Effects of study precision and risk of bias in networks of interventions: a network meta-epidemiological study

BACKGROUND Empirical research has illustrated an association between study size and relative treatment effects, but conclusions have been inconsistent about the association of study size with the risk of bias items. Small studies give generally imprecisely estimated treatment effects, and study variance can serve as a surrogate for study size. METHODS We conducted a network meta-epidemiological study analyzing 32 networks including 613 randomized controlled trials, and used Bayesian network meta-analysis and meta-regression models to evaluate the impact of trial characteristics and study variance on the results of network meta-analysis. We examined changes in relative effects and between-studies variation in network meta-regression models as a function of the variance of the observed effect size and indicators for the adequacy of each risk of bias item. Adjustment was performed both within and across networks, allowing for between-networks variability. RESULTS Imprecise studies with large variances tended to exaggerate the effects of the active or new intervention in the majority of networks, with a ratio of odds ratios of 1.83 (95% CI: 1.09,3.32). Inappropriate or unclear conduct of random sequence generation and allocation concealment, as well as lack of blinding of patients and outcome assessors, did not materially impact on the summary results. Imprecise studies also appeared to be more prone to inadequate conduct. CONCLUSIONS Compared to more precise studies, studies with large variance may give substantially different answers that alter the results of network meta-analyses for dichotomous outcomes.

Effects of weight on blood pressure at rest and during exercise.

Body weight (BW) and blood pressure (BP) have a close relationship, which has been accounted for by hormonal changes. No previous study has evaluated the effect of wearing an external weight vest on BP to determine whether there is a simple mechanism between BW and BP. Seventeen healthy volunteers underwent weight reduction (WR) through caloric restriction. Before and after WR, BW, body fat percentage and BP at rest and during exercise were measured. Before and after WR, exercise testing was performed twice with the random allocation of a weight vest (10 kg) during one of the tests. Linear regression was used to detect independent associations between BP and the weight vest, BW and body fat percentage. BW decreased from 89.4 ± 15.4 kg to 79.1 ± 14.0 kg following WR (P<0.001). WR led to significant decreases in BP at rest (from 130.0/85.9 mm Hg to 112.5/77.8 mm Hg, P<0.001 for systolic and diastolic BPs) and during exercise. The weight vest significantly increased BP at rest (to 136.1/90.7 mm Hg before and 125.8/84.6 mm Hg after WR) and during exercise. Linear regression analysis identified an independent association between the weight vest and BP (P=0.006 for systolic BP and P=0.009 for diastolic BP at rest). This study demonstrates that wearing an external weight vest has immediate effects on BP at rest and during exercise independent of BW or body fat. More research is needed to understand the physiological mechanisms between weight and BP.

Suppressing versus releasing a habit: frequency-dependent effects of prefrontal transcranial magnetic stimulation.

When subjects are required to generate a random sequence of numbers they typically produce too many forward and backward 'counts' (e.g. 5-6, 4-3). This counting bias is interpreted as the consequence of an interference by overlearned tendencies to arrange numbers according to their natural order. Inhibition of such well-learned routines is known to rely on frontal lobe functioning. We examined differential effects of slow (1 Hz) and fast (10 Hz) repetitive transcranial magnetic stimulation (rTMS) over the left or right dorsolateral prefrontal cortex (DLPFC) on random number generation (RNG) performance. Eighteen healthy men performed an RNG task. Those subjects stimulated over the left DLPFC showed a frequency-dependent rTMS effect: counting bias was significantly reduced after the 1 Hz stimulation compared with baseline, but significantly exaggerated after the 10 Hz stimulation compared with 1 Hz stimulation. In contrast, the sequences of the subjects stimulated over the right DLPFC showed the well-known excess of counting in all conditions (i.e. baseline, 1 Hz and 10 Hz). These findings confirm the functional importance of specifically the left DLPFC in sequential response production and show, for the first time, that rTMS affects cognitive processing in a frequency-dependent manner.

What is the influence of randomisation sequence generation and allocation concealment on treatment effects of physical therapy trials? A meta-epidemiological study.

OBJECTIVE To determine if adequacy of randomisation and allocation concealment is associated with changes in effect sizes (ES) when comparing physical therapy (PT) trials with and without these methodological characteristics. DESIGN Meta-epidemiological study. PARTICIPANTS A random sample of randomised controlled trials (RCTs) included in meta-analyses in the PT discipline were identified. INTERVENTION Data extraction including assessments of random sequence generation and allocation concealment was conducted independently by two reviewers. To determine the association between sequence generation, and allocation concealment and ES, a two-level analysis was conducted using a meta-meta-analytic approach. PRIMARY AND SECONDARY OUTCOME MEASURES association between random sequence generation and allocation concealment and ES in PT trials. RESULTS 393 trials included in 43 meta-analyses, analysing 44 622 patients contributed to this study. Adequate random sequence generation and appropriate allocation concealment were accomplished in only 39.7% and 11.5% of PT trials, respectively. Although trials with inappropriate allocation concealment tended to have an overestimate treatment effect when compared with trials with adequate concealment of allocation, the difference was non-statistically significant (ES=0.12; 95% CI -0.06 to 0.30). When pooling our results with those of Nuesch et al, we obtained a pooled statistically significant value (ES=0.14; 95% CI 0.02 to 0.26). There was no difference in ES in trials with appropriate or inappropriate random sequence generation (ES=0.02; 95% CI -0.12 to 0.15). CONCLUSIONS Our results suggest that when evaluating risk of bias of primary RCTs in PT area, systematic reviewers and clinicians implementing research into practice should pay attention to these biases since they could exaggerate treatment effects. Systematic reviewers should perform sensitivity analysis including trials with low risk of bias in these domains as primary analysis and/or in combination with less restrictive analyses. Authors and editors should make sure that allocation concealment and random sequence generation are properly reported in trial reports.

Species interactions and random dispersal rather than habitat filtering drive community assembly during early plant succession

Theory on plant succession predicts a temporal increase in the complexity of spatial community structure and of competitive interactions: initially random occurrences of early colonising species shift towards spatially and competitively structured plant associations in later successional stages. Here we use long-term data on early plant succession in a German post mining area to disentangle the importance of random colonisation, habitat filtering, and competition on the temporal and spatial development of plant community structure. We used species co-occurrence analysis and a recently developed method for assessing competitive strength and hierarchies (transitive versus intransitive competitive orders) in multispecies communities. We found that species turnover decreased through time within interaction neighbourhoods, but increased through time outside interaction neighbourhoods. Successional change did not lead to modular community structure. After accounting for species richness effects, the strength of competitive interactions and the proportion of transitive competitive hierarchies increased through time. Although effects of habitat filtering were weak, random colonization and subsequent competitive interactions had strong effects on community structure. Because competitive strength and transitivity were poorly correlated with soil characteristics, there was little evidence for context dependent competitive strength associated with intransitive competitive hierarchies.

The Effects of Density, Spatial Pattern, and Competitive Symmetry on Size Variation in Simulated Plant Populations

Patterns of size inequality in crowded plant populations are often taken to be indicative of the degree of size asymmetry of competition, but recent research suggests that some of the patterns attributed to size‐asymmetric competition could be due to spatial structure. To investigate the theoretical relationships between plant density, spatial pattern, and competitive size asymmetry in determining size variation in crowded plant populations, we developed a spatially explicit, individual‐based plant competition model based on overlapping zones of influence. The zone of influence of each plant is modeled as a circle, growing in two dimensions, and is allometrically related to plant biomass. The area of the circle represents resources potentially available to the plant, and plants compete for resources in areas in which they overlap. The size asymmetry of competition is reflected in the rules for dividing up the overlapping areas. Theoretical plant populations were grown in random and in perfectly uniform spatial patterns at four densities under size‐asymmetric and size‐symmetric competition. Both spatial pattern and size asymmetry contributed to size variation, but their relative importance varied greatly over density and over time. Early in stand development, spatial pattern was more important than the symmetry of competition in determining the degree of size variation within the population, but after plants grew and competition intensified, the size asymmetry of competition became a much more important source of size variation. Size variability was slightly higher at higher densities when competition was symmetric and plants were distributed nonuniformly in space. In a uniform spatial pattern, size variation increased with density only when competition was size asymmetric. Our results suggest that when competition is size asymmetric and intense, it will be more important in generating size variation than is local variation in density. Our results and the available data are consistent with the hypothesis that high levels of size inequality commonly observed within crowded plant populations are largely due to size‐asymmetric competition, not to variation in local density.

On ANOVA Decompositions of Kernels and Gaussian Random Field Paths

The FANOVA (or “Sobol’-Hoeffding”) decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis. When the objective function f has no simple analytic form and is costly to evaluate, computing FANOVA terms may be unaffordable due to numerical integration costs. Several approximate approaches relying on Gaussian random field (GRF) models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional simulations. Here we focus on FANOVA decompositions of GRF sample paths, and we notably introduce an associated kernel decomposition into 4 d 4d terms called KANOVA. An interpretation in terms of tensor product projections is obtained, and it is shown that projected kernels control both the sparsity of GRF sample paths and the dependence structure between FANOVA effects. Applications on simulated data show the relevance of the approach for designing new classes of covariance kernels dedicated to high-dimensional kriging.