Dataset Information

Visualizing the evolution of evidence: Cumulative network meta-analyses of new generation antidepressants in the last 40?years.

ABSTRACT: It is often challenging to present the available evidence in a timely and comprehensible manner. We aimed to visualize the evolution of evidence about antidepressants for depression by conducting cumulative network meta-analyses (NMAs) and to examine whether it could have helped the selection of optimal drugs. We built a Shiny web application that performs and presents cumulative NMAs based on R netmeta. We used a comprehensive dataset of double-blind randomized controlled trials of 21 antidepressants in the acute treatment of major depression. The primary outcomes were efficacy (treatment response) and acceptability (all-cause discontinuation), and treatment effects were summarized via odds ratios. We evaluated the confidence in evidence using the CINeMA (Confidence in Network Meta-Analysis) framework for a series of consecutive NMAs. Users can change several conditions for the analysis, such as the period of synthesis, among the others. We present the league tables and two-dimensional plots that combine efficacy, acceptability and level of confidence in the evidence together, for NMAs conducted in 1990, 1995, 2000, 2005, 2010, and 2016. They reveal that through the past four decades, newly approved drugs often showed initially exaggerated results, which tended to diminish and stabilize after approximately a decade. Over the years, the drugs with relative superiority changed dramatically; but as the evidence network grew larger and better connected, the overall confidence improved. The Shiny app visualizes how evidence evolved over years, emphasizing the need for a careful interpretation of relative effects between drugs, especially for the potentially amplified performance of newly approved drugs. HIGHLIGHTS: Network meta-analysis is considered to be a proper way of demonstrating the available evidence, since it allows comparisons between multiple interventions, and has been proved to be statistically powerful. It is challenging to present the voluminous results of NMA in an efficient and comprehendible manner. Evidence evolution based on the relatively new method NMA has not been investigated yet. The results of NMA should not only include the effects but also the confidence in the evidence, which can help interpret the findings appropriately. Effective use of rapidly developing statistical analysis and presentation tools such as Shiny package in R, may facilitate and simplify the visualization of NMA output. We should stay conservative towards new drugs, as their performance was often shown to be exaggerated initially, and it took time to become stable.

SUBMITTER: Luo Y

PROVIDER: S-EPMC7818396 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Visualizing the evolution of evidence: Cumulative network meta-analyses of new generation antidepressants in the last 40 years.

Luo Yan Y Chaimani Anna A Furukawa Toshi A TA Kataoka Yuki Y Ogawa Yusuke Y Cipriani Andrea A Salanti Georgia G

Research synthesis methods 20200525 1

It is often challenging to present the available evidence in a timely and comprehensible manner. We aimed to visualize the evolution of evidence about antidepressants for depression by conducting cumulative network meta-analyses (NMAs) and to examine whether it could have helped the selection of optimal drugs. We built a Shiny web application that performs and presents cumulative NMAs based on R netmeta. We used a comprehensive dataset of double-blind randomized controlled trials of 21 antidepre ...[more]

PMID: 32352639

Similar Datasets

Project description:IntroductionDepressive disorders are the most common, burdensome and costly mental disorders. Their treatments have developed through the past decades and we now have more than a dozen new generation antidepressants, while a series of guidelines have been published to provide recommendations over the years. However, there still may exist important gaps in this evidence synthesis and implementation process. Systematic reviews may not have been conducted in the most unbiased, informative and timely manners; guidelines may not have reflected the most up-to-date evidence; clinicians may not have changed their clinical decision-makings in accordance with the relevant evidence. The aim of this study is to examine the gaps between the ideally synthesised evidence, guideline recommendations and real-world clinical practices in the prescription of new generation antidepressants for major depression through the past three decades.Methods and analysisWe will conduct cumulative network meta-analyses (cNMAs) based on the comprehensive systematic review which has identified published and unpublished head-to-head randomised controlled trials comparing the following antidepressants in the acute phase treatment of major depression: agomelatine, amitriptyline, bupropion, citalopram, clomipramine, desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, milnacipran, mirtazapine, nefazodone, paroxetine, reboxetine, sertraline, trazodone, venlafaxine, vilazodone and vortioxetine. The primary outcomes will be the proportions of patients who responded (efficacy) and who withdrew from treatment for any reasons (acceptability). We will conduct a random effects cNMA to synthesise evidence and obtain a comprehensive ranking of all new generation antidepressants based on their surface under the cumulative ranking curves. We will identify series of international clinical practice guidelines for the treatment of major depression of adults and summarise their recommendations. We will estimate real-world prescription patterns of antidepressants in the nationally representative samples in USA in the Medical Expenditure Panel Survey. We will compare and evaluate the gaps between the rankings according to cNMAs conducted at 5-year intervals between 1990 and 2015, recommendations in guidelines published in the ensuing 5?years and actual practices thereafter.Ethics and disseminationThis review does not require ethical approval. We will disseminate our findings through publications in peer-reviewed journals and presentations at conferences.Trial registration numberUMIN000031898.

Project description:Gastric cancer (GC) is the second leading cause of cancer death in China. It is well known that Cixian in Hebei Province is one of the highest risk areas of GC in China and worldwide. This study aims to accurate assessment of GC burden and trend in high-risk area (Hebei Province) from 1973 to 2013. The authors analyzed GC data from 21 population-based cancer registries which represented 15.25% of the entire population of Hebei Province. The collected data were stratified by 5-year age groups, gender, and area. Mortality of GC was extracted from national death surveys from 1973 to 1975, 1990 to 1992, 2004 to 2005, and 2011 to 2013. Trend analysis (1988-2013) in a high-risk area (Cixian) used the Joinpoint Model. The age-period-cohort model was used to estimate the effects of age, period, and birth cohort in GC incidence in Cixian from 1988 to 2013. The crude incidence of GC in 2011 to 2013 was 40.37/100,000 (57.53/100,000 in males and 22.55/100,000 in females). The corresponding age-standardized rate by world age-standard population was 32.18/100,000 (48.87/100,000 in males and 17.53/100,000 in females), which was 2.66-fold (2.81-fold in male and 2.34-fold in female) higher than that in the world (12.1/100,000, 17.4/100,000 in males and 7.5/100,000 in females). Males in rural areas had the highest incidence, with an age-standardized rate of 70.51/100,000. Gastric cardia cancer was primary anatomical subsite which accounting for 59.59% in GC, followed by gastric corpus (13.92%), gastric antrum (11.43%), gastric fundus (4.99%), and overlapping lesion of gastric (4.17%). The age-standardized rate of mortality from GC displayed a significant downward trend (P = 0.019) in Hebei Province from the 1990s (31.44/100,000) to the 2010s (24.63/100,000). In Cixian, the incidence of GC rose from 1988 (38.25/100,000) to 2009 (65.11/100,000). Cixian, where population-based screening of upper gastrointestinal cancer was performed, experienced the increasing rate of GC from 2000 (37.59/100,000) to 2009 (65.11/100,000) and then had a sharp decrease from 2009 to 2013 (55.30/100,000), with annual percentage change of -6.69%. Gastric cardia cancer had an increasing trend from 1988 (6.88/100,000) to 2013 (26.56/100,000). Both age and birth cohort effects played important roles in these changes. In conclusion, males in rural areas had the highest risk of GC. GC mortality rate decreased from the 1990s in Hebei Province. Endoscopic screening project for GC is an effective method of controlling the disease.

Project description:Genome-scale metabolic network reconstructions (GENREs) are valuable tools for understanding microbial metabolism. The process of automatically generating GENREs includes identifying metabolic reactions supported by sufficient genomic evidence to generate a draft metabolic network. The draft GENRE is then gapfilled with additional reactions in order to recapitulate specific growth phenotypes as indicated with associated experimental data. Previous methods have implemented absolute mapping thresholds for the reactions automatically included in draft GENREs; however, there is growing evidence that integrating annotation evidence in a continuous form can improve model accuracy. There is a need for flexibility in the structure of GENREs to better account for uncertainty in biological data, unknown regulatory mechanisms, and context-specificity associated with data inputs. To address this issue, we present a novel method that provides a framework for quantifying combined genomic, biochemical, and phenotypic evidence for each biochemical reaction during automated GENRE construction. Our method, Constraint-based Analysis Yielding reaction Usage across metabolic Networks (CANYUNs), generates accurate GENREs with a quantitative metric for the cumulative evidence for each reaction included in the network. The structuring of CANYUNs allows for the simultaneous integration of three data inputs while maintaining all supporting evidence for biochemical reactions that may be active in an organism. CANYUNs is designed to maximize the utility of experimental and annotation datasets and to ultimately assist in the curation of the reference datasets used for the automatic construction of metabolic networks. We validated CANYUNs by generating an E. coli K-12 model and compared it to the manually curated reconstruction iML1515. Finally, we demonstrated the use of CANYUNs to build a model by generating an E. coli Nissle CANYUNs model using novel phenotypic data that we collected. This method may address key challenges for the procedural construction of metabolic networks by leveraging uncertainty and redundancy in biological data.

Project description:Veterinary dentistry and oral surgery are relatively new clinical disciplines that have rapidly evolved in the last few decades. Although clinical standards of care are supported by a growing body of literature, the extent to which peer-reviewed, evidence-based studies have contributed to advancing the practice of dentistry and oral surgery has not been assessed. The purpose of this study was to survey literature on the clinical practice of small animal dentistry and oral surgery published over the past 40 years to evaluate the levels of evidence over time, authorship affiliation, funding, and clinical subdisciplines within the field. A literature search was conducted in PubMed and the identified articles were screened for inclusion. A total of 1,083 articles were included for final analysis. Three reviewers independently assessed and assigned each article to one of nine predetermined study design categories. Systematic reviews and meta-analyses were considered the highest level of evidence, whereas expert opinion and experimental (ex vivo, in vitro, or in silico) studies were deemed the lowest levels of evidence. For statistical analysis and interpretation, study type was dichotomized into high evidence designs from which causal inference and/or associations could be derived, and low evidence designs which were purely descriptive or non-clinical experiments. No statistically significant difference in the distribution of study type was seen over time, with the majority of research in the last 5 years being largely at high risk of bias and descriptive in nature: 80.6% of articles published between 2014 and 2019 were assigned to the low evidence design tier. The type of study was found to differ by author affiliation: high evidence study designs were found more often than expected when author affiliation was multi-institutional or industrial, whereas private practice authorship was underrepresented in the high evidence design tier. To meet the increasing demand for evidence-based studies on the practice of dentistry and oral surgery in dogs and cats, researchers are encouraged to consider study design when testing hypotheses to improve the quality of research.

Dataset Information

Visualizing the evolution of evidence: Cumulative network meta-analyses of new generation antidepressants in the last 40?years.

Publications

Visualizing the evolution of evidence: Cumulative network meta-analyses of new generation antidepressants in the last 40 years.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets