Systematic reviews. Some examples.

Reviewing the literature is a scientific inquiry that needs a clear design to preclude bias. It is a real enterprise if one aims at completeness of the literature on a certain subject. Going through refereed English language journals is not enough. On line databases are helpful, but mainly as a starting point. This article gives examples of systematic reviews on vitamin C and the common cold, pyridoxine against the premenstrual syndrome, homeopathy, and physiotherapy.     

Systematic reviews: a primer for plastic surgery research

Clinicians rely on review articles to keep current with the rapid accumulation of medical and surgical literature. Traditional expert reviews, however, often suffer from inherent personal biases and may not reflect a true synthesis of the existing literature on a particular subject. Systematic reviews are structured, scientific articles that address the shortcomings of traditional reviews by adhering to strict, reproducible methods and recommended guidelines. The methods are designed to eliminate possible sources of bias, ensure as complete a review of the existing literature as possible, and present the results in a way that is useful for its intended audience. Systematic reviews may at times include a quantitative synthesis of the available data in the form of a meta-analysis. Meta-analysis is a statistical tool for combining the numerical results of separate studies to obtain a summary outcome with increased precision due to the larger, combined number of patients. Meta-analyses may be particularly helpful when individual study results are conflicting and the existing literature is inconclusive. The validity of meta-analysis, however, is highly dependent on the quality of data available in the literature. In its strictest form, meta-analysis is used to combine data from only randomized controlled clinical trials. Because randomized controlled clinical trials are infrequently performed in plastic surgery research, this article will focus on systematic reviews to provide the readers with a useful guide in performing this field of study.     

Systematic reviews and meta-analyses on treatment of asthma: critical evaluation

ObjectiveTo evaluate the clinical, methodological, and reporting aspects of systematic reviews and meta-analyses on the treatment of asthma and to compare those published by the Cochrane Collaboration with those published in paper based journals.DesignAnalysis of studies identified from Medline, CINAHL, HealthSTAR, EMBASE, Cochrane Library, personal collections, and reference lists.StudiesArticles describing a systematic review or a meta-analysis of the treatment of asthma that were published as a full report, in any language or format, in a peer reviewed journal or the Cochrane Library.Results50 systematic reviews and meta-analyses were included. More than half were published in the past two years. Twelve reviews were published in the Cochrane Library and 38 were published in 22 peer reviewed journals. Forced expiratory volume in one second was the most frequently used outcome, but few reviews evaluated the effect of treatment on costs or patient preferences. Forty reviews were judged to have serious or extensive flaws. All six reviews associated with industry were in this group. Seven of the 10 most rigorous reviews were published in the Cochrane Library.ConclusionsMost reviews published in peer reviewed journals or funded by industry have serious methodological flaws that limit their value to guide decisions. Cochrane reviews are more rigorous and better reported than those published in peer reviewed journals.     

Systematic reviews of animal experiments demonstrate poor human clinical and toxicological utility

The assumption that animal models are reasonably predictive of human outcomes provides the basis for their widespread use in toxicity testing and in biomedical research aimed at developing cures for human diseases. To investigate the validity of this assumption, the comprehensive Scopus biomedical bibliographic databases were searched for published systematic reviews of the human clinical or toxicological utility of animal experiments. In 20 reviews in which clinical utility was examined, the authors concluded that animal models were either significantly useful in contributing to the development of clinical interventions, or were substantially consistent with clinical outcomes, in only two cases, one of which was contentious. These included reviews of the clinical utility of experiments expected by ethics committees to lead to medical advances, of highly-cited experiments published in major journals, and of chimpanzee experiments--those involving the species considered most likely to be predictive of human outcomes. Seven additional reviews failed to clearly demonstrate utility in predicting human toxicological outcomes, such as carcinogenicity and teratogenicity. Consequently, animal data may not generally be assumed to be substantially useful for these purposes. Possible causes include interspecies differences, the distortion of outcomes arising from experimental environments and protocols, and the poor methodological quality of many animal experiments, which was evident in at least 11 reviews. No reviews existed in which the majority of animal experiments were of good methodological quality. Whilst the effects of some of these problems might be minimised with concerted effort (given their widespread prevalence), the limitations resulting from interspecies differences are likely to be technically and theoretically impossible to overcome. Non-animal models are generally required to pass formal scientific validation prior to their regulatory acceptance. In contrast, animal models are simply assumed to be predictive of human outcomes. These results demonstrate the invalidity of such assumptions. The consistent application of formal validation studies to all test models is clearly warranted, regardless of their animal, non-animal, historical, contemporary or possible future status. Likely benefits would include, the greater selection of models truly predictive of human outcomes, increased safety of people exposed to chemicals that have passed toxicity tests, increased efficiency during the development of human pharmaceuticals and other therapeutic interventions, and decreased wastage of animal, personnel and financial resources. The poor human clinical and toxicological utility of most animal models for which data exists, in conjunction with their generally substantial animal welfare and economic costs, justify a ban on animal models lacking scientific data clearly establishing their human predictivity or utility.     

Systematic reviews and meta-analyses of preclinical studies: publication bias in laboratory animal experiments

In 2006, Peters et al. identified 86 systematic reviews (SRs) of laboratory animal experiments (LAEs). They found 46 LAE meta-analyses (MAs), often of poor quality. Six of these 46 MAs tried to assess publication bias. Publication bias is the phenomenon of an experiment's results determining its likelihood of publication, often over-representing positive findings. As such, publication bias is the Achilles heel of any SR. Since researchers increasingly become aware of the fact that SRs directly support the 'three Rs', we expect the number of SRs of LAEs will sharply increase. Therefore, it is useful to see how publication bias is dealt with. Our objective was to identify all SRs and MAs of LAEs where the purpose was to inform human health published between July 2005 and 2010 with special attention to MAs' quality features and publication bias. We systematically searched Medline, Embase, Toxline and ScienceDirect from July 2005 to 2010, updating Peters' review. LAEs not directly informing human health or concerning fundamental biology were excluded. We found 2780 references of which 163 met the inclusion criteria: 158 SRs, of which 30 performed an MA, and five MAs without an SR. The number of SRs roughly doubled every three years since 1997. The number of MAs roughly doubled every five years since 1999. Compared with before July 2005, more MAs were preceded by SR and reported on (quality) features of included studies and heterogeneity. A statistically significant proportion of MAs considered publication bias (26/35) and tried to formally assess it (21/35).     

Systematic comparison of family history and polygenic risk across 24 common diseases

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