Literature DB >> 11297118

Evidence-based medicine: how good is the evidence?

D S Celermajer1.   

Abstract

The "evidence" in EBM must be of high quality in order to be useful, but this is not always the case. Even the "gold standard" of evidence-based medicine, the randomised clinical trial, is bedevilled by low inclusion rates and potentially important recruitment biases. "Real world" trials often do not give the same results as these highly artificial controlled clinical studies. Meta-analysis, the next most important level of evidence in EBM, may be unreliable, sometimes giving different results to subsequent large randomised trials. There is a bias in the hypotheses tested in large clinical trials, as the costs involved are usually covered by commercially interested companies. For this reason, trials of non-patentable compounds or therapies of no commercial interest may not be performed. The process of journal review and publication is capricious, slow and may have a selection bias towards positive studies, meaning that communication channels for the "evidence" are often unsatisfactory. For many rarer conditions and situations, there is simply no "high level" evidence, such as in paediatrics and subspecialty surgery.

Mesh:

Year:  2001        PMID: 11297118     DOI: 10.5694/j.1326-5377.2001.tb143274.x

Source DB:  PubMed          Journal:  Med J Aust        ISSN: 0025-729X            Impact factor:   7.738


  4 in total

1.  Expert agreed standards for the selection and development of cancer support group leaders: an online reactive Delphi study.

Authors:  Amanda Pomery; Penelope Schofield; Miranda Xhilaga; Karla Gough
Journal:  Support Care Cancer       Date:  2017-07-21       Impact factor: 3.603

2.  Evidence-based medicine: the fourth revolution in American medicine?

Authors:  Kevin C Chung; Ashwin N Ram
Journal:  Plast Reconstr Surg       Date:  2009-01       Impact factor: 4.730

Review 3.  A systematic evaluation of the quality of meta-analyses in the critical care literature.

Authors:  Anthony Delaney; Sean M Bagshaw; Andre Ferland; Braden Manns; Kevin B Laupland; Christopher J Doig
Journal:  Crit Care       Date:  2005-09-09       Impact factor: 9.097

Review 4.  Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.

Authors:  J Geoffrey Chase; Jean-Charles Preiser; Jennifer L Dickson; Antoine Pironet; Yeong Shiong Chiew; Christopher G Pretty; Geoffrey M Shaw; Balazs Benyo; Knut Moeller; Soroush Safaei; Merryn Tawhai; Peter Hunter; Thomas Desaive
Journal:  Biomed Eng Online       Date:  2018-02-20       Impact factor: 2.819

  4 in total

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