A hierarchy of evidence, comprising levels of evidence (LOEs), that is, evidence levels (ELs), is a heuristic used to rank the relative strength of results obtained from experimental research, especially medical research. There is broad agreement on the relative strength of large-scale, epidemiological studies. More than 80 different hierarchies have been proposed for assessing medical evidence. The design of the study (such as a case report for an individual patient or a blinded randomized controlled trial) and the endpoints measured (such as survival or quality of life) affect the strength of the evidence. In clinical research, the best evidence for treatment efficacy is mainly from meta-analyses of randomized controlled trials (RCTs). Systematic reviews of completed, high-quality randomized controlled trials – such as those published by the Cochrane Collaboration – rank the same as systematic review of completed high-quality observational studies in regard to the study of side effects. Evidence hierarchies are often applied in evidence-based practices and are integral to evidence-based medicine (EBM). In 2014, Jacob Stegenga defined a hierarchy of evidence as "rank-ordering of kinds of methods according to the potential for that method to suffer from systematic bias". At the top of the hierarchy is a method with the most freedom from systemic bias or best internal validity relative to the tested medical intervention's hypothesized efficacy. In 1997, Greenhalgh suggested it was "the relative weight carried by the different types of primary study when making decisions about clinical interventions". The National Cancer Institute defines levels of evidence as "a ranking system used to describe the strength of the results measured in a clinical trial or research study. The design of the study [...] and the endpoints measured [...] affect the strength of the evidence." A large number of hierarchies of evidence have been proposed. Similar protocols for evaluation of research quality are still in development.

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