Predictive Models Revolutionizing Palliative Radiotherapy for Bone Metastases

Palliative radiotherapy remains a cornerstone for the management of bone metastases, offering crucial relief from pain and preserving quality of life for patients with advanced cancer. As the oncology population ages and disease trajectories become increasingly complex, the need for timely, tailored, and evidence-based approaches to palliative care has grown exponentially. Predictive modeling has emerged as a transformative force, enabling clinicians to anticipate patient outcomes, select optimal therapies, and improve shared decision-making for individuals facing bone metastases.Despite progress, significant challenges remain. The integration of machine learning, statistical, and radiomics-based predictive models into clinical workflows is still in its infancy, with wide variability in model performance, endpoints evaluated, and real-world applicability. The goal of this Research Topic is to address these gaps by spotlighting innovative approaches that not only refine outcome prediction but also enhance patient-centered care in the palliative radiotherapy setting.We invite authors to contribute studies that explore, but are not limited to:• Development, validation, or implementation of predictive models (including statistical, machine learning, and AI-based approaches) for pain response, overall survival, functional outcomes, toxicity, or quality of life in patients receiving palliative radiotherapy for bone metastases.• Radiomics and imaging biomarkers to inform prognosis and guide personalized treatment selection.• Integration of biological or molecular markers with predictive models for enhanced risk stratification.• Clinical decision support tools and digital health solutions using predictive analytics in palliative bone metastases.• Comparative studies evaluating predictive models or scores in different clinical scenarios.• Challenges and strategies for translating predictive models from research to bedside, including studies on validation, generalizability, or implementation science.Authors are encouraged to consider both technical and clinical aspects, bridging the gap between model development and meaningful patient outcomes. We strongly welcome multi-disciplinary and collaborative submissions, from proof-of-concept offerings to practical guidelines for implementation in real-world settings. By consolidating new evidence and perspectives at the intersection of prediction science and palliative oncologic care, this collection aims to advance the precision and effectiveness of radiotherapy for bone metastases.Please note: manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal. Topic editors: Maja Guberina, Maria Carmen De Santis, Osamu Tanaka, Riccardo Ray Colciago, Federico Mastroleo Source: https://www.frontiersin.org/research-topics/85353/predictive-models-revolutionizing-palliative-radiotherapy-for-bone-metastases