A randomised, double blind, placebo-controlled trial of a two-week course of dexamethasone for adult patients with a symptomatic Chronic Subdural Haematoma (Dex-CSDH trial).

Background: Chronic subdural haematoma is a collection of 'old blood' and its breakdown products in the subdural space and predominantly affects older people. Surgical evacuation remains the mainstay in the management of symptomatic cases. Objective: The Dex-CSDH (DEXamethasone in Chronic SubDural Haematoma) randomised trial investigated the clinical effectiveness and cost-effectiveness of dexamethasone in patients with a symptomatic chronic subdural haematoma. Design: This was a parallel, superiority, multicentre, pragmatic, randomised controlled trial. Assigned treatment was administered in a double-blind fashion. Outcome assessors were also blinded to treatment allocation. Setting: Neurosurgical units in the UK. Participants: Eligible participants included adults (aged ≥ 18 years) admitted to a neurosurgical unit with a symptomatic chronic subdural haematoma confirmed on cranial imaging. Interventions: Participants were randomly assigned in a 1 : 1 allocation to a 2-week tapering course of dexamethasone or placebo alongside standard care. Main outcome measures: The primary outcome was the Modified Rankin Scale score at 6 months dichotomised to a favourable (score of 0-3) or an unfavourable (score of 4-6) outcome. Secondary outcomes included the Modified Rankin Scale score at discharge and 3 months; number of chronic subdural haematoma-related surgical interventions undertaken during the index and subsequent admissions; Barthel Index and EuroQol 5-Dimension 5-Level utility index score reported at discharge, 3 months and 6 months; Glasgow Coma Scale score reported at discharge and 6 months; mortality at 30 days and 6 months; length of stay; discharge destination; and adverse events. An economic evaluation was also undertaken, during which the net monetary benefit was estimated at a willingness-to-pay threshold of £20,000 per quality-adjusted life-year. Results: A total of 748 patients were included after randomisation: 375 were assigned to dexamethasone and 373 were assigned to placebo. The mean age of the patients was 74 years and 94% underwent evacuation of their chronic subdural haematoma during the trial period. A total of 680 patients (91%) had 6-month primary outcome data available for analysis: 339 in the placebo arm and 341 in the dexamethasone arm. On a modified intention-to-treat analysis of the full study population, there was an absolute reduction in the proportion of favourable outcomes of 6.4% (95% confidence interval 11.4% to 1.4%; p = 0.01) in the dexamethasone arm compared with the control arm at 6 months. At 3 months, the between-group difference was also in favour of placebo (-8.2%, 95% confidence interval -13.3% to -3.1%). Serious adverse events occurred in 60 out of 375 (16.0%) in the dexamethasone arm and 24 out of 373 (6.4%) in the placebo arm. The net monetary benefit of dexamethasone compared with placebo was estimated to be -£97.19. Conclusions: This trial reports a higher rate of unfavourable outcomes at 6 months, and a higher rate of serious adverse events, in the dexamethasone arm than in the placebo arm. Dexamethasone was also not estimated to be cost-effective. Therefore, dexamethasone cannot be recommended for the treatment of chronic subdural haematoma in this population group. Future work and limitations: A total of 94% of individuals underwent surgery, meaning that this trial does not fully define the role of dexamethasone in conservatively managed haematomas, which is a potential area for future study. Trial registration: This trial is registered as ISRCTN80782810. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 13/15/02) and is published in full in Health Technology Assessment; Vol. 28, No. 12. See the NIHR Funding and Awards website for further award information.

Chronic subdural haematoma is one of the most common conditions managed in adult neurosurgery and mainly affects older people. It is an 'old' collection of blood and blood breakdown products found on the surface of the brain. Surgery to drain the liquid collection is effective, with most patients improving. Given that inflammation is involved in the disease process, a commonly used steroid, dexamethasone, has been used alongside surgery or instead of surgery since the 1970s. However, there is no consensus or high-quality studies confirming the effectiveness of dexamethasone for the treatment of chronic subdural haematoma. This study was designed to determine the effectiveness of adding dexamethasone to the normal treatment for patients with a symptomatic chronic subdural haematoma. The benefit of adding dexamethasone was measured using a disability score called the Modified Rankin Scale, which can be divided into favourable and unfavourable outcomes. This was assessed at 6 months after entry into the study. In total, 748 adults with a symptomatic chronic subdural haematoma treated in neurosurgical units in the UK participated. Each participant had an equal chance of receiving either dexamethasone or a placebo because they were assigned randomly. Neither the patients nor the investigators knew who received dexamethasone and who received placebo. Most patients in both groups had an operation to drain the haematoma and experienced significant functional improvement at 6 months compared with their initial admission to hospital. However, patients who received dexamethasone had a lower chance than patients who received placebo of favourable recovery at 6 months. Specifically, 84% of patients who received dexamethasone had recovered well at 6 months, compared with 90% of patients who received placebo. There were more complications in the group that received dexamethasone. This trial demonstrates that adding dexamethasone to standard treatment reduced the chance of a favourable outcome compared with standard treatment alone. Therefore, this study does not support the use of dexamethasone in treating patients with a symptomatic chronic subdural haematoma.

FISH analysis reveals CDKN2A and IFNA14 co-deletion is heterogeneous and is a prominent feature of glioblastoma.

Deletion of CDKN2A occurs in 50% of glioblastomas (GBM), and IFNA locus deletion in 25%. These genes reside closely on chromosome 9. We investigated whether CDKN2A and IFNA were co-deleted within the same heterogeneous tumour and their prognostic implications. We assessed CDKN2A and IFNA14 deletions in 45 glioma samples using an in-house three-colour FISH probe. We examined the correlation between p16INK4a protein expression (via IHC) and CDKN2A deletion along with the impact of these genomic events on patient survival. FISH analyses demonstrated that grades II and III had either wildtype (wt) or amplified CDKN2A/IFNA14, whilst 44% of GBMs harboured homozygous deletions of both genes. Cores with CDKN2A homozygous deletion (n = 11) were negative for p16INK4a. Twenty p16INK4a positive samples lacked CDKN2A deletion with some of cells showing negative p16INK4a. There was heterogeneity in IFNA14/CDKN2A ploidy within each GBM. Survival analyses of primary GBMs suggested a positive association between increased p16INK4a and longer survival; this persisted when considering CDKN2A/IFNA14 status. Furthermore, wt (intact) CDKN2A/IFNA14 were found to be associated with longer survival in recurrent GBMs. Our data suggest that co-deletion of CDKN2A/IFNA14 in GBM negatively correlates with survival and CDKN2A-wt status correlated with longer survival, and with second surgery, itself a marker for improved patient outcomes.

Cardiovascular events and venous thromboembolism after primary malignant or non-malignant brain tumour diagnosis: a population matched cohort study in Wales (United Kingdom).

BACKGROUND: Elevated standardised mortality ratio of cardiovascular diseases (CVD) in patients with brain tumours may result from differences in the CVD incidences and cardiovascular risk factors. We compared the risk of CVD among patients with a primary malignant or non-malignant brain tumour to a matched general population cohort, accounting for other co-morbidities. METHODS: Using data from the Secured Anonymised Information Linkage (SAIL) Databank in Wales (United Kingdom), we identified all adults aged ≥ 18 years in the primary care database with first diagnosis of malignant or non-malignant brain tumour identified in the cancer registry in 2000-2014 and a matched cohort (case-to-control ratio 1:5) by age, sex and primary care provider from the general population without any cancer diagnosis. Outcomes included fatal and non-fatal major vascular events (stroke, ischaemic heart disease, aortic and peripheral vascular diseases) and venous thromboembolism (VTE). We used multivariable Cox models adjusted for clinical risk factors to compare risks, stratified by tumour behaviour (malignant or non-malignant) and follow-up period. RESULTS: There were 2869 and 3931 people diagnosed with malignant or non-malignant brain tumours, respectively, between 2000 and 2014 in Wales. They were matched to 33,785 controls. Within the first year of tumour diagnosis, malignant tumour was associated with a higher risk of VTE (hazard ratio [HR] 21.58, 95% confidence interval 16.12-28.88) and stroke (HR 3.32, 2.44-4.53). After the first year, the risks of VTE (HR 2.20, 1.52-3.18) and stroke (HR 1.45, 1.00-2.10) remained higher than controls. Patients with non-malignant tumours had higher risks of VTE (HR 3.72, 2.73-5.06), stroke (HR 4.06, 3.35-4.93) and aortic and peripheral arterial disease (HR 2.09, 1.26-3.48) within the first year of diagnosis compared with their controls. CONCLUSIONS: The elevated CVD and VTE risks suggested risk reduction may be a strategy to improve life quality and survival in people with a brain tumour.

Clinical trials in cancer screening, prevention and early diagnosis (SPED): a systematic mapping review.

BACKGROUND: Global annual cancer incidence is forecast to rise to 27.5 M by 2040, a 62% increase from 2018. For most cancers, prevention and early detection are the most effective ways of reducing mortality. This study maps trials in cancer screening, prevention, and early diagnosis (SPED) to identify areas of unmet need and highlight research priorities. METHODS: A systematic mapping review was conducted to evaluate all clinical trials focused on cancer SPED, irrespective of tumour type. The National Cancer Research Institute (NCRI) portfolio, EMBASE, PubMed and Medline were searched for relevant papers published between 01/01/2007 and 01/04/2020. References were exported into Covidence software and double-screened. Data were extracted and mapped according to tumour site, geographical location, and intervention type. RESULTS: One hundred seventeen thousand seven hundred one abstracts were screened, 5157 full texts reviewed, and 2888 studies included. 1184 (52%) trials focussed on screening, 554 (24%) prevention, 442 (20%) early diagnosis, and 85 (4%) a combination. Colorectal, breast, and cervical cancer comprised 61% of all studies compared with 6.4% in lung and 1.8% in liver cancer. The latter two are responsible for 26.3% of global cancer deaths compared with 19.3% for the former three. Number of studies varied markedly according to geographical location; 88% were based in North America, Europe, or Asia. CONCLUSIONS: This study shows clear disparities in the volume of research conducted across different tumour types and according to geographical location. These findings will help drive future research effort so that resources can be directed towards major challenges in cancer SPED.

A spectroscopic liquid biopsy for the earlier detection of multiple cancer types.

BACKGROUND: A rapid, low-cost blood test that can be applied to reliably detect multiple different cancer types would be transformational. METHODS: In this large-scale discovery study (n = 2092 patients) we applied the Dxcover® Cancer Liquid Biopsy to examine eight different cancers. The test uses Fourier transform infrared (FTIR) spectroscopy and machine-learning algorithms to detect cancer. RESULTS: Area under the receiver operating characteristic curve (ROC) values were calculated for eight cancer types versus symptomatic non-cancer controls: brain (0.90), breast (0.76), colorectal (0.91), kidney (0.91), lung (0.91), ovarian (0.86), pancreatic (0.84) and prostate (0.86). We assessed the test performance when all eight cancer types were pooled to classify 'any cancer' against non-cancer patients. The cancer versus asymptomatic non-cancer classification detected 64% of Stage I cancers when specificity was 99% (overall sensitivity 57%). When tuned for higher sensitivity, this model identified 99% of Stage I cancers (with specificity 59%). CONCLUSIONS: This spectroscopic blood test can effectively detect early-stage disease and can be fine-tuned to maximise either sensitivity or specificity depending on the requirements from different healthcare systems and cancer diagnostic pathways. This low-cost strategy could facilitate the requisite earlier diagnosis, when cancer treatment can be more effective, or less toxic. STATEMENT OF TRANSLATIONAL RELEVANCE: The earlier diagnosis of cancer is of paramount importance to improve patient survival. Current liquid biopsies are mainly focused on single tumour-derived biomarkers, which limits test sensitivity, especially for early-stage cancers that do not shed enough genetic material. This pan-omic liquid biopsy analyses the full complement of tumour and immune-derived markers present within blood derivatives and could facilitate the earlier detection of multiple cancer types. There is a low barrier to integrating this blood test into existing diagnostic pathways since the technology is rapid, simple to use, only minute sample volumes are required, and sample preparation is minimal. In addition, the spectroscopic liquid biopsy described in this study has the potential to be combined with other orthogonal tests, such as cell-free DNA, which could provide an efficient route to diagnosis. Cancer treatment can be more effective when given earlier, and this low-cost strategy has the potential to improve patient prognosis.

Global serum profiling: an opportunity for earlier cancer detection.

The advances in cancer research achieved in the last 50 years have been remarkable and have provided a deeper knowledge of this disease in many of its conceptual and biochemical aspects. From viewing a tumor as a 'simple' aggregate of mutant cells and focusing on detecting key cell changes leading to the tumorigenesis, the understanding of cancer has broadened to consider it as a complex organ interacting with its close and far surroundings through tumor and non-tumor cells, metabolic mechanisms, and immune processes. Metabolism and the immune system have been linked to tumorigenesis and malignancy progression along with cancer-specific genetic mutations. However, most technologies developed to overcome the barriers to earlier detection are focused solely on genetic information. The concept of cancer as a complex organ has led to research on other analytical techniques, with the quest of finding a more sensitive and cost-effective comprehensive approach. Furthermore, artificial intelligence has gained broader consensus in the oncology community as a powerful tool with the potential to revolutionize cancer diagnosis for physicians. We herein explore the relevance of the concept of cancer as a complex organ interacting with the bodily surroundings, and focus on promising emerging technologies seeking to diagnose cancer earlier, such as liquid biopsies. We highlight the importance of a comprehensive approach to encompass all the tumor and non-tumor derived information salient to earlier cancer detection.

Emotional visual stimuli and simulated laparoscopic surgical performance: A pilot cohort study.

BACKGROUND: Exposure to stress prior to or during surgery can negatively impact performance. Management of stress is an essential non-technical skill required for safe practice. The effects of exposure to emotional visual stressors on surgical performance are poorly understood. This study aims to develop a model to investigate effects of emotive visual stimuli on simulated laparoscopic performance. METHODS AND MATERIALS: A single-centre cohort study. Thirty novice, simulator-naïve medical students were randomly allocated to view either positive, negative, or neutral emotional images (sourced from validated image registry). Participants focused for 5 s on the image before completing a peg-threading laparoscopic task. Time, instrument distance, speed, acceleration, motion smoothness, and ambidexterity were recorded automatically with instrument tracking software. 8 task cycles were completed; 3 control practices followed by 5 with the stimuli, according to group allocation. RESULTS: The final performance metrics of students (time, distance, speed, and motion smoothness) were not significantly different when comparing positive and neutral stimuli groups to those shown negative stimuli. However, changes were seen in the rate of performance improvements (positive: p = 0.711, p = 0.837, p = 0.297, and p = 0.393) (neutral: p = 0.285, p = 0.918, p = 0.835, and p = 0.396). Participation improved performance metrics overall (p=<0.001, p=<0.001, p = 0.088, p = 0.025, p=<0.001). CONCLUSION: Model systems may be valuable for investigating the impact of stress on surgeon performance. The effect of emotive visual stimuli on surgical performance is complex. This model may aid the further exploration of these relationships and ultimately can provide an environment in which surgeons can develop strategies to mitigate the adverse effect of stressors.

Reporting of PPI and the MCID in phase III/IV randomised controlled trials-a systematic review.

BACKGROUND: Patient and public involvement (PPI) in clinical trial design contributes to ensuring the research objectives and outcome measures are relevant to patients. The minimal clinically important difference (MCID) in the primary outcome influences trial design and feasibility and should be predicated on PPI. We aimed to determine current practice of reporting PPI and the MCID in phase III/IV randomised controlled trials (RCTs). METHODS: Following a search of Medline, Embase, and the Cochrane Central Register of Controlled Trials, we included primary publications of phase III/IV RCTs, in English, inclusive of any medical specialty or type of intervention, that reported a health-related outcome. We excluded protocols and secondary publications of RCTs. We extracted RCT characteristics, the use of PPI, and use of the MCID. RESULTS: Between 1 July 2019 and 13 January 2020, 123 phase III/IV RCTs matched our eligibility criteria. Ninety percent evaluated a medical rather than surgical intervention. Oncology accounted for 21% of all included RCTs. Only 2.4% (n = 3) and 1.6% (n = 2) RCTs described PPI and the MCID respectively. CONCLUSIONS: PPI and the MCID are poorly reported, so it is uncertain how these contributed to trial design. Improvement in the reporting of these items would increase confidence that results are relevant and clinically significant to patients, contributing to improving the overall trial design. TRIAL REGISTRATION: Not registered.

Approved and investigational fluorescent optical imaging agents for disease detection in surgery.

Fluorescent optical imaging is becoming an increasingly attractive imaging tool that physicians can utilise as it can detect previously 'unseen' changes in tissue at a cellular level that are consistent with disease. This is possible using a range of fluorescently labelled imaging agents that, once excited by specific wavelengths of light, can illuminate damaged and diseased tissues. For surgeons, such agents can permit dynamic, intraoperative imaging providing a real-time guide as they resect diseased tissue.

Development of prediction models for one-year brain tumour survival using machine learning: a comparison of accuracy and interpretability.

BACKGROUND AND OBJECTIVE: Prediction of survival in patients diagnosed with a brain tumour is challenging because of heterogeneous tumour behaviours and treatment response. Advances in machine learning have led to the development of clinical prognostic models, but due to the lack of model interpretability, integration into clinical practice is almost non-existent. In this retrospective study, we compare five classification models with varying degrees of interpretability for the prediction of brain tumour survival greater than one year following diagnosis. METHODS: 1028 patients aged ≥16 years with a brain tumour diagnosis between April 2012 and April 2020 were included in our study. Three intrinsically interpretable 'glass box' classifiers (Bayesian Rule Lists [BRL], Explainable Boosting Machine [EBM], and Logistic Regression [LR]), and two 'black box' classifiers (Random Forest [RF] and Support Vector Machine [SVM]) were trained on electronic patients records for the prediction of one-year survival. All models were evaluated using balanced accuracy (BAC), F1-score, sensitivity, specificity, and receiver operating characteristics. Black box model interpretability and misclassified predictions were quantified using SHapley Additive exPlanations (SHAP) values and model feature importance was evaluated by clinical experts. RESULTS: The RF model achieved the highest BAC of 78.9%, closely followed by SVM (77.7%), LR (77.5%) and EBM (77.1%). Across all models, age, diagnosis (tumour type), functional features, and first treatment were top contributors to the prediction of one year survival. We used EBM and SHAP to explain model misclassifications and investigated the role of feature interactions in prognosis. CONCLUSION: Interpretable models are a natural choice for the domain of predictive medicine. Intrinsically interpretable models, such as EBMs, may provide an advantage over traditional clinical assessment of brain tumour prognosis by weighting potential risk factors and their interactions that may be unknown to clinicians. An agreement between model predictions and clinical knowledge is essential for establishing trust in the models decision making process, as well as trust that the model will make accurate predictions when applied to new data.

Recurrent neural networks for time domain modelling of FTIR spectra: application to brain tumour detection.

Attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy alongside machine learning (ML) techniques is an emerging approach for the early detection of brain cancer in clinical practice. A crucial step in the acquisition of an IR spectrum is the transformation of the time domain signal from the biological sample to a frequency domain spectrum via a discrete Fourier transform. Further pre-processing of the spectrum is typically applied to reduce non-biological sample variance, and thus to improve subsequent analysis. However, the Fourier transformation is often assumed to be essential even though modelling of time domain data is common in other fields. We apply an inverse Fourier transform to frequency domain data to map these to the time domain. We use the transformed data to develop deep learning models utilising Recurrent Neural Networks (RNNs) to differentiate between brain cancer and control in a cohort of 1438 patients. The best performing model achieves a mean (cross-validated score) area under the receiver operating characteristic (ROC) curve (AUC) of 0.97 with sensitivity of 0.91 and specificity of 0.91. This is better than the optimal model trained on frequency domain data which achieves an AUC of 0.93 with sensitivity of 0.85 and specificity of 0.85. A dataset comprising 385 patient samples which were prospectively collected in the clinic is used to test a model defined with the best performing configuration and fit to the time domain. Its classification accuracy is found to be comparable to the gold-standard for this dataset demonstrating that RNNs can accurately classify disease states using spectroscopic data represented in the time domain.

The Immunopeptidome from a Genomic Perspective: Establishing the Noncanonical Landscape of MHC Class I-Associated Peptides.

Tumor antigens can emerge through multiple mechanisms, including translation of noncoding genomic regions. This noncanonical category of tumor antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry (MS) to enable the discovery of noncanonical MHC class I-associated peptides (ncMAP) from noncoding regions. Considering that the emergence of tumor antigens can also involve posttranslational modifications (PTM), we included an open search component in our pipeline. Leveraging the wealth of MS-based immunopeptidomics, we analyzed data from 26 MHC class I immunopeptidomic studies across 11 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant PTMs, using spectral matching and controlled their FDR to 1%. The noncanonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 55%. The data reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive therapeutic targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targets for T-cell therapies or vaccine development.

Liquid biopsies: the future of cancer early detection.

Cancer is a worldwide pandemic. The burden it imposes grows steadily on a global scale causing emotional, physical, and financial strains on individuals, families, and health care systems. Despite being the second leading cause of death worldwide, many cancers do not have screening programs and many people with a high risk of developing cancer fail to follow the advised medical screening regime due to the nature of the available screening tests and other challenges with compliance. Moreover, many liquid biopsy strategies being developed for early detection of cancer lack the sensitivity required to detect early-stage cancers. Early detection is key for improved quality of life, survival, and to reduce the financial burden of cancer treatments which are greater at later stage detection. This review examines the current liquid biopsy market, focusing in particular on the strengths and drawbacks of techniques in achieving early cancer detection. We explore the clinical utility of liquid biopsy technologies for the earlier detection of solid cancers, with a focus on how a combination of various spectroscopic and -omic methodologies may pave the way for more efficient cancer diagnostics.

Investigating centrifugal filtration of serum-based FTIR spectroscopy for the stratification of brain tumours.

Discrimination of brain cancer versus non-cancer patients using serum-based attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy diagnostics was first developed by Hands et al with a reported sensitivity of 92.8% and specificity of 91.5%. Cameron et al. then went on to stratifying between specific brain tumour types: glioblastoma multiforme (GBM) vs. primary cerebral lymphoma with a sensitivity of 90.1% and specificity of 86.3%. Expanding on these studies, 30 GBM, 30 lymphoma and 30 non-cancer patients were selected to investigate the influence on test performance by focusing on specific molecular weight regions of the patient serum. Membrane filters with molecular weight cut offs of 100 kDa, 50 kDa, 30 kDa, 10 kDa and 3 kDa were purchased in order to remove the most abundant high molecular weight components. Three groups were classified using both partial least squares-discriminate analysis (PLS-DA) and random forest (RF) machine learning algorithms; GBM versus non-cancer, lymphoma versus non-cancer and GBM versus lymphoma. For all groups, once the serum was filtered the sensitivity, specificity and overall balanced accuracies decreased. This illustrates that the high molecular weight components are required for discrimination between cancer and non-cancer as well as between tumour types. From a clinical application point of view, this is preferable as less sample preparation is required.

Scotland's "Incentivised Laparoscopy Practice" programme: Engaging trainees with take-home laparoscopy simulation.

BACKGROUND: The transfer validity of portable laparoscopy simulation is well established. However, attempts to integrate take-home simulation into surgical training have met with inconsistent engagement worldwide, as for example in our 2014-15 study of an Incentivised Laparoscopy Practice programme (ILPv1). Drawing on learning from our subsequent multi-centre study examining barriers and facilitators, we revised the programme for 2018 onwards. We now report on engagement with the 2018-2022 versions of this home-based simulation programme (ILP v2.1-2.3). METHODS: In ILP v2.1-2.3, three consecutive year-groups of new-start Core Surgical Trainees (n = 48, 46 and 53) were loaned portable simulators. The 6-month education programme included induction, technical support, and intermittent feedback. Six tasks were prescribed, with video instruction and charting of metric scores. Video uploads were required and scored by faculty. A pass resulted in an eCertificate, expected at Annual Review (but not mandatory for progression). ILP was set within a wider reform, "Improving Surgical Training". RESULTS: ILP v2.1-2.3 saw pass rates of 94%, 76% and 70% respectively (45/48, 35/46 and 37/53 trainees), compared with only 26% (7/27) in ILP v1, despite now including some trainees not intending careers in laparoscopic specialties. The ILP v2.2 group all reported their engagement with the whole simulation strategy was hampered by the COVID19 pandemic. CONCLUSIONS: Simply providing take-home simulators, no matter how good, is not enough. To achieve trainee engagement, a whole programme is required, with motivated learners, individual and group practice, intermittent feedback, and clear goals and assessments. ILP is a complex intervention, best understood as a "reform within a reform, within a context."

Oncogene expression from extrachromosomal DNA is driven by copy number amplification and does not require spatial clustering in glioblastoma stem cells.

Extrachromosomal DNA (ecDNA) are frequently observed in human cancers and are responsible for high levels of oncogene expression. In glioblastoma (GBM), ecDNA copy number correlates with poor prognosis. It is hypothesized that their copy number, size, and chromatin accessibility facilitate clustering of ecDNA and colocalization with transcriptional hubs, and that this underpins their elevated transcriptional activity. Here, we use super-resolution imaging and quantitative image analysis to evaluate GBM stem cells harbouring distinct ecDNA species (EGFR, CDK4, PDGFRA). We find no evidence that ecDNA routinely cluster with one another or closely interact with transcriptional hubs. Cells with EGFR-containing ecDNA have increased EGFR transcriptional output, but transcription per gene copy is similar in ecDNA compared to the endogenous chromosomal locus. These data suggest that it is the increased copy number of oncogene-harbouring ecDNA that primarily drives high levels of oncogene transcription, rather than specific interactions of ecDNA with each other or with high concentrations of the transcriptional machinery.

Impact of tumour characteristics and cancer treatment on cerebrovascular mortality after glioma diagnosis: Evidence from a population-based cancer registry.

Objective: We aimed to examine brain tumour grade, a marker of biological aggressiveness, tumour size and cancer treatment are associated with cerebrovascular mortality among patients with malignant glioma, the most common and aggressive type of brain tumour. Methods: We conducted a retrospective, observational cohort study using the US National Cancer Institute's state and regional population-based cancer registries. We identified adult patients with glioma in 2000 to 2018 (N=72,916). The primary outcome was death from cerebrovascular disease. Cox regression modelling was used to estimate the associations with cerebrovascular mortality of tumour grade, tumour size and treatment (surgery, radiotherapy, chemotherapy), calculating hazard ratios (HR) adjusted for these factors as well as for age, sex, race, marital status and calendar year. Results: Higher grade (Grade IV vs Grade II: HR=2.47, 95% CI=1.69-3.61, p<0.001) and larger brain tumours (size 3 to <6 cm: HR=1.40, 95% CI=1.03 -1.89, p<0.05; size ≥ 6 cm: HR=1.47, 95% CI=1.02-2.13, p<0.05 compared to size < 3cm) were associated with increased cerebrovascular mortality. Cancer treatment was associated with decreased risk (surgery: HR= 0.60, p<0.001; chemotherapy: HR=0.42, p<0.001; radiation: HR= 0.69, p<0.05). However, among patents surviving five years or more from cancer diagnosis radiotherapy was associated with higher risk of cerebrovascular mortality (HR 2.73, 95% CI 1.49-4.99, p<0.01). Conclusion: More aggressive tumour characteristics are associated with increased cerebrovascular mortality. Radiotherapy increased risk of cerebrovascular mortality five-year after cancer diagnosis. Further research is needed to better understand the long-term cardiovascular consequences of radiation therapy, and whether the consequent risk can be mitigated.

Imaging timing after glioblastoma surgery (INTERVAL-GB): protocol for a UK and Ireland, multicentre retrospective cohort study.

INTRODUCTION: Glioblastoma is the most common malignant primary brain tumour with a median overall survival of 12-15 months (range 6-17 months), even with maximal treatment involving debulking neurosurgery and adjuvant concomitant chemoradiotherapy. The use of postoperative imaging to detect progression is of high importance to clinicians and patients, but currently, the optimal follow-up schedule is yet to be defined. It is also unclear how adhering to National Institute for Health and Care Excellence (NICE) guidelines-which are based on general consensus rather than evidence-affects patient outcomes such as progression-free and overall survival. The primary aim of this study is to assess MRI monitoring practice after surgery for glioblastoma, and to evaluate its association with patient outcomes. METHODS AND ANALYSIS: ImagiNg Timing aftER surgery for glioblastoma: an eVALuation of practice in Great Britain and Ireland is a retrospective multicentre study that will include 450 patients with an operated glioblastoma, treated with any adjuvant therapy regimen in the UK and Ireland. Adult patients ≥18 years diagnosed with glioblastoma and undergoing surgery between 1 August 2018 and 1 February 2019 will be included. Clinical and radiological scanning data will be collected until the date of death or date of last known follow-up. Anonymised data will be uploaded to an online Castor database. Adherence to NICE guidelines and the effect of being concordant with NICE guidelines will be identified using descriptive statistics and Kaplan-Meier survival analysis. ETHICS AND DISSEMINATION: Each participating centre is required to gain local institutional approval for data collection and sharing. Formal ethical approval is not required since this is a service evaluation. Results of the study will be reported through peer-reviewed presentations and articles, and will be disseminated to participating centres, patients and the public.

A systematic review identifying outcome measures used in evaluating adults sustaining cervical spine fractures.

OBJECTIVE: To assess the outcome measures used in studies investigating cervical spine fractures in adults, with or without associated spinal cord injury, to inform development of a core outcome set. METHODS: Medline, Embase and Scopus were searched for relevant studies until May 28, 2022, without a historic limit on study date. Study characteristics, population characteristics and outcomes reported were extracted and analyzed. RESULTS: Our literature search identified 536 studies that met criteria for inclusion, involving 393,266 patients. Most studies were single center (87.3%), retrospective studies (88.9%) and involved a median of 40 patients (range 6-167,278). Treatments assessed included: surgery (55.2%), conservative (6.2%), halo immobilization (4.9%), or a mixture (33.2%). Median study duration was 84 months (range 3-564 months); the timing of clinical and/or radiological follow-up assessment after injury was reported in 56.7%. There was significant heterogeneity in outcomes used, with 79 different reported outcomes measures. Differences in use were identified between smaller/larger, retro-/prospective and single/multicenter cohorts. Over time, the use of radiological outcomes has declined with greater emphasis on patient-reported outcome measures (PROMs). Studies of conservative management were more likely to detail PROMs and mortality, whereas surgical studies reported Frankel/ASIA grade, radiological fusion, complication rates, duration of hospital stay and re-operation rates more frequently. In studies assessing the elderly population (> 65 years), use of PROMs, mortality, hospital stay and discharge destination were more common, whereas fusion was reported less often. Response rates for outcome assessments were lower in studies assessing elderly patients, and studies using PROMs. CONCLUSIONS: We have classified the various outcome measures used for patients with cervical spine fractures based on the COMET outcome taxonomy. We also described the contexts in which different outcomes are more commonly employed to help guide decision-making when designing future research endeavors.