BACKGROUND:To better understand the complexity of sexual dysfunction, we aim to construct multi-factorial explanatory models of sexual dysfunction using data from participants enrolled in the Danish cross-sectional Study of latE effects for those liviNg through cErvical CAncer (SENECA). METHODS:In a nationwide survey, patient-reported outcomes (PRO) were collected from 2002 cervical cancer survivors treated with surgery and/or radio(chemo)therapy between 2005-2020 and a reference cohort consisting of 7853 women without a history of cancer. PROs in the EORTC C30/CX24 questionnaires were analysed. Bayesian Network models were developed for sexual activity and dyspareunia in reference and cancer survivor cohorts, resulting in four explanatory models. The reference cohort served as a structural prior for the cancer models. Sexual activity models included participants with complete data (6706 reference, 1694 cancer), while dyspareunia models included those reporting sexual activity in the past four weeks (4521 reference, 996 cancer). RESULTS:Respondents were stratified by treatment received: (1) reference group (n = 7853), (2) surgery alone (n = 1285), (3) radio(chemo)therapy (RCT) with/without prior surgery (n = 951). Sexual inactivity was reported by 28%, 29% and 49% of reference, surgery and RCT groups respectively, and dyspareunia by 23%, 39% and 54%. Sexual activity was associated with age, treatment modality and social functioning. Social functioning was associated with cognitive and role functioning, global QoL, and financial difficulties, all of which were associated strongly with fatigue. Dyspareunia was associated with vaginal functioning and soreness. The strong associations observed in the cancer survivor cohort between fatigue and functional outcomes/QoL/sexual activity were absent in the reference cohort. CONCLUSIONS:Sexual inactivity and dyspareunia were more common in cervical cancer patients, particularly in those treated with RCT compared with the reference cohort. Differences in explanatory factors between cancer and reference cohorts highlight the need for cancer-specific approaches to sexual rehabilitation.

Background and Purpose Six annual teaching courses were conducted in India between 2017 and 2023, focusing on image-guided adaptive brachytherapy (IGABT) for cervical cancer. The course curriculum was developed as a collaborative initiative between the Association of Radiation Oncologists of India (AROI) and the European Society for Radiation Oncology (ESTRO). The present study reports the academic and clinical impact of these courses. Material and Methods A detailed online master survey of all participants (456 participants from 184 institutions) was conducted in 2023 to understand the impact of these courses on knowledge and practice. The outcomes were compared with pre-course surveys. Results Participants from 104 institutions responded to the master survey while 101 who continued to practice cervical cancer brachytherapy at the time of the survey were included. As per baseline pre-course surveys, imaging used routinely for brachytherapy planning was X-rays (25%), CT (75%) and MRI (10%). IC+IS applications and IGABT were used by 31% and 35% participants, respectively. In the master survey, improvement in knowledge and practice of IGABT was reported by 94% and 87% of respondents, respectively. Meaningful improvements were reported in implementation of critical processes like use of clinical drawings (33%), ultrasound guidance (17%), IC+IS applications (25%), target-volume delineation (38%) and volume-based prescription (35%). Frequent reasons cited for inability to implement and sustain these critical processes included large patient volume, lack of infrastructure, suboptimal human resources etc. Conclusion The survey results suggest that such teaching courses improve implementation of IGABT workflows for cervical cancer in clinical practice. Conference Presentation The outcome was presented in the Oral Proffered presentation at World Congress in Brachytherapy in 10-13 July 2024 at Maryland USA.

Climate change, pollution, and resource depletion pose significant challenges to modern society, including the healthcare sector. While the delivery of health services inherently entails energy and resource utilization, the health care sector has a relevant role to play for sustainable development, since it is estimated to account for approximately 4.7% of total greenhouse gas emissions in the EU whilst also contributing to natural resource depletion, toxic chemical release, and the generation of non-compostable waste. In response, the European Society for Radiotherapy and Oncology (ESTRO) established the Green Task Force in 2022 to support the development of a strategic framework, which integrates environmental sustainability into ESTRO’s activities.This position paper presents ESTRO’s principles for environmental sustainability, which focus on four key areas: (1) raising awareness and sharing best practices, (2) monitoring the environmental impact of ESTRO’s activities, (3) evaluating interventions to reduce carbon emissions and improve the environmental sustainability of ESTRO activities, and (4) embedding sustainability into governance and professional activities. Examples of strategies which can reduce climate impact of ESTRO activities include advocating for environmentally conscious radiotherapy practices, considering venues that facilitate shorter travelling for participants in ESTRO conferences and educational activities, promoting digital participation, facilitating sustainable travel options and promoting healthy lifestyle.By emphasizing sustainability, ESTRO aims to lead the radiation oncology community toward a more environmentally responsible future, balancing scientific progress with climate-conscious practices. This initiative aligns with global sustainability goals and underscores the role of oncology professionals in addressing the climate crisis.

PURPOSE:This report describes the impact of incidence, severity, and time spent in late gastrointestinal (GI) adverse events (AEs) after radio chemotherapy on Quality of Life (QoL) in locally advanced cervical cancer patients. MATERIALS AND METHODS:The Months and Severity Score (MOSES) was applied to late GI AEs (CTCAEv.3) in patients enrolled in the prospective EMBRACE-I study. MOSES scores accumulated severity and duration of diarrhea, flatulence, incontinence, proctitis, stenosis, fistula, bleeding, and MOSES scores for each endpoint were summed to cumulative MOSES (C-MOSES). Functioning (physical, role, emotional, cognitive, social) and QoL scales were assessed using EORTC C30 questionnaire. Patients were grouped according to two C-MOSES cut-offs (0.7 and 2.0). RESULTS:Of 1416 patients included in EMBRACE-I, 977 had both CTCAE and EORTC-C30 data available. The median follow-up was 53 months. C-MOSES ≥ 0.7 was associated with significantly lower functioning and QoL scores than C-MOSES < 0.7. Among patients with G1 AEs, 27.4% had C-MOSES ≥ 0.7, indicating that persistent low-grade symptoms can contribute substantially to burden. C-MOSES ≥ 2.0 was present in 9% of the patient population and was associated with even lower functioning and QoL scores. C-MOSES ≥ 2.0 was most often observed in patients with ≥ 4 AEs (75%). Diarrhea and flatulence had the highest contribution to C-MOSES scores. CONCLUSION:C-MOSES combined with CTCAE maximum grade method identified patients with a higher AE burden over time and worse QoL. This highlights the need to consider cumulative impact of incidence, severity, and duration of AE in assessments, reporting, and analysis.

Purpose. Morbidity endpoints in cancer clinical trials, such as individual or aggregated adverse events (AEs), may not fully capture the overall patients’ burden. This work aims to develop a patient-informed Cumulative Morbidity Score (CMS) which reflects patients’ quality of life (QOL).Materials and method. The CMS was developed using data from a prospective study (EMBRACE-I) enrolling 1416 locally advanced cervical cancer patients (2008-2015) who received radiochemotherapy and brachytherapy. Physician-assessed AEs (CTCAEv.3) and patient-reported outcome (EORTC-C30/CX24) were collected at baseline and follow-ups. Data from 3 months up to 3 years were analyzed. Two scores were developed based on CTCAE (CMSCTCAE) AEs and EORTC (CMSEORTC) symptoms. For each CMS, two independent random forest models ranked AEs/symptoms based on associations with: 1)global-QOL (EORTC-C30), 2)radiation treatment intensity (RTI). CMSCTCAE/ CMSEORTC were calculated as weighted sums of relevant AEs/symptoms identified by the random forest models. CMSCTCAE/ CMSEORTC were internally evaluated in EMBRACE-I by comparing patient subgroups.Results. The analysis included 1002 patients. CTCAE and EORTC rankings presented similar findings for associations with QOL and RTI. Fatigue, insomnia and organ-related symptoms (diarrhea, urinary frequency and incontinence, vaginal stenosis) were highly ranked. Further EORTC symptoms (pain, nausea, appetite loss, peripheral neuropathy) were also highly ranked. Different treatment groups displayed significant differences in CMSCTCAE/CMSEORTC.Conclusions. The feasibility of a data-driven and patient-informed approach to define a cumulative morbidity score was demonstrated. Findings highlight the importance of incorporating both general conditions/symptoms (i.e. fatigue, insomnia, pain) and organ-related endpoints. The generalizability for future clinical trials requires external validation.

Modern oncology increasingly relies on integrated, multimodality care, yet radiation oncology remains undervalued in strategic frameworks despite its central therapeutic role. This ESTRO manifesto calls for a repositioning of radiation oncology as a core discipline in cancer care, scientifically, clinically, and politically. The field now extends beyond beam delivery to encompass systemic therapy integration, personalised strategies based on biology and imaging, and active participation in clinical decision-making and guideline development. Radiation oncology contributes to treatment sequencing, synergistic combinations, and innovation in areas such as radioligand therapy and artificial intelligence. ESTRO's initiatives, including education, research networks, and oncopolicy engagement, underscore the discipline's broad scope and societal value. Strategic partnerships with Pharma and MedTech, alongside a renewed emphasis on equitable access, are essential to sustaining progress. ESTRO invites all stakeholders to recognise radiation oncology as fundamental to the design, delivery, and evolution of modern cancer therapy.

PURPOSE:The Common Terminology Criteria for Adverse Events (CTCAE) is the established toxicity scoring system that assigns severity grades (G1 = mild to G5 = death) to Adverse Events (AEs). Compared to CTCAE v3.0 (2006), updated versions introduced changes in severity grade definitions. This study evaluated changes between v3.0 and v5.0 (2017) for AEs in gynaecological radiotherapy. MATERIAL AND METHODS:After selecting AEs relevant for gynaecological radiotherapy in v3.0, changes in severity grades were identified using CTCAE v3.0-to-v5.0 mapping tables. Six radiation oncologists (ROs) evaluated severity grade definitions for changes in: clinical interpretation, subjective (patient-reported symptoms) and objective (details on medication/intervention) information, and expected severe (≥G3) events. Agreement was based on at least five (≥5)ROs. RESULTS:Gastrointestinal, urinary, reproductive, general and injury/musculoskeletal AEs were selected (n = 118). G4 definitions in v5.0 were removed in 22 % of AEs. ≥5ROs agreed on changes affecting clinical interpretation especially for G2 (31 %) and G3 (30 %). For subjective information, 18 % of G2 and 15 % of G3 were judged relying more on patient-reported symptoms. Less objective information was found in 51 % of G3 definitions. Variability in agreement was observed especially for subjective information in G3 and expected ≥G3 events. CONCLUSION:This analysis revealed that severity grade definitions in v3.0 and v5.0 for AEs in gynaecological radiotherapy present changes with potential impact on scoring in clinical studies. Notably, 22 % of AEs in v5.0 no longer have G4 defined, and G3 definitions often include fewer details on medication/intervention. Variability in ROs' interpretations is frequently observed, highlighting the need for education to standardise toxicity scoring.

Background Climate change is an escalating crisis with significant implications for public health and healthcare services. We aimed to survey radiation oncology (RO) professionals on their understanding and concerns about climate change and the role of ESTRO in addressing the crisis. Materials and Methods A 14-item survey covering environmental impact of RO activities, personal actions, and expectations of ESTRO’s responses to the climate crisis was developed, validated, and disseminated to RO professionals by email and online platforms. Results 706 responses were received out of 9,781 ESTRO members. Concern about climate change was indicated by 90% of respondents and 94% had changed their personal lives to help combat the climate crisis. Yet 50% of respondents could not identify RO’s main contributors to climate change. 39% reported positive attitudes to online conferences and 79% agreed that ESTRO should offer digital participation to reduce the carbon impact of travel. Reported barriers to digital participation were mainly related to lack of face-to-face interaction.Although additional time was the most common barrier to reducing flying for work-related trips, 47 % of respondents were willing to travel by train for ≥ 7 h to an ESTRO conference. The majority of respondents (82 %) agreed that ESTRO should ‘Increase engagement with manufacturers around environmental sustainability’. Conclusion Our results reveal strong concern about the climate crisis among RO professionals, willingness to implement change, lack of knowledge about climate impact of RO and support for ESTRO actions to support its members and the community in these efforts.

BACKGROUND AND PURPOSE:Healthcare professionals attend international meetings to network, disseminate science and update practice. Conferences have large carbon footprints, and this study aimed to estimate the carbon footprint of an ESTRO conference and potential reduction strategies while balancing needs of international networking. MATERIALS AND METHODS:The geographical distribution of ESTRO23 attendees was used. The Climatiq API was utilised to determine the carbon footprint, in kg CO2 equivalent (CO2e), of venue, accommodation and travel. The impact of venue location and train travel on total CO2e was estimated as well as impact of online attendance. The amount and impact of in-person networking was assessed through a post conference survey. RESULTS:The carbon footprint of ESTRO 2023 was 1.4 tCO2e per attendee. Centrally located venues had lowest travel carbon footprint, e.g. Frankfurt with 8,873 tCO2e was 28 % lower than Lisbon. Hotel and venue accounted for < 5 % of the footprint. Train travel could reduce total CO2e by on average 17 % if all Europeans travelled by train. If all non-Europeans joined the conference online, CO2e would drop by 81 %. International networking of ≤ 2 h, 3-6 h and ≥ 7 h was seen in 45 %, 35 % and 20 % of attendees, respectively. CONCLUSION:The ESTRO conference has a significant carbon footprint, with travel accounting for > 95 % (81 % from long-haul flights). Centrally located venues and train travel are important means of reducing CO2e. The amount of international networking varies considerably across attendees, and regional or online participation can potentially reduce CO2e without compromising conference output for some attendees.

PURPOSE:This study aimed to assess patterns and risks of distant metastasis (DM) in patients with cervical cancer treated with chemoradiation therapy and MR-image guided adaptive brachytherapy (IGABT) and to explore a potential dose-effect relationship of concomitant cisplatin. METHODS AND MATERIALS:Data were derived from EMBRACE I, an international, prospective, and multicenter cohort study conducted at 24 centers across Europe, Asia, and North America from July 30, 2008, to December 29, 2015. The study included 1416 patients with biopsy-confirmed cervical cancer (International Federation of Gynecology and Obstetrics [FIGO2009] stage IB-IVA or stage IVB limited to paraaortic lymph nodes below the L1/L2 interspace). Treatment involved external beam radiation therapy (45-50.4 Gy), weekly cisplatin (40 mg/m², 30 mg/m², or paused), and IGABT. DM was defined as extra-pelvic recurrence excluding paraaortic nodes. RESULTS:The analysis included 1318 patients with a median age of 49 years and a median follow-up of 52 months. The 5-year cumulative incidence of DM was 14%, with the lungs (26%), mediastinal lymph nodes (15%), and bones (10%) identified as the most common metastatic sites. Key risk factors for DM included nonsquamous histology (HR, 1.89; 95% CI, 1.30-2.75), nodal involvement at diagnosis (pelvic-only nodes: HR, 1.56; 95% CI, 1.07-2.26; paraaortic nodes: HR, 3.15; 95% CI, 1.93-5.16), and large target volume at brachytherapy (HR, 1.93; 95% CI, 1.21-3.08). Patients receiving fewer than 4 cycles of chemotherapy demonstrated a significantly higher risk of DM (HR, 1.52; 95% CI, 1.08-2.13). CONCLUSION:DM is a substantial burden in patients with locally advanced cervical cancer, with the lungs, distant lymph nodes, and bones being the most frequent sites. Risk factors such as nonsquamous histology, nodal involvement, and large target volumes at brachytherapy are critical considerations for identifying high-risk patients in future studies. These findings highlight the need for tailored strategies to mitigate DM in this patient population.

BACKGROUND:Bayesian networks are seeing increased usage in healthcare, particularly for modeling complex treatment decisions under uncertainty. Bayesian networks offer significant advantages over classical machine learning and deep learning techniques due to their interpretability, with the network visualized through a directed acyclic graph outlining conditional relationships. Prior clinical knowledge can also be incorporated into these networks to enhance their clarity and facilitate integration into clinical workflows. However, out-of-box optimization techniques may produce networks that are not logically coherent or reflective of clinical understanding and may focus solely on optimizing information-based metrics without consideration for performance metrics crucial for developing predictive models. In late morbidity modeling, where the risk factors surrounding an outcome may be complex, intercorrelated, and not yet fully identified, it is important to have a customizable optimization approach to automatically produce logical, interpretable Bayesian networks that outline these complex outcomes. PURPOSE:Develop a simulated annealing-based framework for developing Bayesian network structures for late morbidity prediction in cervical cancer patients, addressing limitations of traditional optimization techniques and prioritizing interpretability. METHODS:This study utilizes the multi-center EMBRACE I cervical cancer dataset (n = 1153) to develop Bayesian network structures for late moderate-to-severe (grade ≥2) cystitis (CTCAEv.3) prediction. The dataset was split into training/validation data (80%) and holdout test data (20%). A process of 10 × 5-fold cross-validation was integrated into the optimization framework. A simulated annealing-based optimization method was developed incorporating information-theoretic measures, predictive performance measures, and complexity measures. The different network structures developed by this framework were compared in terms of complexity, interpretability, and predictive performance to optimization methods available out-of-box from the PyAgrum package for Python (Greedy Hill Climbing, Tree-Augmented Naïve Bayes, and Chow-Liu Optimization). Bayesian networks were also compared to conventional machine learning classifiers in terms of feature importance and predictive performance. Differences in model predictions arising from structure differences were assessed with Cochran's Q-test (p < 0.05). RESULTS:The simulated annealing framework demonstrated the ability to produce Bayesian network structures with comparable or superior predictive performance compared to out-of-box models. A statistically significant performance difference was identified between the simulated annealing and out-of-box methods with Cochran's Q-test (p = 0.03). The simulated annealing approach equalled or outperformed out-of-box models on a bootstrapped holdout test set, with a balanced accuracy of 64.1%, an F1 macro score of 55.9%, and an ROC-AUC of 0.66. Simulated annealing models also featured fewer arcs and nodes, with this simplification resulting in networks that were easier to interpret without compromising on predictive performance, highlighting the effectiveness of simulated annealing in creating highly interpretable models for clinical use. CONCLUSION:The proposed simulated annealing-based framework represents a novel method for automatically generating Bayesian network structures for cervical cancer late morbidity modeling. Compared to out-of-box optimization techniques, the simulated annealing Bayesian networks provide comparable or superior predictive performance while constructing a more simple, interpretable network useful for clinical implementation.

Our world faces transformative challenges that will shape the trajectory of healthcare, including radiation oncology, in the coming decades. Our society will need to adapt to global forces, continuously changing in an era of rapid technological change, a warming planet, changing demographics, economic uncertainty, and global conflicts. The new Society Matters section is an initiative from the Green Journal, which will focus on radiation oncology in a societal frame. As its full title clearly states, 'Society Matters - Sustainability, Education and Health Care Policy" aims to strengthen the radiation oncology profession and the radiation oncology community by being a platform for research, communication, debate, and dialogue within professional and societal matters such as environmental sustainability, social sustainability (equity, diversity, and inclusion), education, health economics, and health care policy. As a kick-off for the new section, this paper discusses sustainable radiation oncology in a world of change. It also aims to present the scope of articles of interest for the new section.