How important is randomisation in a stepped wedge trial?

In cluster randomised trials, randomisation increases internal study validity. If enough clusters are randomised, an unadjusted analysis should be unbiased. If a smaller number of clusters are included, stratified or matched randomisation can increase comparability between trial arms. In addition, an adjusted analysis may be required; nevertheless, randomisation removes the possibility for systematically biased allocation and increases transparency. In stepped wedge trials, clusters are randomised to receive an intervention at different start times ('steps'), and all clusters eventually receive it. In a recent study protocol for a 'modified stepped wedge trial', the investigators considered randomisation of the clusters (hospital wards), but decided against it for ethical and logistical reasons, and under the assumption that it would not add much to the rigour of the evaluation. We show that the benefits of randomisation for cluster randomised trials also apply to stepped wedge trials. The biggest additional issue for stepped wedge trials in relation to parallel cluster randomised trials is the need to control for secular trends in the outcome. Analysis of stepped wedge trials can in theory be based on 'horizontal' or 'vertical' comparisons. Horizontal comparisons are based on measurements taken before and after the intervention is introduced in each cluster, and are unbiased if there are no secular trends. Vertical comparisons are based on outcome measurements from clusters that have switched to the intervention condition and those from clusters that have yet to switch, and are unbiased under randomisation since at any time point, which clusters are in intervention and control conditions will have been determined at random. Secular outcome trends are a possibility in many settings. Many stepped wedge trials are analysed with a mixed model, including a random effect for cluster and fixed effects for time period to account for secular trends, thereby combining both vertical and horizontal comparisons of intervention and control clusters. The importance of randomisation in a stepped wedge trial is that the effects of time can be estimated from the data, and bias from secular trends that would otherwise arise can be controlled for, provided the trends are correctly specified in the model

Bias and inference from misspecified mixed-effect models in stepped wedge trial analysis.

Many stepped wedge trials (SWTs) are analysed by using a mixed-effect model with a random intercept and fixed effects for the intervention and time periods (referred to here as the standard model). However, it is not known whether this model is robust to misspecification. We simulated SWTs with three groups of clusters and two time periods; one group received the intervention during the first period and two groups in the second period. We simulated period and intervention effects that were either common-to-all or varied-between clusters. Data were analysed with the standard model or with additional random effects for period effect or intervention effect. In a second simulation study, we explored the weight given to within-cluster comparisons by simulating a larger intervention effect in the group of the trial that experienced both the control and intervention conditions and applying the three analysis models described previously. Across 500 simulations, we computed bias and confidence interval coverage of the estimated intervention effect. We found up to 50% bias in intervention effect estimates when period or intervention effects varied between clusters and were treated as fixed effects in the analysis. All misspecified models showed undercoverage of 95% confidence intervals, particularly the standard model. A large weight was given to within-cluster comparisons in the standard model. In the SWTs simulated here, mixed-effect models were highly sensitive to departures from the model assumptions, which can be explained by the high dependence on within-cluster comparisons. Trialists should consider including a random effect for time period in their SWT analysis model. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd

Efam: an expanded, metaproteome-supported HMM profile database of viral protein families

Motivation: Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Results: Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from 'conservative' to 'eXtremely Conservative' resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ∼24% on average (up to ∼42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem

Associations between HIV stigma and health-related quality-of-life among people living with HIV: cross-sectional analysis of data from HPTN 071 (PopART)

People living with HIV (PLHIV) report lower health-related quality-of-life (HRQoL) than HIV-negative people. HIV stigma may contribute to this. We explored the association between HIV stigma and HRQoL among PLHIV. We used cross-sectional data from 3991 randomly selected PLHIV who were surveyed in 2017–2018 for HPTN 071 (PopART), a cluster randomised trial in Zambia and South Africa. Participants were 18–44 years, had laboratory-confirmed HIV infection, and knew their status. HRQoL was measured using the EuroQol-5-dimensions-5-levels (EQ-5D-5L) questionnaire. Stigma outcomes included: internalised stigma, stigma experienced in the community, and stigma experienced in healthcare settings. Associations were examined using logistic regression. Participants who had experienced community stigma (n = 693/3991) had higher odds of reporting problems in at least one HRQoL domain, compared to those who had not (adjusted odds ratio, aOR: 1.51, 95% confidence interval, 95% Cl: 1.16–1.98, p = 0.002). Having experienced internalised stigma was also associated with reporting problems in at least one HRQoL domain (n = 552/3991, aOR: 1.98, 95% CI: 1.54–2.54, p < 0.001). However, having experienced stigma in a healthcare setting was less common (n = 158/3991) and not associated with HRQoL (aOR: 1.04, 95% CI: 0.68–1.58, p = 0.850). A stronger focus on interventions for internalised stigma and stigma experienced in the community is required

Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders

Genome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3′ untranslated regions (3′UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3′UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD

Symptom-based stratification of patients with primary Sjögren's syndrome: multi-dimensional characterisation of international observational cohorts and reanalyses of randomised clinical trials

Background Heterogeneity is a major obstacle to developing effective treatments for patients with primary Sjögren's syndrome. We aimed to develop a robust method for stratification, exploiting heterogeneity in patient-reported symptoms, and to relate these differences to pathobiology and therapeutic response. Methods We did hierarchical cluster analysis using five common symptoms associated with primary Sjögren's syndrome (pain, fatigue, dryness, anxiety, and depression), followed by multinomial logistic regression to identify subgroups in the UK Primary Sjögren's Syndrome Registry (UKPSSR). We assessed clinical and biological differences between these subgroups, including transcriptional differences in peripheral blood. Patients from two independent validation cohorts in Norway and France were used to confirm patient stratification. Data from two phase 3 clinical trials were similarly stratified to assess the differences between subgroups in treatment response to hydroxychloroquine and rituximab. Findings In the UKPSSR cohort (n=608), we identified four subgroups: Low symptom burden (LSB), high symptom burden (HSB), dryness dominant with fatigue (DDF), and pain dominant with fatigue (PDF). Significant differences in peripheral blood lymphocyte counts, anti-SSA and anti-SSB antibody positivity, as well as serum IgG, κ-free light chain, β2-microglobulin, and CXCL13 concentrations were observed between these subgroups, along with differentially expressed transcriptomic modules in peripheral blood. Similar findings were observed in the independent validation cohorts (n=396). Reanalysis of trial data stratifying patients into these subgroups suggested a treatment effect with hydroxychloroquine in the HSB subgroup and with rituximab in the DDF subgroup compared with placebo. Interpretation Stratification on the basis of patient-reported symptoms of patients with primary Sjögren's syndrome revealed distinct pathobiological endotypes with distinct responses to immunomodulatory treatments. Our data have important implications for clinical management, trial design, and therapeutic development. Similar stratification approaches might be useful for patients with other chronic immune-mediated diseases. Funding UK Medical Research Council, British Sjogren's Syndrome Association, French Ministry of Health, Arthritis Research UK, Foundation for Research in Rheumatology

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Spatial access priority mapping (SAPM) with fishers : a quantitative GIS method for participatory planning

Spatial management tools, such as marine spatial planning and marine protected areas, are playing an increasingly important role in attempts to improve marine management and accommodate conflicting needs. Robust data are needed to inform decisions among different planning options, and early inclusion of stakeholder involvement is widely regarded as vital for success. One of the biggest stakeholder groups, and the most likely to be adversely impacted by spatial restrictions, is the fishing community. In order to take their priorities into account, planners need to understand spatial variation in their perceived value of the sea. Here a readily accessible, novel method for quantitatively mapping fishers’ spatial access priorities is presented. Spatial access priority mapping, or SAPM, uses only basic functions of standard spreadsheet and GIS software. Unlike the use of remote-sensing data, SAPM actively engages fishers in participatory mapping, documenting rather than inferring their priorities. By so doing, SAPM also facilitates the gathering of other useful data, such as local ecological knowledge. The method was tested and validated in Northern Ireland, where over 100 fishers participated in a semi-structured questionnaire and mapping exercise. The response rate was excellent, 97%, demonstrating fishers’ willingness to be involved. The resultant maps are easily accessible and instantly informative, providing a very clear visual indication of which areas are most important for the fishers. The maps also provide quantitative data, which can be used to analyse the relative impact of different management options on the fishing industry and can be incorporated into planning software, such as MARXAN, to ensure that conservation goals can be met at minimum negative impact to the industry. This research shows how spatial access priority mapping can facilitate the early engagement of fishers and the ready incorporation of their priorities into the decision-making process in a transparent, quantitative way

Challenges and opportunities for conducting a vaccine trial during the COVID-19 pandemic in the United Kingdom

The COVID-19 pandemic has resulted in unprecedented challenges for healthcare systems worldwide. It has also stimulated research in a wide range of areas including rapid diagnostics, novel therapeutics, use of technology to track patients and vaccine development. Here, we describe our experience of rapidly setting up and delivering a novel COVID-19 vaccine trial, using clinical and research staff and facilities in three National Health Service Trusts in Cambridgeshire, United Kingdom. We encountered and overcame a number of challenges including differences in organisational structures, research facilities available, staff experience and skills, information technology and communications infrastructure, and research training and assessment procedures. We overcame these by setting up a project team that included key members from all three organisations that met at least daily by teleconference. This group together worked to identify the best practices and procedures and to harmonise and cascade these to the wider trial team. This enabled us to set up the trial within 25 days and to recruit and vaccinate the participants within a further 23 days. The lessons learned from our experiences could be used to inform the conduct of clinical trials during a future infectious disease pandemic or public health emergency