Adaptive platform trials using multi-arm, multi-stage protocols: getting fast answers in pandemic settings [version 2; peer review: 2 approved]

Global health pandemics, such as coronavirus disease 2019 (COVID19), require efficient and well-conducted trials to determine effective interventions, such as treatments and vaccinations. Early work focused on rapid sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), subsequent in-vitro and in-silico work, along with greater understanding of the different clinical phases of the infection, have helped identify a catalogue of potential therapeutic agents requiring assessment. In a pandemic, there is a need to quickly identify efficacious treatments, and reject those that are non-beneficial or even harmful, using randomised clinical trials. Whilst each potential treatment could be investigated across multiple, separate, competing two-arm trials, this is a very inefficient process. Despite the very large numbers of interventional trials for COVID-19, the vast majority have not used efficient trial designs. Well conducted, adaptive platform trials utilising a multi-arm multistage (MAMS) approach provide a solution to overcome limitations of traditional designs. The multi-arm element allows multiple different treatments to be investigated simultaneously against a shared, standard-of-care control arm. The multi-stage element uses interim analyses to assess accumulating data from the trial and ensure that only treatments showing promise continue to recruitment during the next stage of the trial. The ability to test many treatments at once and drop insufficiently active interventions significantly speeds up the rate at which answers can be achieved. This article provides an overview of the benefits of MAMS designs and successes of trials, which have used this approach to COVID-19. We also discuss international collaboration between trial teams, including prospective agreement to synthesise trial results, and identify the most effective interventions. We believe that international collaboration will help provide faster answers for patients, clinicians, and health care systems around the world, including for each further wave of COVID-19, and enable preparedness for future global health pandemics

Adaptive platform trials using multi-arm, multi-stage protocols: getting fast answers in pandemic settings [version 1; peer review: 2 approved]

Global health pandemics, such as coronavirus disease 2019 (COVID-19), require efficient and well-conducted trials to determine effective interventions, such as treatments and vaccinations. Early work focused on rapid sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), subsequent in-vitro and in-silico work, along with greater understanding of the different clinical phases of the infection, have helped identify a catalogue of potential therapeutic agents requiring assessment. In a pandemic, there is a need to quickly identify efficacious treatments, and reject those that are non-beneficial or even harmful, using randomised clinical trials. Whilst each potential treatment could be investigated across multiple, separate, competing two-arm trials, this is a very inefficient process. Despite the very large numbers of interventional trials for COVID-19, the vast majority have not used efficient trial designs. Well conducted, adaptive platform trials utilising a multi-arm multi-stage (MAMS) approach provide a solution to overcome limitations of traditional designs. The multi-arm element allows multiple different treatments to be investigated simultaneously against a shared, standard-of-care control arm. The multi-stage element uses interim analyses to assess accumulating data from the trial and ensure that only treatments showing promise continue to recruitment during the next stage of the trial. The ability to test many treatments at once and drop insufficiently active interventions significantly speeds up the rate at which answers can be achieved. This article provides an overview of the benefits of MAMS designs and successes of trials, which have used this approach to COVID-19. We also discuss international collaboration between trial teams, including prospective agreement to synthesise trial results, and identify the most effective interventions. We believe that international collaboration will help provide faster answers for patients, clinicians, and health care systems around the world, including for future waves of COVID-19, and enable preparedness for future global health pandemics

A compact high field magnet system for medical applications

High magnetic field gradients can be used for various medical applications including magnetically targeted drug delivery, magnetic cell separation and controlled local heating for the ablation of tumours. These processes involve the use of biocompatible magnetic nanoparticles directed to the area of interest by the use of a field gradient. The force on the nanoparticle is proportional to the field gradient product, so high fields are required for effective delivery. Bulk superconductors are an attractive solution for both drug delivery and the next generation of low cost magnetic resonance imaging magnets. In particular, MgB2 is seen as an attractive material due to its low cost, simple processing and relatively high transition temperature (∼39 K). This paper describes the development of a breadboard compact delivery system suitable for medical applications. This incorporates a cryogenic stage which utilises long life space-proven technology and state of the art ex-situ processed MgB 2 pellets.EP/P026427/1

In-hospital mortality is associated with inflammatory response in NAFLD patients admitted for COVID-19

Background & aims Although metabolic risk factors are associated with more severe COVID-19, there is little evidence on outcomes in patients with non-alcoholic fatty liver disease (NAFLD). We here describe the clinical characteristics and outcomes of NAFLD patients in a cohort hospitalised for COVID-19. Methods This study included all consecutive patients admitted for COVID-19 between February and April 2020 at Imperial College Healthcare NHS Trust, with either imaging of the liver available dated within one year from the admission or a known diagnosis of NAFLD. Clinical data and early weaning score (EWS) were recorded. NAFLD diagnosis was based on imaging or past medical history and patients were stratified for Fibrosis-4 (FIB-4) index. Clinical endpoints were admission to intensive care unit (ICU)and in-hospital mortality. Results 561 patients were admitted. Overall, 193 patients were included in the study. Fifty nine patients (30%) died, 9 (5%) were still in hospital, and 125 (65%) were discharged. The NAFLD cohort (n = 61) was significantly younger (60 vs 70.5 years, p = 0.046) at presentation compared to the non-NAFLD (n = 132). NAFLD diagnosis was not associated with adverse outcomes. However, the NAFLD group had higher C reactive protein (CRP) (107 vs 91.2 mg/L, p = 0.05) compared to non-NAFLD(n = 132). Among NAFLD patients, male gender (p = 0.01), ferritin (p = 0.003) and EWS (p = 0.047) were associated with in-hospital mortality, while the presence of intermediate/high risk FIB-4 or liver cirrhosis was not. Conclusion The presence of NAFLD per se was not associated with worse outcomes in patients hospitalised for COVID-19. Though NAFLD patients were younger on admission, disease stage was not associated with clinical outcomes. Yet, mortality was associated with gender and a pronounced inflammatory response in the NAFLD group

Quantum Tricritical Points in NbFe2_2

Quantum critical points (QCPs) emerge when a 2nd order phase transition is suppressed to zero temperature. In metals the quantum fluctuations at such a QCP can give rise to new phases including unconventional superconductivity. Whereas antiferromagnetic QCPs have been studied in considerable detail ferromagnetic (FM) QCPs are much harder to access. In almost all metals FM QCPs are avoided through either a change to 1st order transitions or through an intervening spin-density-wave (SDW) phase. Here, we study the prototype of the second case, NbFe$_2$. We demonstrate that the phase diagram can be modelled using a two-order-parameter theory in which the putative FM QCP is buried within a SDW phase. We establish the presence of quantum tricritical points (QTCPs) at which both the uniform and finite $q$ susceptibility diverge. The universal nature of our model suggests that such QTCPs arise naturally from the interplay between SDW and FM order and exist generally near a buried FM QCP of this type. Our results promote NbFe$_2$ as the first example of a QTCP, which has been proposed as a key concept in a range of narrow-band metals, including the prominent heavy-fermion compound YbRh$_2$Si$_2$.Comment: 21 pages including S

Prediction of chronic disability in work-related musculoskeletal disorders: a prospective, population-based study

BACKGROUND: Disability associated with work-related musculoskeletal disorders is an increasingly serious societal problem. Although most injured workers return quickly to work, a substantial number do not. The costs of chronic disability to the injured worker, his or her family, employers, and society are enormous. A means of accurate early identification of injured workers at risk for chronic disability could enable these individuals to be targeted for early intervention to promote return to work and normal functioning. The purpose of this study is to develop statistical models that accurately predict chronic work disability from data obtained from administrative databases and worker interviews soon after a work injury. Based on these models, we will develop a brief instrument that could be administered in medical or workers' compensation settings to screen injured workers for chronic disability risk. METHODS: This is a population-based, prospective study. The study population consists of workers who file claims for work-related back injuries or carpal tunnel syndrome (CTS) in Washington State. The Washington State Department of Labor and Industries claims database is reviewed weekly to identify workers with new claims for work-related back injuries and CTS, and these workers are telephoned and invited to participate. Workers who enroll complete a computer-assisted telephone interview at baseline and one year later. The baseline interview assesses sociodemographic, employment-related, biomedical/health care, legal, and psychosocial risk factors. The follow-up interview assesses pain, disability, and work status. The primary outcome is duration of work disability over the year after claim submission, as assessed by administrative data. Secondary outcomes include work disability status at one year, as assessed by both self-report and work disability compensation status (administrative records). A sample size of 1,800 workers with back injuries and 1,200 with CTS will provide adequate statistical power (0.96 for low back and 0.85 for CTS) to predict disability with an alpha of .05 (two-sided) and a hazard ratio of 1.2. Proportional hazards regression models will be constructed to determine the best combination of predictors of work disability duration at one year. Regression models will also be developed for the secondary outcomes

Numerical analysis of the resistance behavior of an electrostatically-induced graphene double junction

We present a numerical approach that we have developed in order to reproduce and explain the resistance behavior recently observed, as a function of the backgate voltage and of the position of a biased scanning probe, in a graphene flake in which a double p-n junction has been electrostatically induced. A simplified electrostatic model has been adopted to simulate the effect of gate voltages on the potential landscape, assuming for it a slow variation in space and using a simple capacitive model for the coupling between the electrodes and the graphene sheet. The transport analysis has then been performed with a solution of the Dirac equation in the reciprocal space coupled with a recursive scattering matrix approach. The efficiency of the adopted numerical procedure has allowed us to explore a wide range of possible potential landscapes and bias points, with the result of achieving a good agreement with available experimental data

Patients’ Perceptions of Memory Functioning Before and After Surgical Intervention to Treat Medically Refractory Epilepsy.

Purpose:One risk associated with epilepsy surgery is memory loss, but perhaps more important is how patients perceive changes in their memories. This longitudinal study evaluated changes in memory self-reports and investigated how self-reports relate to changes on objective memory measures in temporal or extratemporal epilepsy patients who underwent surgery. Methods: Objective memory (Wechsler Memory Scale–Revised) and subjective memory self-reports (Memory Assessment Clinics Self-Rating Scale) were individually assessed for 136 patients ∼6 months before and 6 months after surgery. A measure of depressive affect (Beck Depression Inventory–2nd Edition) was used to control variance attributable to emotional distress. Results: Despite a lack of significant correlational relationships between objective and subjective memory for the entire sample, significant correlations between objective memory scores and self-reports did emerge for a subset of patients who evidenced memory decline. Differences also were found in the subjective memory ratings of temporal lobe versus extratemporal patients. Temporal lobe patients rated their memories more negatively than did extratemporal patients and were more likely to report significant improvements in their memory after surgery. Conclusions: In general, patients were not accurate when rating their memories compared to other adults. However, patients with significant declines in their memories were sensitive to actual changes in their memories over time relative to their own personal baselines

Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe [version 1; peer review: 2 approved, 1 approved with reservations]

Two billion people are infected with Mycobacterium tuberculosis, leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, Mykrobe predictor, which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations. Here we present a new tool, Mykrobe, which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates. Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that Mykrobe gives concordant results with nanopore data. We measure the ability of Mykrobe-based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools

cExternal beam radiation results in minimal changes in post void residual urine volumes during the treatment of clinically localized prostate cancer

<p>Abstract</p> <p>Background</p> <p>To evaluate the impact of external beam radiation therapy (XRT) on weekly ultrasound determined post-void residual (PVR) urine volumes in patients with prostate cancer.</p> <p>Methods</p> <p>125 patients received XRT for clinically localized prostate cancer. XRT was delivered to the prostate only (n = 66) or if the risk of lymph node involvement was greater than 10% to the whole pelvis followed by a prostate boost (n = 59). All patients were irradiated in the prone position in a custom hip-fix mobilization device with an empty bladder and rectum. PVR was obtained at baseline and weekly. Multiple clinical and treatment parameters were evaluated as predictors for weekly PVR changes.</p> <p>Results</p> <p>The mean patient age was 73.9 years with a mean pre-treatment prostate volume of 53.3 cc, a mean IPSS of 11.3 and a mean baseline PVR of 57.6 cc. During treatment, PVR decreased from baseline in both cohorts with the absolute difference within the limits of accuracy of the bladder scanner. Alpha-blockers did not predict for a lower PVR during treatment. There was no significant difference in mean PVR urine volumes or differences from baseline in either the prostate only or pelvic radiation groups (p = 0.664 and p = 0.458, respectively). Patients with a larger baseline PVR (>40 cc) had a greater reduction in PVR, although the greatest reduction was seen between weeks one and three. Patients with a small PVR (<40 cc) had no demonstrable change throughout treatment.</p> <p>Conclusion</p> <p>Prostate XRT results in clinically insignificant changes in weekly PVR volumes, suggesting that radiation induced bladder irritation does not substantially influence bladder residual urine volumes.</p