with a multivariable Cox regression model for OS stratified by center was performed. Stepwise selection of predictive factors with the Akaike Information Criterion was used to obtain a predictive model and construct a nomogram for OS predictions 60 months from diagnosis; this was internally validated by concordance probability as a measure of discrimination and a calibration plot.

RESULTS

Thirteen potential predictive factors were evaluated; 10 factors reached statistical significance in univariate analysis (age, Hemoglobin, FIGO Stage₂₀₀₉, tumor width, corpus involvement, lymph node involvement, concurrent chemotherapy, dose to 90% of the high-risk clinical target volume_, volume of CTV at the first brachytherapy [CTV_HRVolumeBT], overall treatment time [OTT]). Four factors were confirmed significant within the multivariable Cox regression model (FIGO Stage₂₀₀₉, lymph node involvement, concurrent chemotherapy, CTV_HRVolumeBT). The predictive model and corresponding nomogram were based on 7 Akaike Information Criterion-selected factors (age, corpus involvement, FIGO Stage₂₀₀₉, lymph node involvement, concurrent chemotherapy, CTV_HRVolumeBT, OTT) and showed promising calibration and discrimination (cross-validated concordance probability c = 0.73).

CONCLUSIONS

This is the first nomogram to predict OS in patients with LACC treated with IGABT. In addition to previously reported factors (age, FIGO₂₀₀₉ stage, corpus involvement, chemotherapy delivery, OTT, lymph node involvement), status of primary tumor at the time of brachytherapy seems to be an essential outcome predictor. These results can facilitate individualized tailoring of treatment and patient counseling during the treatment.