A snapshot of “real world” current neuro-oncology practice in ten UK centres participating in the Tessa Jowell BRAIN MATRIX platform study
Authors: Wykes Victoria , Apps John R , Savage Joshua , Meade Sara , Pohl Ute , Patel Amit , Billingham Lucinda , Thompson Gerard , Waldman Adam , Ansorge Olaf , Watts Colin 
Published: October 2021

Abstract

Aims
The TJBM Platform Study (https://www.birmingham.ac.uk/research/crctu/trials/brain-matrix) is a programme of work aimed at improving the knowledge of, and treatment for, glioma. The study will develop a backbone infrastructure for a molecular diagnostic pathway, particularly epigenetic classification and whole genome sequencing (WGS), and a data-repository of disease imaging, including real-time centralised Response Assessment in Neuro-Oncology (RANO) review, treatment and outcome data. Developed with the involvement of patients and relatives, patient reported outcome measures (PROMs), particularly quality of life assessment will be collected for patients.
We present the feasibility data collected from the initial ten UK centres selected to participate in the TJBM study. This presents an opportunity to understand current local neuro-oncology practice, identify differences between services and chances to optimise these, bearing in mind the heterogeneity in our patient populations, staff and hospital facilities.

Method
Ten UK centres were selected to participate in the TJBM platform study, and each centre completed a multi-disciplinary feasibility questionnaire to facilitate participation and collaboration across the centres. Data were collected from hospital electronic MDT (Multi-Disciplinary Team) records, clinic letters, operative and imaging notes, MDT or personal experience. Continuous variables were reported using medians and ranges due to the non-normality of the data and categorical variables were reported as numbers and percentages. Tables and bar charts were generated to display relevant data. Analysis and plots were generated using Microsoft Excel sheets and SPSS (IBM) version 26.

Results
Work load
Between 2016-2018 service provision redistribution reflects a trend towards higher volume centres. Overall, glioma workload within ten TJBM centres has remained stable (Figure 1).
Imaging All TJBM centres have good access to imaging techniques and neuroradiology expertise, including relevant ‘advanced’ imaging. All have RANO capability, although not widely used clinically.
Neurosurgery All centres have access to 5 ALA, perform awake craniotomy for language assessment and motor/sensory mapping are typically performed asleep, with subtle variation in techniques.
Pathology Despite molecular analysis advances, current practice is limited to the evaluation of formalin embedded tissue by traditional morphology/ immuno-histochemical staining, with limited targeted testing of specific genetic changes (Figure 2).
Clinical oncology Oncology treatments for glioma were as per NICE guidance with some minor local variation.
The data has informed the development of the TJBM protocol, an overview of which will be presented (Figure 3).

Conclusion
Through systematic real-world data collection the TJBM platform study will provide a detailed understanding of practice within the UK, linked to molecular tumour genotype, treatment response outcome measures, and also regular quality of life assessments.
Use of the platform infrastructure, will facilitate trials and add-on observational and biological studies to obtain rapid, efficient, and cost-effective data collection, and integrate findings with comprehensive molecular biological profiling and radiological features, thereby reducing the time and administrative burdens in trial delivery.
This infrastructure will help establish a trial-competent network on which future research and collaborations can be based. Academic and industry partners will be able to use the TJBM platform through collaboration, overseen by a strong governance framework. This will maximise the opportunities and abilities to translate advances into trials and patient benefit.