Desmoid tumours are a rare fibroblastic proliferation of monoclonal origin, arising in deep soft-tissues. Histologically, they are characterized by locally aggressive behaviour and an inability to metastasize, and clinically by a heterogeneous and unpredictable course. Desmoid tumours can occur in any anatomical site, but commonly arise in the limbs. Despite their benign nature, they can be extremely disabling and sometimes life-threatening, causing severe pain and functional limitations. Their surgical management is complex and challenging, due to uncertainties surrounding the biological and clinical behaviour, rarity, and limited available literature. Resection has been the first-line approach for patients with a desmoid tumour but, during the last few decades, a shift towards a more conservative approach has occurred, with an initial ‘wait and see’ policy. Many medical and regional forms of treatment are also available for the management of this condition, and others have recently emerged with promising results. However, many areas of controversy remain, and further studies and global collaboration are needed to obtain prospective and randomized data, in order to develop an appropriate shared stepwise approach. Cite this article:
Chondrosarcoma is the second most common surgically treated primary bone sarcoma. Despite a large number of scientific papers in the literature, there is still significant controversy about diagnostics, treatment of the primary tumour, subtypes, and complications. Therefore, consensus on its day-to-day treatment decisions is needed. In January 2024, the Birmingham Orthopaedic Oncology Meeting (BOOM) attempted to gain global consensus from 300 delegates from over 50 countries. The meeting focused on these critical areas and aimed to generate consensus statements based on evidence amalgamation and expert opinion from diverse geographical regions. In parallel, periprosthetic joint infection (PJI) in oncological reconstructions poses unique challenges due to factors such as adjuvant treatments, large exposures, and the complexity of surgery. The meeting debated two-stage revisions, antibiotic prophylaxis, managing acute PJI in patients undergoing chemotherapy, and defining the best strategies for wound management and allograft reconstruction. The objectives of the meeting extended beyond resolving immediate controversies. It sought to foster global collaboration among specialists attending the meeting, and to encourage future research projects to address unsolved dilemmas. By highlighting areas of disagreement and promoting collaborative research endeavours, this initiative aims to enhance treatment standards and potentially improve outcomes for patients globally. This paper sets out some of the controversies and questions that were debated in the meeting. Cite this article:
Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS. Cite this article:
Two discrete legal factors enable the surgeon to treat an injured patient the fully informed, autonomous consent of the adult patient with capacity via civil law; and the medical exception to the criminal law. This article discusses current concepts in consent in trauma; and also considers the perhaps less well known medical exception to the Offences against the Person Act 1861, which exempts surgeons from criminal liability as long as they provide ‘proper medical treatment’. Cite this article:
Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.
