Efficient designs for three-sequence stepped wedge trials with continuous recruitment.

BACKGROUND/AIMS: The standard approach to designing stepped wedge trials that recruit participants in a continuous stream is to divide time into periods of equal length. But the choice of design in such cases is infinitely more flexible: each cluster could cross from the control to the intervention at any point on the continuous time-scale. We consider the case of a stepped wedge design with clusters randomised to just three sequences (designs with small numbers of sequences may be preferred for their simplicity and practicality) and investigate the choice of design that minimises the variance of the treatment effect estimator under different assumptions about the intra-cluster correlation. METHODS: We make some simplifying assumptions in order to calculate the variance: in particular that we recruit the same number of participants, m, from each cluster over the course of the trial, and that participants present at regularly spaced intervals. We consider an intra-cluster correlation that decays exponentially with separation in time between the presentation of two individuals from the same cluster, from a value of ρ for two individuals who present at the same time, to a value of ρτ for individuals presenting at the start and end of the trial recruitment interval. We restrict attention to three-sequence designs with centrosymmetry - the property that if we reverse time and swap the intervention and control conditions then the design looks the same. We obtain an expression for the variance of the treatment effect estimator adjusted for effects of time, using methods for generalised least squares estimation, and we evaluate this expression numerically for different designs, and for different parameter values. RESULTS: There is a two-dimensional space of possible three-sequence, centrosymmetric stepped wedge designs with continuous recruitment. The variance of the treatment effect estimator for given ρ and τ can be plotted as a contour map over this space. The shape of this variance surface depends on τ and on the parameter mρ/(1-ρ), but typically indicates a broad, flat region of close-to-optimal designs. The 'standard' design with equally spaced periods and 1:1:1 allocation rarely performs well, however. CONCLUSIONS: In many different settings, a relatively simple design can be found (e.g. one based on simple fractions) that offers close-to-optimal efficiency in that setting. There may also be designs that are robustly efficient over a wide range of settings. Contour maps of the kind we illustrate can help guide this choice. If efficiency is offered as one of the justifications for using a stepped wedge design, then it is worth designing with optimal efficiency in mind.

Tailored psychological intervention for anxiety or depression in COPD (TANDEM): a randomised controlled trial.

BACKGROUND: The TANDEM multicentre, pragmatic, randomised controlled trial evaluated whether a tailored psychological intervention based on a cognitive behavioural approach for people with COPD and symptoms of anxiety and/or depression improved anxiety or depression compared with usual care (control). METHODS: People with COPD and moderate to very severe airways obstruction and Hospital Anxiety and Depression Scale subscale scores indicating mild to moderate anxiety (HADS-A) and/or depression (HADS-D) were randomised 1.25:1 (242 intervention and 181 control). Respiratory health professionals delivered the intervention face-to-face over 6-8 weeks. Co-primary outcomes were HADS-A and HADS-D measured 6 months post-randomisation. Secondary outcomes at 6 and 12 months included: HADS-A and HADS-D (12 months), Beck Depression Inventory II, Beck Anxiety Inventory, St George's Respiratory Questionnaire, social engagement, the EuroQol instrument five-level version (EQ-5D-5L), smoking status, completion of pulmonary rehabilitation, and health and social care resource use. RESULTS: The intervention did not improve anxiety (HADS-A mean difference -0.60, 95% CI -1.40-0.21) or depression (HADS-D mean difference -0.66, 95% CI -1.39-0.07) at 6 months. The intervention did not improve any secondary outcomes at either time-point, nor did it influence completion of pulmonary rehabilitation or healthcare resource use. Deaths in the intervention arm (13/242; 5%) exceeded those in the control arm (3/181; 2%), but none were associated with the intervention. Health economic analysis found the intervention highly unlikely to be cost-effective. CONCLUSION: This trial has shown, beyond reasonable doubt, that this cognitive behavioural intervention delivered by trained and supervised respiratory health professionals does not improve psychological comorbidity in people with advanced COPD and depression or anxiety.

The batched stepped wedge design: A design robust to delays in cluster recruitment.

Stepped wedge designs are an increasingly popular variant of longitudinal cluster randomized trial designs, and roll out interventions across clusters in a randomized, but step-wise fashion. In the standard stepped wedge design, assumptions regarding the effect of time on outcomes may require that all clusters start and end trial participation at the same time. This would require ethics approvals and data collection procedures to be in place in all clusters before a stepped wedge trial can start in any cluster. Hence, although stepped wedge designs are useful for testing the impacts of many cluster-based interventions on outcomes, there can be lengthy delays before a trial can commence. In this article, we introduce "batched" stepped wedge designs. Batched stepped wedge designs allow clusters to commence the study in batches, instead of all at once, allowing for staggered cluster recruitment. Like the stepped wedge, the batched stepped wedge rolls out the intervention to all clusters in a randomized and step-wise fashion: a series of self-contained stepped wedge designs. Provided that separate period effects are included for each batch, software for standard stepped wedge sample size calculations can be used. With this time parameterization, in many situations including when linear models are assumed, sample size calculations reduce to the setting of a single stepped wedge design with multiple clusters per sequence. In these situations, sample size calculations will not depend on the delays between the commencement of batches. Hence, the power of batched stepped wedge designs is robust to unexpected delays between batches.

Clinical Impact of Rectal Hyposensitivity: A Cross-Sectional Study of 2,876 Patients With Refractory Functional Constipation.

INTRODUCTION: Normal bowel function requires intact sensory pathways. Diminished rectal sensation (rectal hyposensitivity [RH]) is associated with constipation, although its clinical importance remains unclear. METHODS: Consecutive patients (aged 18-80) attending a tertiary center (2004-2016) for investigation of refractory functional constipation (Rome IV core criteria defined, applied post hoc) were included. Patients completed a clinical symptom questionnaire and underwent anorectal physiologic investigations, including rectal sensory testing (balloon distension) to determine 3 well-established sensory thresholds. Multivariate regression analyses were performed to evaluate associations between RH, symptomology, and allied physiologic investigations. RESULTS: Of 2,876 patients meeting inclusion criteria, 722 (25%) had RH based on ≥1 elevated sensory thresholds (0: n = 2,154 [74.9%]; 1: n = 327 [11.4%]; 2: n = 209 [7.3%]; and 3: n = 186 [6.5%]). A linear relationship existed between increasing number of elevated sensory thresholds and constipation severity (Cleveland Clinic constipation score: mean difference per threshold [95% confidence interval] 0.69 [0.48-0.90]; P < 0.001). Several symptoms were significantly (P < 0.05) associated with RH including: infrequent defecation (odds ratio 1.29 [1.17-1.42]), painful evacuation (1.15 [1.05-1.27]), prolonged toileting (1.14 [1.05-1.24]), and digitation or enema use (1.18 [1.08-1.30]). On defecography, a "functional" evacuation disorder was also associated with RH (1.37 [1.25-1.50], P < 0.001), as was megarectum (2.52 [2.08-3.05], P < 0.001). DISCUSSION: RH occurs in 25% of patients with refractory functional constipation. Increased number of elevated sensory thresholds is associated with more severe constipation phenotype. These data, in the largest study to date, provide for the first time evidence to show that RH is a major pathophysiologic mechanism in constipation, with recognized clinical impact (http://links.lww.com/AJG/B765).(Equation is included in full-text article.).

Optimal design of cluster randomized trials allowing unequal allocation of clusters and unequal cluster size between arms.

There are sometimes cost, scientific, or logistical reasons to allocate individuals unequally in an individually randomized trial. In cluster randomized trials we can allocate clusters unequally and/or allow different cluster size between trial arms. We consider parallel group designs with a continuous outcome, and optimal designs that require the smallest number of individuals to be measured given the number of clusters. Previous authors have derived the optimal allocation ratio for clusters under different variance and/or intracluster correlations (ICCs) between arms, allowing different but prespecified cluster sizes by arm. We derive closed-form expressions to identify the optimal proportions of clusters and of individuals measured for each arm, thereby defining optimal cluster sizes, when cluster size can be chosen freely. When ICCs differ between arms but the variance is equal, the optimal design allocates more than half the clusters to the arm with the higher ICC, but (typically only slightly) less than half the individuals and hence a smaller cluster size. We also describe optimal design under constraints on the number of clusters or cluster size in one or both arms. This methodology allows trialists to consider a range for the number of clusters in the trial and for each to identify the optimal design. Except if there is clear prior evidence for the ICC and variance by arm, a range of values will need to be considered. Researchers should choose a design with adequate power across the range, while also keeping enough clusters in each arm to permit the intended analysis method.

Independence estimators for re-randomisation trials in multi-episode settings: a simulation study.

BACKGROUND: Re-randomisation trials involve re-enrolling and re-randomising patients for each new treatment episode they experience. They are often used when interest lies in the average effect of an intervention across all the episodes for which it would be used in practice. Re-randomisation trials are often analysed using independence estimators, where a working independence correlation structure is used. However, research into independence estimators in the context of re-randomisation has been limited. METHODS: We performed a simulation study to evaluate the use of independence estimators in re-randomisation trials. We focussed on a continuous outcome, and the setting where treatment allocation does not affect occurrence of subsequent episodes. We evaluated different treatment effect mechanisms (e.g. by allowing the treatment effect to vary across episodes, or to become less effective on re-use, etc), and different non-enrolment mechanisms (e.g. where patients who experience a poor outcome are less likely to re-enrol for their second episode). We evaluated four different independence estimators, each corresponding to a different estimand (per-episode and per-patient approaches, and added-benefit and policy-benefit approaches). RESULTS: We found that independence estimators were unbiased for the per-episode added-benefit estimand in all scenarios we considered. We found independence estimators targeting other estimands (per-patient or policy-benefit) were unbiased, except when there was differential non-enrolment between treatment groups (i.e. when different types of patients from each treatment group decide to re-enrol for subsequent episodes). We found the use of robust standard errors provided close to nominal coverage in all settings where the estimator was unbiased. CONCLUSIONS: Careful choice of estimand can ensure re-randomisation trials are addressing clinically relevant questions. Independence estimators are a useful approach, and should be considered as the default estimator until the statistical properties of alternative estimators are thoroughly evaluated.

Optimal design of cluster randomised trials with continuous recruitment and prospective baseline period.

BACKGROUND: Cluster randomised trials, like individually randomised trials, may benefit from a baseline period of data collection. We consider trials in which clusters prospectively recruit or identify participants as a continuous process over a given calendar period, and ask whether and for how long investigators should collect baseline data as part of the trial, in order to maximise precision. METHODS: We show how to calculate and plot the variance of the treatment effect estimator for different lengths of baseline period in a range of scenarios, and offer general advice. RESULTS: In some circumstances it is optimal not to include a baseline, while in others there is an optimal duration for the baseline. All other things being equal, the circumstances where it is preferable not to include a baseline period are those with a smaller recruitment rate, smaller intracluster correlation, greater decay in the intracluster correlation over time, or wider transition period between recruitment under control and intervention conditions. CONCLUSION: The variance of the treatment effect estimator can be calculated numerically, and plotted against the duration of baseline to inform design. It would be of interest to extend these investigations to cluster randomised trial designs with more than two randomised sequences of control and intervention condition, including stepped wedge designs.

Physiological, hyaluronan-selected intracytoplasmic sperm injection for infertility treatment (HABSelect): a parallel, two-group, randomised trial.

BACKGROUND: Sperm selection strategies aimed at improving success rates of intracytoplasmic sperm injection (ICSI) include binding to hyaluronic acid (herein termed hyaluronan). Hyaluronan-selected sperm have reduced levels of DNA damage and aneuploidy. Use of hyaluronan-based sperm selection for ICSI (so-called physiological ICSI [PICSI]) is reported to reduce the proportion of pregnancies that end in miscarriage. However, the effect of PICSI on livebirth rates is uncertain. We aimed to investigate the efficacy of PICSI versus standard ICSI for improving livebirth rates among couples undergoing fertility treatment. METHODS: This parallel, two-group, randomised trial included couples undergoing an ICSI procedure with fresh embryo transfer at 16 assisted conception units in the UK. Eligible women (aged 18-43 years) had a body-mass index of 19-35 kg/m2 and a follicle-stimulating hormone (FSH) concentration of 3·0-20·0 mIU/mL or, if no FSH measurement was available, an anti-müllerian hormone concentration of at least 1·5 pmol/L. Eligible men (aged 18-55 years) had not had a vasovasostomy or been treated for cancer in the 24 months before recruitment and were able, after at least 3 days of sexual abstinence, to produce freshly ejaculated sperm for the treatment cycle. Couples were randomly assigned (1:1) with an online system to receive either PICSI or a standard ICSI procedure. The primary outcome was full-term (≥37 weeks' gestational age) livebirth, which was assessed in all eligible couples who completed follow-up. This trial is registered, number ISRCTN99214271. FINDINGS: Between Feb 1, 2014, and Aug 31, 2016, 2772 couples were randomly assigned to receive PICSI (n=1387) or ICSI (n=1385), of whom 2752 (1381 in the PICSI group and 1371 in the ICSI group) were included in the primary analysis. The term livebirth rate did not differ significantly between PICSI (27·4% [379/1381]) and ICSI (25·2% [346/1371]) groups (odds ratio 1·12, 95% CI 0·95-1·34; p=0·18). There were 56 serious adverse events in total, including 31 in the PICSI group and 25 in the ICSI group; most were congenital abnormalities and none were attributed to treatment. INTERPRETATION: Compared with ICSI, PICSI does not significantly improve term livebirth rates. The wider use of PICSI, therefore, is not recommended at present. FUNDING: National Institute for Health Research Efficacy and Mechanism Evaluation Programme.

Improving the healthcare response to domestic violence and abuse in UK primary care: interrupted time series evaluation of a system-level training and support programme.

BACKGROUND: It is unknown whether interventions known to improve the healthcare response to domestic violence and abuse (DVA)-a global health concern-are effective outside of a trial. METHODS: An observational interrupted time series study in general practice. All registered women aged 16 and above were eligible for inclusion. In four implementation boroughs' general practices, there was face-to-face, practice-based, clinically relevant DVA training, a prompt in the electronic medical record, reminding clinicians to consider DVA, a simple referral pathway to a named advocate, ensuring direct access for women to specialist services, overseen by a national, health-focused DVA organisation, fostering best practice. The fifth comparator borough had only a session delivered by a local DVA specialist agency at community venues conveying information to clinicians. The primary outcome was the daily number of referrals received by DVA workers per 1000 women registered in a general practice, from 205 general practices, in all five northeast London boroughs. The secondary outcome was recorded new DVA cases in the electronic medical record in two boroughs. Data was analysed using an interrupted time series with a mixed effects Poisson regression model. RESULTS: In the 144 general practices in the four implementation boroughs, there was a significant increase in referrals received by DVA workers-global incidence rate ratio of 30.24 (95% CI 20.55 to 44.77, p < 0.001). There was no increase in the 61 general practices in the other comparator borough (incidence rate ratio of 0.95, 95% CI 0.13 to 6.84, p = 0.959). New DVA cases recorded significantly increased with an incident rate ratio of 1.27 (95% CI 1.09 to 1.48, p < 0.002) in the implementation borough but not in the comparator borough (incidence rate ratio of 1.05, 95% CI 0.82 to 1.34, p = 0.699). CONCLUSIONS: Implementing integrated referral routes, training and system-level support, guided by a national health-focused DVA organisation, outside of a trial setting, was effective and sustainable at scale, over four years (2012 to 2017) increasing referrals to DVA workers and new DVA cases recorded in electronic medical records.

External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis.

BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. METHODS: IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. RESULTS: Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. CONCLUSIONS: The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. TRIAL REGISTRATION: PROSPERO ID: CRD42015029349 .

Sample size and power calculations for open cohort longitudinal cluster randomized trials.

When calculating sample size or power for stepped wedge or other types of longitudinal cluster randomized trials, it is critical that the planned sampling structure be accurately specified. One common assumption is that participants will provide measurements in each trial period, that is, a closed cohort, and another is that each participant provides only one measurement during the course of the trial. However some studies have an "open cohort" sampling structure, where participants may provide measurements in variable numbers of periods. To date, sample size calculations for longitudinal cluster randomized trials have not accommodated open cohorts. Feldman and McKinlay (1994) provided some guidance, stating that the participant-level autocorrelation could be varied to account for the degree of overlap in different periods of the study, but did not indicate precisely how to do so. We present sample size and power formulas that allow for open cohorts and discuss the impact of the degree of "openness" on sample size and power. We consider designs where the number of participants in each cluster will be maintained throughout the trial, but individual participants may provide differing numbers of measurements. Our results are a unification of closed cohort and repeated cross-sectional sample results of Hooper et al (2016), and indicate precisely how participant autocorrelation of Feldman and McKinlay should be varied to account for an open cohort sampling structure. We discuss different types of open cohort sampling schemes and how open cohort sampling structure impacts on power in the presence of decaying within-cluster correlations and autoregressive participant-level errors.

The hunt for efficient, incomplete designs for stepped wedge trials with continuous recruitment and continuous outcome measures.

BACKGROUND: We consider the design of stepped wedge trials with continuous recruitment and continuous outcome measures. Suppose we recruit from a fixed number of clusters where eligible participants present continuously, and suppose we have fine control over when each cluster crosses to the intervention. Suppose also that we want to minimise the number of participants, leading us to consider "incomplete" designs (i.e. without full recruitment). How can we schedule recruitment and cross-over at different clusters to recruit efficiently while achieving good precision? METHODS: The large number of possible designs can make exhaustive searches impractical. Instead we consider an algorithm using iterative improvements to hunt for an efficient design. At each iteration (starting from a complete design) a single participant - the one with the smallest impact on precision - is removed, and small changes preserving total sample size are made until no further improvement in precision can be found. RESULTS: Striking patterns emerge. Solutions typically focus recruitment and cross-over on the leading diagonal of the cluster-by-time diagram, but in some scenarios clusters form distinct phases resembling before-and-after designs. CONCLUSIONS: There is much to be learned about optimal design for incomplete stepped wedge trials. Algorithmic searches could offer a practical approach to trial design in complex settings generally.

Cluster randomised trials with different numbers of measurements at baseline and endline: Sample size and optimal allocation.

BACKGROUND/AIMS: Published methods for sample size calculation for cluster randomised trials with baseline data are inflexible and primarily assume an equal amount of data collected at baseline and endline, that is, before and after the intervention has been implemented in some clusters. We extend these methods to any amount of baseline and endline data. We explain how to explore sample size for a trial if some baseline data from the trial clusters have already been collected as part of a separate study. Where such data aren't available, we show how to choose the proportion of data collection devoted to the baseline within the trial, when a particular cluster size or range of cluster sizes is proposed. METHODS: We provide a design effect given the cluster size and correlation parameters, assuming different participants are assessed at baseline and endline in the same clusters. We show how to produce plots to identify the impact of varying the amount of baseline data accounting for the inevitable uncertainty in the cluster autocorrelation. We illustrate the methodology using an example trial. RESULTS: Baseline data provide more power, or allow a greater reduction in trial size, with greater values of the cluster size, intracluster correlation and cluster autocorrelation. CONCLUSION: Investigators should think carefully before collecting baseline data in a cluster randomised trial if this is at the expense of endline data. In some scenarios, this will increase the sample size required to achieve given power and precision.

Mediterranean-style diet in pregnant women with metabolic risk factors (ESTEEM): A pragmatic multicentre randomised trial.

BACKGROUND: Pregnant women with metabolic risk factors are at high risk of complications. We aimed to assess whether a Mediterranean-style diet reduces adverse pregnancy outcomes in high-risk women. METHODS AND FINDINGS: We conducted a multicentre randomised trial in 5 maternity units (4 in London and 1 in Birmingham) between 12 September 2014 and 29 February 2016. We randomised inner-city pregnant women with metabolic risk factors (obesity, chronic hypertension, or hypertriglyceridaemia) to a Mediterranean-style diet with high intake of nuts, extra virgin olive oil, fruits, vegetables, nonrefined grains, and legumes; moderate to high consumption of fish; low to moderate intake of poultry and dairy products; low intake of red and processed meat; and avoidance of sugary drinks, fast food, and food rich in animal fat versus usual care. Participants received individualised dietary advice at 18, 20, and 28 weeks' gestation. The primary endpoints were composite maternal (gestational diabetes or preeclampsia) and composite offspring (stillbirth, small for gestational age, or admission to neonatal care unit) outcomes prioritised by a Delphi survey. We used an intention-to-treat (ITT) analysis with multivariable models and identified the stratification variables and prognostic factors a priori. We screened 7,950 and randomised 1,252 women. Baseline data were available for 593 women in the intervention (93.3% follow-up, 553/593) and 612 in the control (95.6% follow-up, 585/612) groups. Over a quarter of randomised women were primigravida (330/1,205; 27%), 60% (729/1,205) were of Black or Asian ethnicity, and 69% (836/1,205) were obese. Women in the intervention arm consumed more nuts (70.1% versus 22.9%; adjusted odds ratio [aOR] 6.8, 95% confidence interval [CI] 4.3-10.6, p ≤ 0.001) and extra virgin olive oil (93.2% versus 49.0%; aOR 32.2, 95% CI 16.0-64.6, p ≤ 0.001) than controls; increased their intake of fish (p < 0.001), white meat (p < 0.001), and pulses (p = 0.05); and reduced their intake of red meat (p < 0.001), butter, margarine, and cream (p < 0.001). There was no significant reduction in the composite maternal (22.8% versus 28.6%; aOR 0.76, 95% CI 0.56-1.03, p = 0.08) or composite offspring (17.3% versus 20.9%; aOR 0.79, 95% CI 0.58-1.08, p = 0.14) outcomes. There was an apparent reduction in the odds of gestational diabetes by 35% (aOR 0.65, 95% CI 0.47-0.91, p = 0.01) but not in other individual components of the composite outcomes. Mothers gained less gestational weight (mean 6.8 versus 8.3 kg; adjusted difference -1.2 Kg, 95% CI -2.2 to -0.2, p = 0.03) with intervention versus control. There was no difference in any of the other maternal and offspring complications between both groups. When we pooled findings from the Effect of Simple, Targeted Diet in Pregnant Women With Metabolic Risk Factors on Pregnancy Outcomes (ESTEEM) trial with similar trials using random effects meta-analysis, we observed a significant reduction in gestational diabetes (odds ratio [OR] 0.67, 95% CI 0.53-0.84, I2 = 0%), with no heterogeneity (2 trials, 2,397 women). The study's limitations include the use of participant reported tools for adherence to the intervention instead of objective biomarkers. CONCLUSIONS: A simple, individualised, Mediterranean-style diet in pregnancy did not reduce the overall risk of adverse maternal and offspring complications but has the potential to reduce gestational weight gain and the risk of gestational diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT02218931.

Vitamin D to prevent exacerbations of COPD: systematic review and meta-analysis of individual participant data from randomised controlled trials.

BACKGROUND: Randomised controlled trials (RCTs) of vitamin D to prevent COPD exacerbations have yielded conflicting results.Individual participant data meta-analysis could identify factors that explain this variation. METHODS: PubMed, Embase, the Cochrane Central Register of Controlled Trials and Web of Science were searched from inception up to and including 5 October 2017 to identify RCTs of vitamin D supplementation in patients with COPD that reported incidence of acute exacerbations. Individual participant data meta-analysis was performed using fixed effects models adjusting for age, sex, Global Initiative for Chronic Obstructive Lung Disease spirometric grade and trial. RESULTS: Four eligible RCTs (total 560 participants) were identified; individual participant data were obtained for 469/472 (99.4%) participants in three RCTs. Supplementation did not influence overall rate of moderate/severe COPD exacerbations (adjusted incidence rate ratio (aIRR) 0.94, 95% CI 0.78 to 1.13). Prespecified subgroup analysis revealed that protective effects were seen in participants with baseline 25-hydroxyvitamin D levels <25 nmol/L (aIRR 0.55, 95% CI 0.36 to 0.84) but not in those with baseline 25-hydroxyvitamin D levels ≥25 nmol/L (aIRR 1.04, 95% CI 0.85 to 1.27; p for interaction=0.015). Vitamin D did not influence the proportion of participants experiencing at least one serious adverse event (adjusted OR 1.16, 95% CI 0.76 to 1.75). CONCLUSIONS: Vitamin D supplementation safely and substantially reduced the rate of moderate/severe COPD exacerbations in patients with baseline 25-hydroxyvitamin D levels <25 nmol/L but not in those with higher levels. TRIAL REGISTRATION NUMBER: CRD42014013953.

Improving the efficiency of individually randomized clinical trials by staggering the introduction of the intervention.

In cluster randomized trials, the introduction of the intervention can be staggered in different clusters, leading to a stepped wedge design. This strategy can lead to gains in efficiency, which might also translate to the context of individually randomized trials, though this has been relatively unexplored. Here, we present one illustrative example. We consider trials in which participants start in a control condition such as routine care and can cross over at any stage to the active intervention. We make the assumption that the effect of the intervention is the same however long the delay before a participant crosses over to the intervention condition. We consider designs for a trial with three repeated assessments, including a baseline, and show that a three-sequence design with staggered introduction of the intervention in two of the sequences estimates the treatment effect after one period more efficiently than a parallel groups design.

Dietary patterns and respiratory health in adults from nine European countries-Evidence from the GA2 LEN study.

BACKGROUND: Dietary patterns defined using principal component analysis (PCA) offer an alternative to the analysis of individual foods and nutrients and have been linked with asthma and allergic disease. However, results have not been reproducible in different settings. OBJECTIVE: To identify dietary patterns common to different European countries and examine their associations with asthma and allergic symptoms. METHODS: In sixteen study centers in nine European countries, 3206 individuals aged 15-77 years completed a common, internationally validated, food frequency questionnaire and a respiratory symptoms questionnaire. The outcomes of interest were current asthma, asthma symptoms score (derived based on responses to 5 asthma symptom-related questions), atopy (positive skin prick test). Spirometry was used to estimate forced expiratory volume in 1 second (FEV1 ), forced vital capacity (FVC), the FEV1 /FVC, spirometric restriction (FVC below the lower limit of normal (

Cell salvage and donor blood transfusion during cesarean section: A pragmatic, multicentre randomised controlled trial (SALVO).

BACKGROUND: Excessive haemorrhage at cesarean section requires donor (allogeneic) blood transfusion. Cell salvage may reduce this requirement. METHODS AND FINDINGS: We conducted a pragmatic randomised controlled trial (at 26 obstetric units; participants recruited from 4 June 2013 to 17 April 2016) of routine cell salvage use (intervention) versus current standard of care without routine salvage use (control) in cesarean section among women at risk of haemorrhage. Randomisation was stratified, using random permuted blocks of variable sizes. In an intention-to-treat analysis, we used multivariable models, adjusting for stratification variables and prognostic factors identified a priori, to compare rates of donor blood transfusion (primary outcome) and fetomaternal haemorrhage ≥2 ml in RhD-negative women with RhD-positive babies (a secondary outcome) between groups. Among 3,028 women randomised (2,990 analysed), 95.6% of 1,498 assigned to intervention had cell salvage deployed (50.8% had salvaged blood returned; mean 259.9 ml) versus 3.9% of 1,492 assigned to control. Donor blood transfusion rate was 3.5% in the control group versus 2.5% in the intervention group (adjusted odds ratio [OR] 0.65, 95% confidence interval [CI] 0.42 to 1.01, p = 0.056; adjusted risk difference -1.03, 95% CI -2.13 to 0.06). In a planned subgroup analysis, the transfusion rate was 4.6% in women assigned to control versus 3.0% in the intervention group among emergency cesareans (adjusted OR 0.58, 95% CI 0.34 to 0.99), whereas it was 2.2% versus 1.8% among elective cesareans (adjusted OR 0.83, 95% CI 0.38 to 1.83) (interaction p = 0.46). No case of amniotic fluid embolism was observed. The rate of fetomaternal haemorrhage was higher with the intervention (10.5% in the control group versus 25.6% in the intervention group, adjusted OR 5.63, 95% CI 1.43 to 22.14, p = 0.013). We are unable to comment on long-term antibody sensitisation effects. CONCLUSIONS: The overall reduction observed in donor blood transfusion associated with the routine use of cell salvage during cesarean section was not statistically significant. TRIAL REGISTRATION: This trial was prospectively registered on ISRCTN as trial number 66118656 and can be viewed on http://www.isrctn.com/ISRCTN66118656.

Sample size calculation for stepped wedge and other longitudinal cluster randomised trials.

The sample size required for a cluster randomised trial is inflated compared with an individually randomised trial because outcomes of participants from the same cluster are correlated. Sample size calculations for longitudinal cluster randomised trials (including stepped wedge trials) need to take account of at least two levels of clustering: the clusters themselves and times within clusters. We derive formulae for sample size for repeated cross-section and closed cohort cluster randomised trials with normally distributed outcome measures, under a multilevel model allowing for variation between clusters and between times within clusters. Our formulae agree with those previously described for special cases such as crossover and analysis of covariance designs, although simulation suggests that the formulae could underestimate required sample size when the number of clusters is small. Whether using a formula or simulation, a sample size calculation requires estimates of nuisance parameters, which in our model include the intracluster correlation, cluster autocorrelation, and individual autocorrelation. A cluster autocorrelation less than 1 reflects a situation where individuals sampled from the same cluster at different times have less correlated outcomes than individuals sampled from the same cluster at the same time. Nuisance parameters could be estimated from time series obtained in similarly clustered settings with the same outcome measure, using analysis of variance to estimate variance components. Copyright © 2016 John Wiley & Sons, Ltd.

Correlates between models of virulence for Mycobacterium tuberculosis among isolates of the Central Asian lineage: a case for lysozyme resistance testing?

Virulence factors (VFs) contribute to the emergence of new human Mycobacterium tuberculosis strains, are lineage dependent, and are relevant to the development of M. tuberculosis drugs/vaccines. VFs were sought within M. tuberculosis lineage 3, which has the Central Asian (CAS) spoligotype. Three isolates were selected from clusters previously identified as dominant in London, United Kingdom. Strain-associated virulence was studied in guinea pig, monocyte-derived macrophage, and lysozyme resistance assays. Whole-genome sequencing, single nucleotide polymorphism (SNP) analysis, and a literature review contributed to the identification of SNPs of interest. The animal model revealed borderline differences in strain-associated pathogenicity. Ex vivo, isolate C72 exhibited statistically significant differences in intracellular growth relative to C6 and C14. SNP candidates inducing lower fitness levels included 123 unique nonsynonymous SNPs, including three located in genes (lysX, caeA, and ponA2) previously identified as VFs in the laboratory-adapted reference strain H37Rv and shown to confer lysozyme resistance. C72 growth was most affected by lysozyme in vitro. A BLAST search revealed that all three SNPs of interest (C35F, P76Q, and P780R) also occurred in Tiruvallur, India, and in Uganda. Unlike C72, however, no single isolate identified through BLAST carried all three SNPs simultaneously. CAS isolates representative of three medium-sized human clusters demonstrated differential outcomes in models commonly used to estimate strain-associated virulence, supporting the idea that virulence varies within, not just across, M. tuberculosis lineages. Three VF SNPs of interest were identified in two additional locations worldwide, which suggested independent selection and supported a role for these SNPs in virulence. The relevance of lysozyme resistance to strain virulence remains to be established.