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Objectives To assess the overall effect of vitamin D supplementation on risk of acute respiratory tract infection, and to identify factors modifying this effect.Design Systematic review and meta-analysis of individual participant data (IPD) from randomised controlled trials.Data sources Medline, Embase, the Cochrane Central Register of Controlled Trials, Web of Science, ClinicalTrials.gov, and the International Standard Randomised Controlled Trials Number registry from inception to December 2015.Eligibility criteria for study selection Randomised, double blind, placebo controlled trials of supplementation with vitamin D3 or vitamin D2 of any duration were eligible for inclusion if they had been approved by a research ethics committee and if data on incidence of acute respiratory tract infection were collected prospectively and prespecified as an efficacy outcome.Results 25 eligible randomised controlled trials (total 11 321 participants, aged 0 to 95 years) were identified. IPD were obtained for 10 933 (96.6%) participants. Vitamin D supplementation reduced the risk of acute respiratory tract infection among all participants (adjusted odds ratio 0.88, 95% confidence interval 0.81 to 0.96; P for heterogeneity <0.001). In subgroup analysis, protective effects were seen in those receiving daily or weekly vitamin D without additional bolus doses (adjusted odds ratio 0.81, 0.72 to 0.91) but not in those receiving one or more bolus doses (adjusted odds ratio 0.97, 0.86 to 1.10; P for interaction=0.05). Among those receiving daily or weekly vitamin D, protective effects were stronger in those with baseline 25-hydroxyvitamin D levels <25 nmol/L (adjusted odds ratio 0.30, 0.17 to 0.53) than in those with baseline 25-hydroxyvitamin D levels ≥25 nmol/L (adjusted odds ratio 0.75, 0.60 to 0.95; P for interaction=0.006). Vitamin D did not influence the proportion of participants experiencing at least one serious adverse event (adjusted odds ratio 0.98, 0.80 to 1.20, P=0.83). The body of evidence contributing to these analyses was assessed as being of high quality.Conclusions Vitamin D supplementation was safe and it protected against acute respiratory tract infection overall. Patients who were very vitamin D deficient and those not receiving bolus doses experienced the most benefit.Systematic review registration PROSPERO CRD42014013953.

Questions often arise concerning when, whether, and how we should adjust our interpretation of the results from multiple hypothesis tests. Strong arguments have been put forward in the epidemiological literature against any correction or adjustment for multiplicity, but regulatory requirements (particularly for pharmaceutical trials) can sometimes trump other concerns. The formal basis for adjustment is often the control of error rates, and hence the problems of multiplicity may seem rooted in a purely frequentist paradigm, though this can be a restrictive viewpoint. Commentators may never wholly agree on any of these things. This article draws some of the key threads from the discussion and suggests further reading.

BackgroundRandomised 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.MethodsPubMed, 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.ResultsFour 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).ConclusionsVitamin 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 numberCRD42014013953.

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.

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. 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. 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. ClinicalTrials.gov NCT02218931.

Normal bowel function requires intact sensory pathways. Diminished rectal sensation (rectal hyposensitivity [RH]) is associated with constipation, although its clinical importance remains unclear. 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. 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). 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.).

To review methodological guidance for nonlinear covariate-outcome associations (NL), and linear effect modification and nonlinear effect modification (LEM and NLEM) at the participant level in individual participant data meta-analyses (IPDMAs) and their power requirements. We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify methodology publications on IPDMA of LEM, NL or NLEM (PROSPERO CRD42019126768). Through screening 6,466 records we identified 54 potential articles of which 23 full texts were relevant. Nine further relevant publications were published before or after the literature search and were added. Of these 32 references, 21 articles considered LEM, 6 articles NL or NLEM and 6 articles described sample size calculations. A book described all four. Sample size may be calculated through simulation or closed form. Assessments of LEM or NLEM at the participant level need to be based on within-trial information alone. Nonlinearity (NL or NLEM) can be modeled using polynomials or splines to avoid categorization. Detailed methodological guidance on IPDMA of effect modification at participant-level is available. However, methodology papers for sample size and nonlinearity are rarer and may not cover all scenarios. On these aspects, further guidance is needed.

To review analysis methods used for linear effect modification (LEM), nonlinear covariate-outcome associations (NL) and nonlinear effect modification (NLEM) at the participant-level in individual participant data meta-analysis (IPDMA). We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify IPDMA of randomized controlled trials (PROSPERO CRD42019126768). We investigated if and how IPDMA examined LEM, NL and NLEM, including whether aggregation bias was addressed and if power was considered. We screened 6,466 records, randomly sampled 207 and identified 100 IPDMA of LEM, NL or NLEM. Power for LEM was calculated a priori in 3 IPDMA. Of 100 IPDMA, 94 analyzed LEM, 4 NLEM and 8 NL. One-stage models were favoured for all three (56%, 100%, 50%, respectively). Two-stage models were used in 15%, 0% and 25% of IPDMA with unclear descriptions in 30%, 0% and 25%, respectively. Only 12% of one-stage LEM and NLEM IPDMA provided sufficient detail to confirm they had addressed aggregation bias. Investigation of effect modification at the participant-level is common in IPDMA projects, but methods are often open to bias or lack detailed descriptions. Nonlinearity of continuous covariates and power of IPDMA are rarely assessed.

Normal bowel function requires intact sensory pathways. Diminished rectal sensation (rectal hyposensitivity [RH]) is associated with constipation, although its clinical importance remains unclear. 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. 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). 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).

Background In randomised controlled trials with efficacy-related primary outcomes, adverse events are collected to monitor potential intervention harms. The analysis of adverse event data is challenging, due to the complex nature of the data and the large number of unprespecified outcomes. This is compounded by a lack of guidance on best analysis approaches, resulting in widespread inadequate practices and the use of overly simplistic methods; leading to sub-optimal exploitation of these rich datasets. To address the complexities of adverse events analysis, statistical methods are proposed that leverage existing structures within the data, for instance by considering groupings of adverse events based on biological or clinical relationships. Methods We conducted a methodological scoping review of the literature to identify all existing methods using structures within the data to detect signals for adverse reactions in a trial. Embase, MEDLINE, Scopus and Web of Science databases were systematically searched. We reviewed the analysis approaches of each method, extracted methodological characteristics and constructed a narrative summary of the findings. Results We identified 18 different methods from 14 sources. These were categorised as either Bayesian approaches ( n =11), which flagged events based on posterior estimates of treatment effects, or error controlling procedures ( n =7), which flagged events based on adjusted p -values while controlling for some type of error rate. We identified 5 defining methodological characteristics: the type of outcomes considered (e.g. binary outcomes), the nature of the data (e.g. summary data), the timing of the analysis (e.g. final analysis), the restrictions on the events considered (e.g. rare events) and the grouping systems used. Conclusions We found a large number of analysis methods that use the group structures of adverse events. Continuous methodological developments in this area highlight the growing awareness that better practices are needed. The use of more adequate analysis methods could help trialists obtain a better picture of the safety-risk profile of an intervention. The results of this review can be used by statisticians to better understand the current methodological landscape and identify suitable methods for data analysis - although further research is needed to determine which methods are best suited and create adequate recommendations.