title: Level of evidence and therapeutic evaluation: need for more thoughts.
abstract: The practice of evidence-based medicine requires a tool to assess and discriminate available data based on objective grounds, thus facilitating access to reliable information. The level of evidence, conceptually and practically embedded in scientific activity, allows comparing the results from multiple studies testing an identical hypothesis along the lines of at least two dimensions. The first dimension deals with the design of the study, i.e. the extent to which bias is avoided or managed, the second with the quality of incorporated data. A third dimension specific to therapeutic evaluation focuses on the clinical relevance of the tested hypothesis. The concern of the final user of the information is thus put to the fore. Indeed, a general practitioner will be interested in the benefit for its patients whereas the concern of a biologist might significantly diverge from the former matter. The bulk of existing scales of level of evidence concentrate on methodology. Some may include the second dimension but none embrace the three of them. Seldom considered are matters regarding reproducibility and procedure. This is all the more unfortunate as reproducibility is a cornerstone of scientific progress. Moreover, scales used for overviews fail to take into account the methodology designed to produce the synthesis. Inconsistent existing scales prevent the emergence of a generally agreed standard. Therefore, there is a need to further specify the concept of level of evidence in therapy evaluation and design scales encompassing the three above-mentioned dimensions: methodology of experiment, quality of data, and clinical relevance of the primary criterion.
authors.affiliation: Service de Biostatistique, Centre Hospitalier Lyon Sud, Lyon, France.
authors.forename: Nadine
authors.initials: N
authors.lastname: Bossard
authors.forename: François-Henri
authors.initials: FH
authors.lastname: Boissel
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Boissel
mesh_terms: D019317:Evidence-Based Medicine / Q000379:methods*; D006801:Humans; D012107:Research Design