Background/Objectives: Endometriosis is a chronic gynecological disorder characterized by ectopic endometrial-like tissue. The symptoms of this disease negatively affect the patient’s quality of life, both physically and mentally. This study aims to identify key factors impacting health-related quality of life in endometriosis patients. Methods: A total of 175 patients from the Endometriosis Centre of the RWTH Aachen University Hospital were assessed using the German version of the EHP-30. The EHP is a patient self-report tool used to measure the wide range of impacts that endometriosis can have on women’s lives (affecting pain levels, leading to feelings of powerlessness and a loss of control, and affecting their emotional well-being, social support, and self-image). Multivariate linear regression and random forest analyses were performed to evaluate predictors of health-related quality of life, focusing on demographic characteristics, pain severity, endometriosis symptoms and planned procedures. Results: Key factors that have a significant negative impact on QoL include higher pain scores, dysuria, and persistent endometriosis. Higher pain scores negatively affect the EHP-30 pain (p < 0.0001), control and powerlessness (p < 0.0001) and emotional well-being (p < 0.01) scores. Dysuria has a negative effect on pain (p < 0.001), control and powerlessness (p < 0.001), emotional well-being (p < 0.05), and social support (p < 0.05). Persistent endometriosis was negatively associated with pain (p < 0.01), control and powerlessness (p < 0.01), and social support. Previous endometriosis surgery has a positive effect on the EHP-30 scores for pain, control and powerlessness, emotional well-being, and self-image (p < 0.05). Conclusions: Our study highlights the multifactorial impact of endometriosis on health-related QoL. Personalized treatments focusing on pain management, emotional support and social interventions are crucial to improve patient outcomes.

Background: Endometriosis is a chronic gynecological condition marked by ectopic endometrial-like tissue, leading to inflammation, pain, and infertility. Diagnosis is often delayed by up to 10 years. Identifying non-invasive biomarkers could facilitate earlier detection. MicroRNAs, known for their stability in biological fluids and role in disease processes, have emerged as potential diagnostic tools. This pilot study investigated whether serum miRNA profiling can differentiate endometriosis from other causes of chronic pelvic pain. Methods: Serum samples from 52 patients (36 with laparoscopically confirmed endometriosis and 16 controls) treated for chronic pelvic pain at a University Endometriosis Centre were analyzed. High-throughput miRNA sequencing was performed. Feature selection reduced 4285 miRNAs to the 20 most informative MiRNAs. Machine learning models, including logistic regression, decision tree, random forest, and support vector machine, were trained and evaluated. Results: Among the tested machine learning models, support vector machine achieved the best overall performance (accuracy 0.71, precision 0.80), while logistic regression and random forest showed the highest AUC values (0.84 and 0.81, respectively), indicating strong diagnostic potential of serum miRNA profiling. Conclusions: This study demonstrates the feasibility of using serum miRNA profiling combined with machine learning for the non-invasive classification of endometriosis. The identified miRNA signature shows strong diagnostic potential and could contribute to earlier and more accurate detection of the disease.

The GENEVIEVE study, comparing neoadjuvant cabazitaxel versus paclitaxel in triple-negative breast cancer (TNBC) and luminal B/human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC), previously reported significant differences in pathological complete response (pCR) rates. Effects on long-term outcome are unknown. GENEVIEVE randomized patients with cT2-3, any cN or cT1, cN+/pN_SLN+, centrally confirmed TNBC or luminal B/HER2-negative BC (latter defined as estrogen/progesterone receptor-positive and >14% Ki-67-stained cells) to receive either cabazitaxel 25 mg/m² q3w for four cycles or paclitaxel 80 mg/m² weekly for 12 weeks. Anthracycline-containing chemotherapy was allowed in case of histologically proven invasive residuals as neoadjuvant treatment or after surgery as adjuvant treatment. Here we report the secondary endpoints invasive disease-free survival (iDFS), distant disease-free survival (DDFS), and overall survival (OS). Of the 333 patients randomized, 74.7% and 83.2% completed treatment in the cabazitaxel and paclitaxel arms, respectively. After a median follow-up of 89.3 months (interquartile range 68.8-97.3 months), 80 iDFS events (43 after cabazitaxel and 37 after paclitaxel) and 47 deaths (23 after cabazitaxel and 24 after paclitaxel) were reported. IDFS rates were not significantly different between the cabazitaxel and paclitaxel arms after a 3-year (83.6% versus 85.0%) and 5-year follow-up (76.2% versus 78.3%) [hazard ratio (HR) = 1.27, 95% confidence interval 0.82-1.96, P = 0.294], respectively. DDFS rates at 3 years (88.6% versus 87.8%) and 5 years (82.1% versus 82.8%) for cabazitaxel and paclitaxel were comparable (HR = 1.15, P = 0.573). Similarly, OS rates at 3 years (91.6% versus 91.8%) and 5 years (89.2% versus 86.8%) showed no significant differences (HR = 1.05, P = 0.872). Subgroup analysis for TNBC and luminal B/HER2-negative BCs indicated no significant variations in 3- or 5-year iDFS, DDFS, or OS. The significant differences in pCR rates observed in both treatment arms did not significantly impact long-term outcomes for patients treated with cabazitaxel versus paclitaxel in the GENEVIEVE trial.

Background: Adenomyosis remains difficult to diagnose non-invasively due to clinical overlap with endometriosis and the limited specificity of imaging techniques. This pilot study evaluated whether serum- and urine-derived microRNA (miRNA) profiles, combined with machine-learning approaches, could support non-invasive diagnosis. Methods: Serum and urine samples were collected from 59 patients undergoing surgery for chronic pelvic pain at the Endometriosis Centre of RWTH Aachen University Hospital. Seven patients had isolated adenomyosis, 34 had histologically confirmed endometriosis, and 18 served as negative controls. miRNAs were profiled using next-generation sequencing. A structured feature-selection pipeline (variance filtering, univariate testing, mutual information, recursive feature elimination) was applied before training Logistic Regression, Random Forest, Support Vector Machine, and Decision Tree models using cross-validation. Model performance was evaluated using accuracy, precision, recall, F1 score, and ROC-AUC. Results: Distinct miRNA signatures were detected in both serum and urine, with urine-based models showing superior discriminatory performance. Logistic Regression and Support Vector Machine achieved excellent separation in urine datasets, although perfect AUC values must be interpreted cautiously due to the small number of adenomyosis cases. In serum, Random Forest achieved the highest AUC values (up to 0.98). Several miRNAs, including miR-183-3p, miR-320d-2, and miR-17, emerged as promising candidate biomarkers for differentiating adenomyosis from endometriosis and from negative controls. Conclusions: This pilot study demonstrates the feasibility of liquid-biopsy miRNA profiling combined with machine learning for non-invasive adenomyosis detection. Although results are preliminary and require validation in larger cohorts, urine miRNA profiles may represent a promising complementary tool to improve diagnostic accuracy and reduce diagnostic delay.

Objective: Vulvar lichen sclerosus (VLS) is an underestimated chronic disease. It can cause significant symptom burden and sexual dysfunction. This study aimed to evaluate patient satisfaction and current challenges in the management of VLS in a certified dysplasia unit, particularly during the COVID-19 pandemic. Methods: This survey analyzed patients who had been diagnosed with VLS and treated at our DKG-certified dysplasia unit. The study was conducted during the COVID-19 pandemic in the Department of Gynecology and Obstetrics at the University of Aachen. The questionnaire contained 43 questions on general treatment, diagnostic delays, disease education, psychologic and sexual issues, and specific questions regarding the COVID-19 pandemic. The questionnaires were distributed between January 2021 and September 2023. Results: This study included 103 patients diagnosed with VLS, who were treated at our certified dysplasia unit. Overall, 48% of the patients were satisfied with the success of the therapy. Most participants reported psychologic problems (36.8%), fear of cancer (53.3%), or sexual restrictions (53.3%). Among the patients, 38% were bothered by the regular application of topical cortisone. However, 72% were willing to undergo treatment for more than 24 months. The COVID-19 outbreak in March 2020 had a significant negative impact on general VLS care from the patient’s perspective (3.83/5 before vs. 3.67/5 after; p = 0.046). There was a general request for booklets to inform and educate the patients about their disease. Furthermore, the respondents demanded a telephone hotline to answer the questions and wished for follow-up visits via e-mail to cope better with their current situation. Conclusion: This study highlights the need for more effective treatments for VLS and an increased awareness of psychologic and sexual distress. To ensure patient well-being and satisfaction, it is imperative to offer individualized care with adequate disease education in a team of specialists from various disciplines.