Literature DB >> 30570169

Assessing the Evidence in Evidence-Based Medicine.

Ronald L Koretz1,2.   

Abstract

Evidence-based medicine (EBM) has become a fixture in today's medical practice. Evidence consists of memorialized observations and should be contrasted with dogmatic pronouncements and/or hypotheses. Evidence has varying degrees of reliability. The randomized clinical trial (RCT) or a systematic review of RCTs is accorded the highest level of credibility and expert opinion the lowest. This ranking reflects the internal validity (degree to which factors in the study interfere with the gathering or interpretation of the observations) of the study design; more valid designs are more credible. The provision of healthcare requires an almost constant assessment of evidence. In so doing, there are a number of principles of EBM that need to be kept in mind: Association can never prove causation. Various methodologic biases can influence conclusions made in both RCTs and observational studies. The strength of RCTs is in the elimination of confounding bias. Surrogate outcomes must be validated in RCTs assessing how they are changed compared with the clinical outcomes. Subgroup analyses cannot prove hypotheses although they can generate them. P < 0.05 is not the same as truth. Type I errors are more likely to occur when multiple analyses are performed, when trials are prematurely stopped for perceived benefit when there was no a priori plan to do so, or in small papers with dramatic results that are selectively published. The failure to find a difference does not mean that no difference exists (type II error).
© 2018 American Society for Parenteral and Enteral Nutrition.

Entities:  

Keywords:  P value; bias; critical thinking; evidence-based medicine; research design; statistics; subgroup analysis; surrogate outcome; type I error; type II error

Mesh:

Year:  2018        PMID: 30570169     DOI: 10.1002/ncp.10227

Source DB:  PubMed          Journal:  Nutr Clin Pract        ISSN: 0884-5336            Impact factor:   3.080


  5 in total

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Authors:  Maiken B Ravn; Kirsten S Petersen; Jette Thuesen
Journal:  J Aging Res       Date:  2019-06-02

2.  How feasible is it to abandon statistical significance? A reflection based on a short survey.

Authors:  Fredi Alexander Diaz-Quijano; Fernando Morelli Calixto; José Mário Nunes da Silva
Journal:  BMC Med Res Methodol       Date:  2020-06-03       Impact factor: 4.615

3.  Construction of Clinical Pathway Information Management System under the Guidance of Evidence-Based Medicine.

Authors:  Xinyu Wang; Jie Chen; Fang Peng; Jingtai Lu
Journal:  J Healthc Eng       Date:  2021-12-02       Impact factor: 2.682

4.  From registration, protocol to report: are COVID-19-related RCTs in mainland China consistent? A systematic review of clinical trial registry and literature.

Authors:  Yu Chen; Ruiqing Yan
Journal:  BMJ Open       Date:  2022-07-21       Impact factor: 3.006

5.  Strength of clinical evidence leading to approval of novel cancer medicines in Europe: A systematic review and data synthesis.

Authors:  Alberto Farina; Federico Moro; Frederick Fasslrinner; Annahita Sedghi; Miluska Bromley; Timo Siepmann
Journal:  Pharmacol Res Perspect       Date:  2021-08
  5 in total

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