Improving Providers’ Survival Estimates and Selection of Prognosis- and Guidelines-Appropriate Radiotherapy Regimens for Patients with Symptomatic Bone Metastases: Development and Evaluation of the BMETS Model and Decision Support Platform

In the management of symptomatic bone metastases, selection of appropriate palliative radiotherapy (RT) regimens should be based on patient-specific characteristics including estimated survival time. Yet, provider predictions of patient survival are notoriously inaccurate. Moreover, available evidence- and consensus-based guidelines do not provide clear criteria for selecting between the range of palliative RT regimens available. In an effort to improve selection of prognosis- and guidelines-appropriate palliative bone treatments, we developed the Bone Metastases Ensemble Trees for Survival (BMETS) model. Built using an institutional database of 397 patients seen in consultation for symptomatic bone metastases, this machine-learning model estimates survival time following RT consultation using 27 prognostic covariates. Cross validations procedures revealed excellent discrimination for survival, and the BMETS outperformed validated, simpler statistical models, justifying its use in this population. To better characterize a component of decisional uncertainty faced by providers, we next sought to identify the prevalence of “complicated” symptomatic bone metastases across a breadth of possible operational definitions. Our efforts identified up to 96 possible definitions of “complicated” bone metastases, present in up to 67.1% of patients in our database. Given that such “complicated” lesions may have been excluded from clinical trials in this setting, these data highlight the difficulty faced by providers when attempting to select appropriate RT regimens using inadequately defined selection criteria. Informed by these insights, we developed the BMETS Decision Support Platform (BMETS-DSP). This provider-facing, web-based tool was created to (1) collect relevant patient-specific data, (2) display an individualized predicted survival curve as per the BMETS model, and (3) provide case-specific, evidence-based recommendations for treatment of symptomatic bone metastases. We then conducted a pilot assessment of the clinical utility of the BMETS-DSP. In this preliminary assessment, the BMETS-DSP significantly improved physician accuracy in estimating survival and increased prognostic confidence, likelihood of sharing prognosis, and use of prognosis-appropriate RT regimens in the care of case patients. Collectively, this research provides early justification for the use of a machine-learning survival model and resultant decisions support platform to guide individualized selection of palliative RT regimens for symptomatic bone metastases. These data support a multi-institutional, randomized trial of the BMETS-DSP

Blending human and artificial intelligence to support autistic children’s social communication skills

This paper examines the educational efficacy of a learning environment in which children diagnosed with Autism Spectrum Conditions (ASC) engage in social interactions with an artificially intelligent (AI) virtual agent and where a human practitioner acts in support of the interactions. A multi-site intervention study in schools across the UK was conducted with 29 children with ASC and learning difficulties, aged 4-14 years old. For reasons related to data completeness and amount of exposure to the AI environment, data for 15 children was included in the analysis. The analysis revealed a significant increase in the proportion of social responses made by ASC children to human practitioners. The number of initiations made to human practitioners and to the virtual agent by the ASC children also increased numerically over the course of the sessions. However, due to large individual differences within the ASC group, this did not reach significance. Although no evidence of transfer to the real-world post-test was shown, anecdotal evidence of classroom transfer was reported. The work presented in this paper offers an important contribution to the growing body of research in the context of AI technology design and use for autism intervention in real school contexts. Specifically, the work highlights key methodological challenges and opportunities in this area by leveraging interdisciplinary insights in a way that (i) bridges between educational interventions and intelligent technology design practices, (ii) considers the design of technology as well as the design of its use (context and procedures) on par with one another, and (iii) includes design contributions from different stakeholders, including children with and without ASC diagnosis, educational practitioners and researchers

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

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Postoperative continuous positive airway pressure to prevent pneumonia, re-intubation, and death after major abdominal surgery (PRISM): a multicentre, open-label, randomised, phase 3 trial

Background: Respiratory complications are an important cause of postoperative morbidity. We aimed to investigate whether continuous positive airway pressure (CPAP) administered immediately after major abdominal surgery could prevent postoperative morbidity. Methods: PRISM was an open-label, randomised, phase 3 trial done at 70 hospitals across six countries. Patients aged 50 years or older who were undergoing elective major open abdominal surgery were randomly assigned (1:1) to receive CPAP within 4 h of the end of surgery or usual postoperative care. Patients were randomly assigned using a computer-generated minimisation algorithm with inbuilt concealment. The primary outcome was a composite of pneumonia, endotracheal re-intubation, or death within 30 days after randomisation, assessed in the intention-to-treat population. Safety was assessed in all patients who received CPAP. The trial is registered with the ISRCTN registry, ISRCTN56012545. Findings: Between Feb 8, 2016, and Nov 11, 2019, 4806 patients were randomly assigned (2405 to the CPAP group and 2401 to the usual care group), of whom 4793 were included in the primary analysis (2396 in the CPAP group and 2397 in the usual care group). 195 (8\ub71%) of 2396 patients in the CPAP group and 197 (8\ub72%) of 2397 patients in the usual care group met the composite primary outcome (adjusted odds ratio 1\ub701 [95% CI 0\ub781-1\ub724]; p=0\ub795). 200 (8\ub79%) of 2241 patients in the CPAP group had adverse events. The most common adverse events were claustrophobia (78 [3\ub75%] of 2241 patients), oronasal dryness (43 [1\ub79%]), excessive air leak (36 [1\ub76%]), vomiting (26 [1\ub72%]), and pain (24 [1\ub71%]). There were two serious adverse events: one patient had significant hearing loss and one patient had obstruction of their venous catheter caused by a CPAP hood, which resulted in transient haemodynamic instability. Interpretation: In this large clinical effectiveness trial, CPAP did not reduce the incidence of pneumonia, endotracheal re-intubation, or death after major abdominal surgery. Although CPAP has an important role in the treatment of respiratory failure after surgery, routine use of prophylactic post-operative CPAP is not recommended