Lodelinsart, Belgium

MIDI (MR Imaging Abnormality Deep Learning Identification)

An automated strategy for identifying abnormalities in head scans could address the unmet clinical need for faster abnormality identification times, potentially allowing for early intervention to improve short- and long-term clinical outcomes. Radiologist shortages and increased demand for MRI scans lead to delays in reporting, particularly in the outpatient setting. Furthermore, there is a wide variation in the management of incidental findings (IFs) discovered in 'healthy volunteers.' The routine reporting of 'healthy volunteer' scans by a radiologist poses logistical and financial challenges. It would be valuable to devise automated strategies to reliably and accurately identify IFs, potentially reducing the number of scans requiring routine radiological review by up to 90%, thus increasing the feasibility of implementing a routine reporting strategy. Deep learning is a novel technique in computer science that automatically learns hierarchies of relevant features directly from the raw inputs (such as MRI or CT) using multi-layered neural networks. A deep learning algorithm will be trained on a large database of head MRI scans to recognize scans with abnormalities. This algorithm will be trained to classify a subset of these scans as normal or abnormal and then tested on an independent subset to determine its validity. If the tested neural network demonstrates high diagnostic accuracy, future research participants and patients may benefit, as not all institutions currently review their research scans for incidental findings and clinical scans may not be reported for weeks in some cases. In both research and clinical scenarios, an algorithm could rapidly identify abnormal pathology and prioritize scans for reporting. In summary, the aim is to develop a deep learning abnormality detection algorithm for use in both research and clinical settings.

EXTENDed Antibiotic Durations Compared to Standard Durations for Patients With Complicated Intra-abdominal Infection.

UK data suggests that current treatment for complicated intra-abdominal infections (cIAIs) results in unacceptably high rates of cIAI relapse and extra-abdominal infection. As a guiding rule, shorter antibiotic durations are important to combat antimicrobial resistance, but this is not true when these shorter courses need repeating and result in more days in hospital. Optimal care for patients should be our primary concern. The EXTEND trial aims to find out whether a fixed extended duration of 28 days of antibiotics is superior to the current standard duration (typically 7-18 days) based on clinical outcomes and quality of life assessed over 180 days of follow up. Cost effectiveness will also be determined. A target of 1166 patients will be recruited from ICUs and hospital in-patient wards across approximately 30 NHS trust hospitals. Only patients that are able provide consent (or those with a consultee able to confirm whether the patient would wish to be included in the study) can take part in the trial. They will receive antibiotics as prescribed by their treating clinician, but the duration of treatment will be determined by randomisation. Patients will have equal chance of randomisation to the standard care arm, in which the antibiotic duration will be determined by the treating clinician, or the intervention arm, a fixed duration of 28 days treatment. Patients (or a personal consultee) will complete a quality of life questionnaire at baseline and 30, 60 and 180 days after randomisation. At follow-up timepoints they will also complete questionnaires on antibiotic use and health care resource use. Hospital notes will be used to collect data on inpatient admissions, relapse and further infections. The study is Sponsored by the University of Leeds

Renal Adjuvant MultiPle Arm Randomised Trial

Magnetic Resonance Tumour Regression Grade (mrTRG) as a Novel Biomarker - Phase III Non CTIMP Trial

The only phase III clinical trial in the UK offering watch and wait, the TRIGGER trial aims to validate mrTRG as an imaging biomarker for the stratified management of patients with locally advanced rectal cancer. The 'good responders' (mrTRG1&2) often have no evidence of tumour and it may be possible to avoid surgery in this group and so maintaining QoL while not impacting survival rates. The 'poor responders' (mrTRG3-5) are at high risk of poor oncological outcomes and this knowledge is useful in planning ongoing treatment and surveillance. TRIGGER is now a non-cTIMP trial as the protocol does not specify chemotherapy or IMP treatments. Decisions about the use of chemotherapy will be based upon local MDT discussions as is normal practice and national policy and the trial CRFs will capture these decisions and whether more treatment is given to patients or not. TRIGGER does not mandate or recommend the use of any treatments: specifically it does not suggest the use of investigational medicinal products. If any centre wishes to use IMPs this would be in the context of separate trial protocols and would not preclude entry into TRIGGER.

Randomised Evaluation of Sodium Dialysate Levels on Vascular Events

RESOLVE is a pragmatic, cluster-randomised, open-label study designed to evaluate in real-world conditions the comparative effectiveness of two default dialysate sodium concentrations. Dialysis sites will be randomised in a 1:1 ratio to a default dialysate sodium concentration of 137mmol/l or 140mmol/l. 'Default' is defined as the use of the allocated dialysate sodium for ≥ 90% of delivered dialysis sessions in the unit. All other care will be according to standard local practices as determined by the site. Outcomes will be assessed on individual patients dialysing at those sites. Sites will be asked to consent to participation while waiver or opt-out consent will be sought for individual patients. It is anticipated that site accrual will occur over 5-7 years with average study duration expected to be approximately 2-5 years. The actual length of the study will be end-point determined.

Myeloma XIV: Frailty-adjusted Therapy in Transplant Non-Eligible Patients With Newly Diagnosed Multiple Myeloma

The Role of Ixazomib in Autologous Stem Cell Transplant in Relapsed Myeloma - Myeloma XII (ACCoRd)