Are citations from clinical trials evidence of higher impact research? An analysis of ClinicalTrials.gov

An important way in which medical research can translate into improved health outcomes is by motivating or influencing clinical trials that eventually lead to changes in clinical practice. Citations from clinical trials records to academic research may therefore serve as an early warning of the likely future influence of the cited articles. This paper partially assesses this hypothesis by testing whether prior articles referenced in ClinicalTrials.gov records are more highly cited than average for the publishing journal. The results from four high profile general medical journals support the hypothesis, although there may not be a cause-and effect relationship. Nevertheless, it is reasonable for researchers to use citations to their work from clinical trials records as partial evidence of the possible long-term impact of their research

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Systematic review and meta-analysis of the efficacy and safety of amfepramone and mazindol as a monotherapy for the treatment of obese or overweight patients

© 2017 CLINICS. The aim of this study was to evaluate efficacy and safety of amfepramone, fenproporex and mazindol as a monotherapy for the treatment of obese or overweight patients. A systematic review of primary studies was conducted, followed by a direct meta-analysis (random effect) and mixed treatment comparison. Medline and other databases were searched. Heterogeneity was explored through I2 associated with a p-value. Of 739 identified publications, 25 were included in the meta-analysis. The global evaluation of Cochrane resulted in 19 studies with a high level of bias and six with unclear risk. Due to the lack of information in primary studies, direct meta-analyses were conducted only for amfepramone and mazindol. Compared to placebo, amfepramone resulted in higher weight loss in the short-term (<180 days; mean difference (MD) -1.281 kg; p<0.05; I2: 0.0%; p=0.379) and long-term (≥180 days; MD -6.518 kg; p<0.05; I2: 0.0%; p=0.719). Only studies with long-term follow up reported efficacy in terms of abdominal circumference and 5-10% weight reduction. These results corroborated the finding that the efficacy of amfepramone is greater than that of placebo. Treatment with mazindol showed greater short-term weight loss than that with placebo (MD -1.721 kg; p<0.05; I2: 0.9%; p=0.388). However, metabolic outcomes were poorly described, preventing a meta-analysis. A mixed treatment comparison corroborated the direct meta-analysis. Considering the high level of risk of bias and the absence of important published outcomes for anti-obesity therapy assessments, this study found that the evaluated drugs showed poor evidence of efficacy in the treatment of overweight and obese patients. Robust safety data were not identified to suggest changes in their regulatory status

Diethylpropion and mazindol: An end to the discussion?

Antiobesity pharmacotherapy remains the main point of disagreement among both scientists and regulators. This is probably due to small sample sizes, high levels of heterogeneity, and low methodological quality. For many years, Brazil was one of the largest consumers of appetite suppressants worldwide, with evidence of irrational use of this drug class. Therefore, the country was the scene of a debate that divided the Brazilian Health Surveillance Agency (Anvisa - Agência Nacional de Vigilância Sanitáia) and medical societies over the maintenance record of diethylpropion, mazindol and fenproporex. In this context, this commentary presents new arguments to contribute to the discussion, as well as recommendations for future studies