Does the extended Glasgow Outcome Scale add value to the conventional Glasgow Outcome Scale?

The Glasgow Outcome Scale (GOS) is firmly established as the primary outcome measure for use in Phase III trials of interventions in traumatic brain injury (TBI). However, the GOS has been criticized for its lack of sensitivity to detect small but clinically relevant changes in outcome. The Glasgow Outcome Scale-Extended (GOSE) potentially addresses this criticism, and in this study we estimate the efficiency gain associated with using the GOSE in place of the GOS in ordinal analysis of 6-month outcome. The study uses both simulation and the reanalysis of existing data from two completed TBI studies, one an observational cohort study and the other a randomized controlled trial. As expected, the results show that using an ordinal technique to analyze the GOS gives a substantial gain in efficiency relative to the conventional analysis, which collapses the GOS onto a binary scale (favorable versus unfavorable outcome). We also found that using the GOSE gave a modest but consistent increase in efficiency relative to the GOS in both studies, corresponding to a reduction in the required sample size of the order of 3–5%. We recommend that the GOSE be used in place of the GOS as the primary outcome measure in trials of TBI, with an appropriate ordinal approach being taken to the statistical analysis

Psip1/p52 regulates posterior Hoxa genes through activation of lncRNA Hottip

Long noncoding RNAs (lncRNAs) have been implicated in various biological functions including the regulation of gene expression, however, the functionality of lncRNAs is not clearly understood and conflicting conclusions have often been reached when comparing different methods to investigate them. Moreover, little is known about the upstream regulation of lncRNAs. Here we show that the short isoform (p52) of a transcriptional co-activator—PC4 and SF2 interacting protein (Psip1), which is known to be involved in linking transcription to RNA processing, specifically regulates the expression of the lncRNA Hottip–located at the 5’ end of the Hoxa locus. Using both knockdown and knockout approaches we show that Hottip expression is required for activation of the 5’ Hoxa genes (Hoxa13 and Hoxa10/11) and for retaining Mll1 at the 5’ end of Hoxa. Moreover, we demonstrate that artificially inducing Hottip expression is sufficient to activate the 5’ Hoxa genes and that Hottip RNA binds to the 5’ end of Hoxa. By engineering premature transcription termination, we show that it is the Hottip lncRNA molecule itself, not just Hottip transcription that is required to maintains active expression of posterior Hox genes. Our data show a direct role for a lncRNA molecule in regulating the expression of developmentally-regulated mRNA genes in cis

Body mass index and use and costs of primary care services among women aged 55-79 years in England: a cohort and linked data study.

BACKGROUND: Excess weight is associated with poor health and increased healthcare costs. There are no reliable data describing the association between BMI and the use and costs of primary care services in the United Kingdom. METHODS: Among 69,440 participants in the Million Women Study with primary care records in the Clinical Practice Research Datalink between April 2006 (mean age 64 years) and March 2014, the annual rates and costs of their primary care consultations, prescription medications, and diagnostic and monitoring tests were estimated in relation to their self-reported body mass index (BMI) at recruitment in 1996-2001 (mean age 56 years). Associations of BMI with annual costs were projected to all women in England aged 55-79 years in 2013. RESULTS: Over an average follow-up of 6.0 years, annual rates and mean costs were lowest for women with a BMI of 20 to <22.5 kg/m2 for consultations (7.0 consultations, 99% CI 6.8-7.1; £288, £280-£295) and prescription medications (27.0 prescribed items, 26.0-27.9; £227, £216-£237). Above 20 kg/m2, a 2 kg/m2 higher BMI (a 5 kg change in weight for a woman of average height) was associated with 5.2% (4.8-5.6) and 9.9% (9.2-10.6) higher mean annual consultation and prescription medication costs, respectively. Annual rates and mean costs of diagnostic and monitoring tests were similar for women with different BMIs. Among all women aged 55-79 years in England, excess weight accounted for an estimated 11% (£229 million/£2.2 billion) of all consultation costs and 20% (£384 million/£1.9 billion) of all prescription medication costs, of which 27% were for diabetes drugs, 19% for circulatory system drugs, and 13% for analgesics. CONCLUSIONS: Excess body weight is associated with higher use and costs of primary care services among women in England. Reducing the prevalence of excess weight could improve the health of women and reduce pressures on primary care.Cancer Research UK (grant C570/A16491); Medical Research Council (grant MR/K02700X/1)

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics.

BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable prediction of outcome on admission is of great clinical relevance. We aimed to develop prognostic models with readily available traditional and novel predictors. METHODS AND FINDINGS: Prospectively collected individual patient data were analyzed from 11 studies. We considered predictors available at admission in logistic regression models to predict mortality and unfavorable outcome according to the Glasgow Outcome Scale at 6 mo after injury. Prognostic models were developed in 8,509 patients with severe or moderate TBI, with cross-validation by omission of each of the 11 studies in turn. External validation was on 6,681 patients from the recent Medical Research Council Corticosteroid Randomisation after Significant Head Injury (MRC CRASH) trial. We found that the strongest predictors of outcome were age, motor score, pupillary reactivity, and CT characteristics, including the presence of traumatic subarachnoid hemorrhage. A prognostic model that combined age, motor score, and pupillary reactivity had an area under the receiver operating characteristic curve (AUC) between 0.66 and 0.84 at cross-validation. This performance could be improved (AUC increased by approximately 0.05) by considering CT characteristics, secondary insults (hypotension and hypoxia), and laboratory parameters (glucose and hemoglobin). External validation confirmed that the discriminative ability of the model was adequate (AUC 0.80). Outcomes were systematically worse than predicted, but less so in 1,588 patients who were from high-income countries in the CRASH trial. CONCLUSIONS: Prognostic models using baseline characteristics provide adequate discrimination between patients with good and poor 6 mo outcomes after TBI, especially if CT and laboratory findings are considered in addition to traditional predictors. The model predictions may support clinical practice and research, including the design and analysis of randomized controlled trials

Advancing care for traumatic brain injury : findings from the IMPACT studies and perspectives on future research

Research in Traumatic Brain Injury (TBI) is challenging because of many differences between patients. Advances in basic science have failed to translate into successful clinical treatments and the evidence underpinning guideline recommendations is low. Clinical research has been hampered by lack of standardized data collection, limited multidisciplinary collaboration and by insensitive approaches to classification and efficacy analyses. Multidisciplinary collaborations are now being fostered. Approaches for dealing with heterogeneity have been developed by the IMPACT study group. These can increase statistical power in clinical trials by up to 50% and are also relevant to other heterogeneous neurological diseases, such as stroke and subarachnoid hemorrhage. Rather than trying to limit heterogeneity, we may also be able to exploit it by analyzing differences in treatment and outcome between countries and centers in comparative effectiveness designs. This concept offers an additional research approach with great potential to advance the care in TBI

A simulation study evaluating approaches to the analysis of ordinal outcome data in randomized controlled trials in traumatic brain injury : results from the IMPACT Project

Background Clinical trials in traumatic brain injury have a disappointing track record, with a long history of 'negative' Phase III trials. One contributor to this lack of success is almost certainly the low efficiency of the conventional approach to the analysis, which discards information by dichotomizing an ordinal outcome scale. Purpose Our goal was to evaluate the potential efficiency gains, which can be achieved by using techniques, which extract additional information from ordinal outcome data - the proportional odds model and the sliding dichotomy. In addition, we evaluated the additional efficiency gains, which can be achieved through covariate adjustment. Methods The study was based on simulations, which were built around a database of patient-level data extracted from eight Phase III trials and three observational studies in traumatic brain injury. Two different putative treatment effects were explored, one which followed the proportional odds model, and the other which assumed that the effect of the intervention was to reduce the risk of death without changing the distribution of outcomes within survivors. The results are expressed as efficiency gains, reported as the percentage reduction in sample size that can be used with the ordinal analyses without loss of statistical power relative to the conventional binary analysis. Results The simulation results show substantial efficiency gains. Use of the sliding dichotomy allows sample sizes to be reduced by up to 40% without loss of statistical power. The proportional odds model gives modest additional gains over and above the gains achieved by use of the sliding dichotomy. Limitations As with any simulation study, it is difficult to know how far the findings may be extrapolated beyond the actual situations that were modeled. Conclusions Both ordinal techniques offer substantial efficiency gains relative to the conventional binary analysis. The choice between the two techniques involves subtle value judgments. In the situations examined, the proportional odds model gave efficiency gains over and above the sliding dichotomy, but arguably, the sliding dichotomy is more intuitive and clinically appealing. Clinical Trials 2010; 7: 44-57. http://ctj.sagepub.com

IMPACT recommendations for improving the design and analysis of clinical trials in moderate to severe traumatic brain injury

Clinical trials in traumatic brain injury (TBI) pose complex methodological challenges, largely related to the heterogeneity of the population. The International Mission on Prognosis and Clinical Trial Design in TBI study group has explored approaches for dealing with this heterogeneity with the aim to optimize clinical trials in TBI. Extensive prognostic analyses and simulation studies were conducted on individual patient data from eight trials and three observational studies. Here, we integrate the results of these studies into the International Mission on Prognosis and Clinical Trial Design in TBI recommendations for design and analysis of trials in TBI: • Details of the major baseline prognostic characteristics should be provided in every report on a TBI study; in trials they should be differentiated per treatment group. We also advocate the reporting of the baseline prognostic risk as determined by validated prognostic models. • Inclusion criteria should be as broad as is compatible with the current understanding of the mechanisms of action of the intervention being evaluated. This will maximize recruitment rates and enhance the generalizability of the results. • The statistical analysis should incorporate prespecified covariate adjustment to mitigate the effects of the heterogeneity. • The statistical analysis should use an ordinal approach, based on either sliding dichotomy or proportional odds methodology. Broad inclusion criteria, prespecified covariate adjustment, and an ordinal analysis will promote an efficient trial, yielding gains in statistical efficiency of more than 40%. This corresponds to being able to detect a 7% treatment effect with the same number of patients needed to demonstrate a 10% difference with an unadjusted analysis based on the dichotomized Glasgow outcome scale