Evidence-based preclinical medicine最新文献

{"title":"The relationship between risk of bias criteria, research outcomes, and study sponsorship in a cohort of preclinical thiazolidinedione animal studies: a meta-analysis","authors":"M. Abdel-Sattar,&nbsp;D. Krauth,&nbsp;A. Anglemyer,&nbsp;L. Bero","doi":"10.1002/ebm2.5","DOIUrl":"10.1002/ebm2.5","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>There is little evidence regarding the influence of conflicts of interest on preclinical research. This study examines whether industry sponsorship is associated with increased risks of bias and/or effect sizes of outcomes in published preclinical thiazolidinedione (TZD) studies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We identified preclinical TZD studies published between January 1, 1965, and November 14, 2012. Coders independently extracted information on study design criteria aimed at reducing bias, results for all relevant outcomes, sponsorship source and investigator financial ties from the 112 studies meeting the inclusion criteria. The average standardized mean difference (SMD) across studies was calculated for plasma glucose (efficacy outcome) and weight gain (harm outcome). In subgroup analyses, TZD outcomes were assessed by sponsorship source and risk of bias criteria.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Seven studies were funded by industry alone, 17 studies funded by both industry and non-industry, 49 studies funded by non-industry alone and 39 studies had no disclosures. None of the studies used sample size calculations, intention-to-treat analyses, blinding of investigators or concealment of allocation. Most studies reported favourable results (88 of 112) and conclusions (95 of 112) supporting TZD use. Efficacy estimates were significantly larger in six studies sponsored by industry alone (−3.41; 95% CI −5.21, −1.53; I²\u0000 = 93%) versus 42 studies sponsored by non-industry sources (−0.97; 95% CI −1.37, −0.56; I²\u0000 = 81%; p-value = 0.01). Harms estimates were significantly larger in four studies sponsored by industry alone (5.00; 95% CI 1.22, 8.77; I²\u0000 = 93%) versus 38 studies sponsored by non-industry sources (0.30; 95% CI −0.08, 0.68; I²\u0000 = 79%; p-value = 0.02). TZD efficacy and harms did not differ by disclosure of financial COIs or risks of bias.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Industry-sponsored TZD animal studies have exaggerated efficacy and harms outcomes compared with studies funded by non-industry sources. There was poor reporting of COIs.</p>\u0000 </section>\u0000 </div>","PeriodicalId":90826,"journal":{"name":"Evidence-based preclinical medicine","volume":"1 1","pages":"11-20"},"PeriodicalIF":0.0,"publicationDate":"2015-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/ebm2.5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33020784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review and meta-analysis of gene therapy in animal models of cerebral glioma: why did promise not translate to human therapy?","authors":"T. C. Hirst,&nbsp;H. M. Vesterinen,&nbsp;S. Conlin,&nbsp;K. J. Egan,&nbsp;A. Antonic,&nbsp;A. Lawson McLean,&nbsp;M. R. Macleod,&nbsp;R. Grant,&nbsp;P. M. Brennan,&nbsp;E. S. Sena,&nbsp;I. R. Whittle","doi":"10.1002/ebm2.6","DOIUrl":"https://doi.org/10.1002/ebm2.6","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The development of therapeutics is often characterized by promising animal research that fails to translate into clinical efficacy; this holds for the development of gene therapy in glioma. We tested the hypothesis that this is because of limitations in the internal and external validity of studies reporting the use of gene therapy in experimental glioma.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>We systematically identified studies testing gene therapy in rodent glioma models by searching three online databases. The number of animals treated and median survival were extracted and studies graded using a quality checklist. We calculated median survival ratios and used random effects meta-analysis to estimate efficacy. We explored effects of study design and quality and searched for evidence of publication bias.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified 193 publications using gene therapy in experimental glioma, including 6,366 animals. Overall, gene therapy improved median survival by a factor of 1.60 (95% CI 1.53–1.67). Study quality was low and the type of gene therapy did not account for differences in outcome. Study design characteristics accounted for a significant proportion of between-study heterogeneity. We observed similar findings in a data subset limited to the most common gene therapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>As the dysregulation of key molecular pathways is characteristic of gliomas, gene therapy remains a promising treatment for glioma. Nevertheless, we have identified areas for improvement in conduct and reporting of studies, and we provide a basis for sample size calculations. Further work should focus on genes of interest in paradigms recapitulating human disease. This might improve the translation of such therapies into the clinic.</p>\u0000 </section>\u0000 </div>","PeriodicalId":90826,"journal":{"name":"Evidence-based preclinical medicine","volume":"1 1","pages":"21-33"},"PeriodicalIF":0.0,"publicationDate":"2015-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/ebm2.6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72158935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anti-inflammatory compounds to reduce infarct size in large-animal models of myocardial infarction: A meta-analysis","authors":"G.P.J. van Hout,&nbsp;S.J. Jansen of Lorkeers,&nbsp;K.E. Wever,&nbsp;E.S. Sena,&nbsp;W.W. van Solinge,&nbsp;P.A. Doevendans,&nbsp;G. Pasterkamp,&nbsp;S.A.J. Chamuleau,&nbsp;I.E. Hoefer","doi":"10.1002/ebm2.4","DOIUrl":"https://doi.org/10.1002/ebm2.4","url":null,"abstract":"<div>\u0000 \u0000 <p>Targeting the inflammatory response after myocardial infarction (MI) could potentially prevent infarct expansion, resulting in a preservation of cardiac function. Despite extensive testing in large-animal models of MI, anti-inflammatory therapeutics are not incorporated in daily clinical practice. Methodological review of the literature describing the effects of anti-inflammatory compounds in large-animal models of MI may provide useful insights into the reasons for the translational failure from preclinical to clinical studies. Moreover, systematic review of these preclinical studies may allow us to determine which anti-inflammatory agents have the greatest potential to successfully treat MI in the clinic and guide which preclinical setting appears most appropriate to test these future treatment strategies in. The current systematic review protocol provides a detailed description of the design of this systematic review of studies investigating the effects of anti-inflammatory compounds in large-animal models of MI.</p>\u0000 </div>","PeriodicalId":90826,"journal":{"name":"Evidence-based preclinical medicine","volume":"1 1","pages":"4-10"},"PeriodicalIF":0.0,"publicationDate":"2015-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/ebm2.4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72158934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Raising standards for preclinical research","authors":"","doi":"10.1111/ebm2.3","DOIUrl":"https://doi.org/10.1111/ebm2.3","url":null,"abstract":"<p>Systematic review and meta-analysis are powerful analytical tools. The Cochrane Collaboration, formed in 1993, provides an excellent example of the use of these tools to gather the best evidence regarding the efficacy of interventions in clinical medicine. The use of these tools however is not widespread in preclinical science. Thus Evidence-Based Preclinical Medicine (EBPM) is a new online peer-reviewed open access journal designed to provide a vehicle which fosters the systematic capture and rigorous analysis of all available basic science data on questions relevant to human health. By doing so we aim to raise the standards of preclinical research and improve the efficiency with which preclinical data is translated into improvements in human health.</p><p>The analysis of industrial, agricultural or environmental toxicology, processes of drug discovery and evaluation, disease risk factor modelling and pre- and post-disease behavioural modification as well as early discovery science are all areas where systematic capture of all available data will accelerate our ability to improve human health. The application of rigorous analytical techniques which can give a realistic appreciation of the quality, breadth and potential importance of the available evidence will help researchers decide which hypotheses should be explored further, identify the presence and likely impact of confounding biases and will help health professionals decide which will have an impact on people.</p><p>Most scientists would like to believe that the systems required for these aims are already in place. However, the explosion in the volume of available data makes reliance on traditional systems untenable.</p><p>The problems start with the way we portray science and the aspirations this engenders. In the mass media, text books and popular histories of science and medicine the process of discovery is commonly portrayed a series of Eureka moments. Giant leaps forward made by the greatest minds of an era. But this is not the process. Around the world teams of scientists nibble away at a problem, new ideas are circulated and considered and experiments designed and performed. Many ideas and experiments are dead ends and lead nowhere. But since we learn by our mistakes, knowing how things don't happen refines our knowledge base and nudges us ever closer to the truth by allowing more scientists to focus on the threads that do reveal the true pattern of life.</p><p>Two of the most famous quotes in science speak directly to these issues. Louis Pasteur's “Chance favours only the prepared mind” makes it clear that you have to understand a field if you are to contribute to it. Isaac Newton's “If I have seen further it is by standing on the shoulders of giants” is perhaps more important because it also acknowledges that science is an incremental process. Only a fortunate few are in the right place at the right time and with the right education and knowledge base to finally understand a la","PeriodicalId":90826,"journal":{"name":"Evidence-based preclinical medicine","volume":"1 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2014-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/ebm2.3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72169498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}