Иерархии доказательств в научных исследованиях

Heuristic ranking science research results

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. So far, the available protocols pay relatively little attention to whether outcome research is relevant to efficacy (the outcome of a treatment performed under ideal conditions) or to effectiveness (the outcome of the treatment performed under ordinary, expectable conditions).

A protocol for evaluation of research quality was suggested by a report from the Centre for Reviews and Dissemination, prepared by Khan et al. and intended as a general method for assessing both medical and psychosocial interventions. While strongly encouraging the use of randomized designs, this protocol noted that such designs were useful only if they met demanding criteria, such as true randomization and concealment of the assigned treatment group from the client and from others, including the individuals assessing the outcome. The Khan et al. protocol emphasized the need to make comparisons on the basis of "intention to treat" in order to avoid problems related to greater attrition in one group. The Khan et al. protocol also presented demanding criteria for nonrandomized studies, including matching of groups on potential confounding variables and adequate descriptions of groups and treatments at every stage, and concealment of treatment choice from persons assessing the outcomes. This protocol did not provide a classification of levels of evidence, but included or excluded treatments from classification as evidence based depending on whether the research met the stated standards.

An assessment protocol has been developed by the U. S. National Registry of Evidence Based Practices and Programs (NREPP). Evaluation under this protocol occurs only if an intervention has already had one or more positive outcomes, with a probability of less than .05, reported, if these have been published in a peer reviewed journal or an evaluation report, and if documentation such as training materials has been made available. The NREPP evaluation, which assigns quality ratings from 0 to 4 to certain criteria, examines reliability and validity of outcome measures used in the research, evidence for intervention fidelity (predictable use of the treatment in the same way every time), levels of missing data and attrition, potential confounding variables, and the appropriateness of statistical handling, including sample size.

In 1988, the United States Preventive Services Task Force (USPSTF) came out with its guidelines based on the CTF using the same 3 levels, further subdividing level II. Level I: Evidence obtained from at least one properly designed randomized controlled trial. Level II 1: Evidence obtained from well designed controlled trials without randomization. Level II 2: Evidence obtained from well designed cohort or case control analytic studies, preferably from more than one center or research group. Level II 3: Evidence obtained from multiple time series designs with or without the intervention. Dramatic results in uncontrolled trials might also be regarded as this type of evidence. Level III: Opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees. Over the years many more grading systems have been described.

In 2007, the World Cancer Research Fund grading system described 4 levels: Convincing, probable, possible and insufficient evidence. All Global Burden of Disease Studies have used it to evaluate epidemiologic evidence supporting causal relationships.

In 1995 Wilson et al., in 1996 Hadorn et al. and in 1996 Atkins et al. have described and defended various types of grading systems.

In 2011, a systematic review of the critical literature found 3 kinds of criticism: procedural aspects of EBM (especially from Cartwright, Worrall and Howick), greater than expected fallibility of EBM (Ioaanidis and others), and EBM being incomplete as a philosophy of science (Ashcroft and others). Rawlins and Bluhm note, that EBM limits the ability of research results to inform the care of individual patients, and that to understand the causes of diseases both population level and laboratory research are necessary. EBM hierarchy of evidence does not take into account research on the safety and efficacy of medical interventions. RCTs should be designed "to elucidate within group variability, which can only be done if the hierarchy of evidence is replaced by a network that takes into account the relationship between epidemiological and laboratory research"

The hierarchy of evidence produced by a study design has been questioned, because guidelines have "failed to properly define key terms, weight the merits of certain non randomized controlled trials, and employ a comprehensive list of study design limitations". Stegenga has criticized specifically that meta analyses are placed at the top of such hierarchies. The assumption that RCTs ought to be necessarily near the top of such hierarchies has been criticized by Worrall and Cartwright. In 2005, Ross Upshur said that EBM claims to be a normative guide to being a better physician, but is not a philosophical doctrine. Borgerson in 2009 wrote that the justifications for the hierarchy levels are not absolute and do not epistemically justify them, but that "medical researchers should pay closer attention to social mechanisms for managing pervasive biases". La Caze noted that basic science resides on the lower tiers of EBM though it "plays a role in specifying experiments, but also analysing and interpreting the data." Concato said in 2004, that it allowed RCTs too much authority and that not all research questions could be answered through RCTs, either because of practical or because of ethical issues. Even when evidence is available from high quality RCTs, evidence from other study types may still be relevant. Stegenga opined that evidence assessment schemes are unreasonably constraining and less informative than other schemes now available.