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Objectives: Symptoms of insomnia are highly prevalent in the elderly. A significant number of pharmacological and non‐pharmacological interventions exist, but, up‐to‐date, their comparative efficacy and safety has not been sufficiently assessed. Methods: We integrated the randomized evidence from every available treatment for insomnia in the elderly (>65 years) by performing a network meta‐analysis. Several electronic databases were searched up to May 25, 2019. The two primary outcomes were total sleep time and sleep quality. Data for other 6 efficacy and 8 safety outcomes were also analyzed. Results: Fifty‐three RCTs with 6832 participants (75 years old on average) were included, 43 of which examined the efficacy of one or more drugs. Ten RCTs examined the efficacy of non‐pharmacological interventions and were evaluated only with pairwise meta‐analyses because they were disconnected from the network. The overall confidence in the evidence was very low primarily due to the small amount of data per comparison and their sparse connectedness. Several benzodiazepines, antidepressants, and z‐drugs performed better in both primary outcomes, but few comparisons had data from more than one trial. The limited evidence on non‐pharmacological interventions suggested that acupressure, auricular acupuncture, mindfulness‐based stress reduction program, and tart cherry juice were better than their control interventions. Regarding safety, no clear differences were detected among interventions due to large uncertainty. Conclusions: Insufficient evidence exists on which intervention is more efficacious for elderly patients with insomnia. More RCTs, with longer duration, making more direct interventions among active treatments and presenting more outcomes are urgently needed. [ABSTRACT FROM AUTHOR]

Background: In fixed‐dose antidepressant trials, the lower range of the licensed dose achieves the optimal balance between efficacy and tolerability. Whether flexible upward titration while side‐effects permit provides additional benefits is unknown. Methods: We did a systematic review of placebo‐controlled randomized trials that examined selective serotonin reuptake inhibitors (SSRIs), venlafaxine or mirtazapine in the acute treatment of major depression. Our primary outcome was response, defined as 50% or greater reduction in depression severity. Secondary outcomes included drop‐outs due to adverse effects and drop‐outs for any reason. We conducted random‐effects meta‐analyses to calculate the ratios of odds ratios (RORs) between trials comparing the flexible dose titrating above the minimum licensed dose against placebo and those comparing the fixed minimum licensed dose against placebo. Results: We included 123 published and unpublished randomized controlled trials (29 420 participants). There was no evidence supporting efficacy of the flexible dosing over the fixed low dose of SSRIs (ROR 0.96, 95% CI: 0.73 to 1.25), venlafaxine (1.24, 0.96 to 1.60) or mirtazapine (0.77, 0.33 to 1.78). No important differences were noted for tolerability or for any subgroup analyses except the superior efficacy of venlafaxine flexible dosing between 75 and 150 mg over the fixed 75 mg (1.30, 1.02 to 1.65). Conclusion: There was no evidence to support added value in terms of efficacy, tolerability or acceptability of flexibly titrating up the dosage over the minimum licensed dose of SSRIs or mirtazapine. For venlafaxine, increased efficacy can be expected by flexibly titrating up to 150 mg. [ABSTRACT FROM AUTHOR]

There is good empirical evidence that specific flaws in the conduct of randomized controlled trials are associated with exaggeration of treatment effect estimates. Mixed treatment comparison meta-analysis, which combines data from trials on several treatments that form a network of comparisons, has the potential both to estimate bias parameters within the synthesis and to produce bias-adjusted estimates of treatment effects. We present a hierarchical model for bias with common mean across treatment comparisons of active treatment versus control. It is often unclear, from the information that is reported, whether a study is at risk of bias or not. We extend our model to estimate the probability that a particular study is biased, where the probabilities for the ‘unclear’ studies are drawn from a common beta distribution. We illustrate these methods with a synthesis of 130 trials on four fluoride treatments and two control interventions for the prevention of dental caries in children. Whether there is adequate allocation concealment and/or blinding are considered as indicators of whether a study is at risk of bias. Bias adjustment reduces the estimated relative efficacy of the treatments and the extent of between-trial heterogeneity. [ABSTRACT FROM AUTHOR]

Eur J Clin Invest 2010; 40 (2): 172–182 Background Most clinical trials on medical interventions are sponsored by the industry. The choice of comparators shapes the accumulated evidence. We aimed to assess how often major companies sponsor trials that involve only their own products. Methods Studies were identified by searching ClinicalTrials.gov for trials registered in 2006. We focused on randomized trials involving the 15 companies that had sponsored the largest number of registered trials in ClinicalTrials.gov in that period. Results Overall, 577 randomized trials were eligible for analysis and 82% had a single industry sponsor [89% (166/187) of the placebo-control trials, 87% (91/105) of trials comparing different doses or ways of administration of the same intervention, and 78% (221/285) of other active control trials]. The compared intervention(s) belonged to a single company in 67% of the trials (89%, 81% and 47% in the three categories respectively). All 15 companies strongly preferred to run trials where they were the only industry sponsor or even the only owner of the assessed interventions. Co-sponsorship typically reflected co-ownership of the same intervention by both companies. Head-to-head comparison of different active interventions developed by different companies occurred in only 18 trials with two or more industry sponsors. Conclusions Each company generates a clinical research agenda that is strongly focused on its own products, while comparisons involving different interventions from different companies are uncommon. This diminishes the ability to understand the relative merits of different interventions for the same condition. [ABSTRACT FROM AUTHOR]

Bladder cancer is an increasingly important international public health problem, with over 330,000 new cases being diagnosed each year worldwide. In a systematic review and evidence synthesis, the authors investigated the joint effects of the N-acetyltransferase genes NAT1 and NAT2 and cigarette smoking on bladder carcinogenesis. Studies were identified through an exhaustive search of multiple electronic databases and reference lists and through direct contact with study authors and experts. Random-effects meta-analysis was used within a Bayesian framework to investigate individual effects of NAT1 and NAT2 acetylation status on bladder cancer risk, while a novel approach was used to investigate joint effects of these two genes with cigarette smoking. An increased risk of bladder cancer was found in NAT2 slow acetylators (odds ratio = 1.46, 95% credible interval (CI): 1.26, 1.68) but not in NAT1 fast acetylators (odds ratio = 1.01, 95% CI: 0.86, 1.22). The joint effects in the highest risk category (NAT2 slow acetylator, NAT1 fast acetylator, and current or ever cigarette smoking) as compared with the reference category (NAT2 fast acetylator, NAT1 slow acetylator, and never smoking) were associated with an odds ratio of 2.73 (95% CI: 1.70, 4.31). The importance of considering joint effects between genetic and environmental factors in the etiology of common complex diseases is underlined. [ABSTRACT FROM AUTHOR]

In 1997 the German MAK Commission set new general threshold limit values for dust. The procedure has recently been assessed (McLaughlin et al. 2001). One of the points raised was the use of inappropriate statistical methods. We want to address this point to a greater extent by discussing several alternatives implied by the already established threshold models, and we present results from a new approach that has been refined in the meantime: the use of the additive isotonic model. The underlined assumption of monotonicity regarding the dose-response relationship has been extensively investigated. One very flexible model, based on smoothing splines, shows in some of the samples a decline in the risk over a certain range of the exposure compared to the risk at baseline. Another approach with fractional polynomials and segmented regression lines shows that this result can be explained by chance. These methods show an increasing risk with increasing exposure. Additionally, permutation tests are used to prove the trend within the isotonic framework. The results from the additive isotonic model confirm previous assessments of the general threshold limit value. [ABSTRACT FROM AUTHOR]