David Atkins

Grading quality of evidence and strength of recommendations.

Abstract Users of clinical practice guidelines and other recommendations need to know how much confidence they can place in the recommendations. Systematic and explicit methods of making judgments can reduce errors and improve communication. We have developed a system for grading the quality of evidence and the strength of recommendations that can be applied across a wide range of interventions and contexts. In this article we present a summary of our approach from the perspective of a guideline user. Judgments about the strength of a recommendation require consideration of the balance between benefits and harms, the quality of the evidence, translation of the evidence into specific circumstances, and the certainty of the baseline risk. It is also important to consider costs (resource utilisation) before making a recommendation. Inconsistencies among systems for grading the quality of evidence and the strength of recommendations reduce their potential to facilitate critical appraisal and improve communication of these judgments. Our system for guiding these complex judgments balances the need for simplicity with the need for full and transparent consideration of all important issues. Clinical guidelines are only as good as the evidence and judgments they are based on. The GRADE approach aims to make it easier for users to assess the judgments behind recommendations

GRADE guidelines: 9. Rating up the quality of evidence.

The most common reason for rating up the quality of evidence is a large effect. GRADE suggests considering rating up quality of evidence one level when methodologically rigorous observational studies show at least a two-fold reduction or increase in risk, and rating up two levels for at least a five-fold reduction or increase in risk. Systematic review authors and guideline developers may also consider rating up quality of evidence when a dose-response gradient is present, and when all plausible confounders or biases would decrease an apparent treatment effect, or would create a spurious effect when results suggest no effect. Other considerations include the rapidity of the response, the underlying trajectory of the condition, and indirect evidence.

Current methods of the U.S. Preventive Services Task Force: A review of the process

The U.S. Preventive Services Task Force (USPSTF/Task Force) represents one of several efforts to take a more evidence-based approach to the development of clinical practice guidelines. As methods have matured for assembling and reviewing evidence and for translating evidence into guidelines, so too have the methods of the USPSTF. This paper summarizes the current methods of the third USPSTF, supported by the Agency for Healthcare Research and Quality (AHRQ) and two of the AHRQ Evidence-based Practice Centers (EPCs). The Task Force limits the topics it reviews to those conditions that cause a large burden of suffering to society and that also have available a potentially effective preventive service. It focuses its reviews on the questions and evidence most critical to making a recommendation. It uses analytic frameworks to specify the linkages and key questions connecting the preventive service with health outcomes. These linkages, together with explicit inclusion criteria, guide the literature searches for admissible evidence. Once assembled, admissible evidence is reviewed at three strata: (1) the individual study, (2) the body of evidence concerning a single linkage in the analytic framework, and (3) the body of evidence concerning the entire preventive service. For each stratum, the Task Force uses explicit criteria as general guidelines to assign one of three grades of evidence: good, fair, or poor. Good or fair quality evidence for the entire preventive service must include studies of sufficient design and quality to provide an unbroken chain of evidence-supported linkages, generalizable to the general primary care population, that connect the preventive service with health outcomes. Poor evidence contains a formidable break in the evidence chain such that the connection between the preventive service and health outcomes is uncertain. For services supported by overall good or fair evidence, the Task Force uses outcomes tables to help categorize the magnitude of benefits, harms, and net benefit from implementation of the preventive service into one of four categories: substantial, moderate, small, or zero/negative. The Task Force uses its assessment of the evidence and magnitude of net benefit to make a recommendation, coded as a letter: from A (strongly recommended) to D (recommend against). It gives an I recommendation in situations in which the evidence is insufficient to determine net benefit. The third Task Force and the EPCs will continue to examine a variety of methodologic issues and document work group progress in future communications.Abstract Abstract: The U.S. Preventive Services Task Force (USPSTF/Task Force) represents one of several efforts to take a more evidence-based approach to the development of clinical practice guidelines. As methods have matured for assembling and reviewing evidence and for translating evidence into guidelines, so too have the methods of the USPSTF. This paper summarizes the current methods of the third USPSTF, supported by the Agency for Healthcare Research and Quality (AHRQ) and two of the AHRQ Evidence-based Practice Centers (EPCs). mThe Task Force limits the topics it reviews to those conditions that cause a large burden of suffering to society and that also have available a potentially effective preventive service. It focuses its reviews on the questions and evidence most critical to making a recommendation. It uses analytic frameworks to specify the linkages and key questions connecting the preventive service with health outcomes. These linkages, together with explicit inclusion criteria, guide the literature searches for admissible evidence. mOnce assembled, admissible evidence is reviewed at three strata: (1) the individual study, (2) the body of evidence concerning a single linkage in the analytic framework, and (3) the body of evidence concerning the entire preventive service. For each stratum, the Task Force uses explicit criteria as general guidelines to assign one of three grades of evidence: good, fair, or poor. Good or fair quality evidence for the entire preventive service must include studies of sufficient design and quality to provide an unbroken chain of evidence-supported linkages, generalizable to the general primary care population, that connect the preventive service with health outcomes. Poor evidence contains a formidable break in the evidence chain such that the connection between the preventive service and health outcomes is uncertain. For services supported by overall good or fair evidence, the Task Force uses outcomes tables to help categorize the magnitude of benefits, harms, and net benefit from implementation of the preventive service into one of four categories: substantial, moderate, small, or zero/negative. mThe Task Force uses its assessment of the evidence and magnitude of net benefit to make a recommendation, coded as a letter: from A (strongly recommended) to D (recommend against). It gives an I recommendation in situations in which the evidence is insufficient to determine net benefit. mThe third Task Force and the EPCs will continue to examine a variety of methodologic issues and document work group progress in future communications.

GRADE guidelines: 4. Rating the quality of evidence—study limitations (risk of bias)

In the GRADE approach, randomized trials start as high-quality evidence and observational studies as low-quality evidence, but both can be rated down if most of the relevant evidence comes from studies that suffer from a high risk of bias. Well-established limitations of randomized trials include failure to conceal allocation, failure to blind, loss to follow-up, and failure to appropriately consider the intention-to-treat principle. More recently recognized limitations include stopping early for apparent benefit and selective reporting of outcomes according to the results. Key limitations of observational studies include use of inappropriate controls and failure to adequately adjust for prognostic imbalance. Risk of bias may vary across outcomes (e.g., loss to follow-up may be far less for all-cause mortality than for quality of life), a consideration that many systematic reviews ignore. In deciding whether to rate down for risk of bias--whether for randomized trials or observational studies--authors should not take an approach that averages across studies. Rather, for any individual outcome, when there are some studies with a high risk, and some with a low risk of bias, they should consider including only the studies with a lower risk of bias.

GRADE guidelines: 2. Framing the question and deciding on important outcomes

GRADE requires a clear specification of the relevant setting, population, intervention, and comparator. It also requires specification of all important outcomes--whether evidence from research studies is, or is not, available. For a particular management question, the population, intervention, and outcome should be sufficiently similar across studies that a similar magnitude of effect is plausible. Guideline developers should specify the relative importance of the outcomes before gathering the evidence and again when evidence summaries are complete. In considering the importance of a surrogate outcome, authors should rate the importance of the patient-important outcome for which the surrogate is a substitute and subsequently rate down the quality of evidence for indirectness of outcome.

GRADE guidelines: 5. Rating the quality of evidence—publication bias

In the GRADE approach, randomized trials start as high-quality evidence and observational studies as low-quality evidence, but both can be rated down if a body of evidence is associated with a high risk of publication bias. Even when individual studies included in best-evidence summaries have a low risk of bias, publication bias can result in substantial overestimates of effect. Authors should suspect publication bias when available evidence comes from a number of small studies, most of which have been commercially funded. A number of approaches based on examination of the pattern of data are available to help assess publication bias. The most popular of these is the funnel plot; all, however, have substantial limitations. Publication bias is likely frequent, and caution in the face of early results, particularly with small sample size and number of events, is warranted.

Systems for grading the quality of evidence and the strength of recommendations I: Critical appraisal of existing approaches The GRADE Working Group

BackgroundA number of approaches have been used to grade levels of evidence and the strength of recommendations. The use of many different approaches detracts from one of the main reasons for having explicit approaches: to concisely characterise and communicate this information so that it can easily be understood and thereby help people make well-informed decisions. Our objective was to critically appraise six prominent systems for grading levels of evidence and the strength of recommendations as a basis for agreeing on characteristics of a common, sensible approach to grading levels of evidence and the strength of recommendations.MethodsSix prominent systems for grading levels of evidence and strength of recommendations were selected and someone familiar with each system prepared a description of each of these. Twelve assessors independently evaluated each system based on twelve criteria to assess the sensibility of the different approaches. Systems used by 51 organisations were compared with these six approaches.ResultsThere was poor agreement about the sensibility of the six systems. Only one of the systems was suitable for all four types of questions we considered (effectiveness, harm, diagnosis and prognosis). None of the systems was considered usable for all of the target groups we considered (professionals, patients and policy makers). The raters found low reproducibility of judgements made using all six systems. Systems used by 51 organisations that sponsor clinical practice guidelines included a number of minor variations of the six systems that we critically appraised.ConclusionsAll of the currently used approaches to grading levels of evidence and the strength of recommendations have important shortcomings.

AHRQ Series Paper 5: Grading the strength of a body of evidence when comparing medical interventions—Agency for Healthcare Research and Quality and the Effective Health-Care Program

OBJECTIVE To establish guidance on grading strength of evidence for the Evidence-based Practice Center (EPC) program of the U.S. Agency for Healthcare Research and Quality. STUDY DESIGN AND SETTING Authors reviewed authoritative systems for grading strength of evidence, identified domains and methods that should be considered when grading bodies of evidence in systematic reviews, considered public comments on an earlier draft, and discussed the approach with representatives of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group. RESULTS The EPC approach is conceptually similar to the GRADE system of evidence rating; it requires assessment of four domains: risk of bias, consistency, directness, and precision. Additional domains to be used when appropriate include dose-response association, presence of confounders that would diminish an observed effect, strength of association, and publication bias. Strength of evidence receives a single grade: high, moderate, low, or insufficient. We give definitions, examples, mechanisms for scoring domains, and an approach for assigning strength of evidence. CONCLUSION EPCs should grade strength of evidence separately for each major outcome and, for comparative effectiveness reviews, all major comparisons. We will collaborate with the GRADE group to address ongoing challenges in assessing the strength of evidence.

GRADE guidelines: 11. Making an overall rating of confidence in effect estimates for a single outcome and for all outcomes

GRADE requires guideline developers to make an overall rating of confidence in estimates of effect (quality of evidence-high, moderate, low, or very low) for each important or critical outcome. GRADE suggests, for each outcome, the initial separate consideration of five domains of reasons for rating down the confidence in effect estimates, thereby allowing systematic review authors and guideline developers to arrive at an outcome-specific rating of confidence. Although this rating system represents discrete steps on an ordinal scale, it is helpful to view confidence in estimates as a continuum, and the final rating of confidence may differ from that suggested by separate consideration of each domain. An overall rating of confidence in estimates of effect is only relevant in settings when recommendations are being made. In general, it is based on the critical outcome that provides the lowest confidence.

Systems for grading the quality of evidence and the strength of recommendations II: Pilot study of a new system

BackgroundSystems that are used by different organisations to grade the quality of evidence and the strength of recommendations vary. They have different strengths and weaknesses. The GRADE Working Group has developed an approach that addresses key shortcomings in these systems. The aim of this study was to pilot test and further develop the GRADE approach to grading evidence and recommendations.MethodsA GRADE evidence profile consists of two tables: a quality assessment and a summary of findings. Twelve evidence profiles were used in this pilot study. Each evidence profile was made based on information available in a systematic review. Seventeen people were given instructions and independently graded the level of evidence and strength of recommendation for each of the 12 evidence profiles. For each example judgements were collected, summarised and discussed in the group with the aim of improving the proposed grading system. Kappas were calculated as a measure of chance-corrected agreement for the quality of evidence for each outcome for each of the twelve evidence profiles. The seventeen judges were also asked about the ease of understanding and the sensibility of the approach. All of the judgements were recorded and disagreements discussed.ResultsThere was a varied amount of agreement on the quality of evidence for the outcomes relating to each of the twelve questions (kappa coefficients for agreement beyond chance ranged from 0 to 0.82). However, there was fair agreement about the relative importance of each outcome. There was poor agreement about the balance of benefits and harms and recommendations. Most of the disagreements were easily resolved through discussion. In general we found the GRADE approach to be clear, understandable and sensible. Some modifications were made in the approach and it was agreed that more information was needed in the evidence profiles.ConclusionJudgements about evidence and recommendations are complex. Some subjectivity, especially regarding recommendations, is unavoidable. We believe our system for guiding these complex judgements appropriately balances the need for simplicity with the need for full and transparent consideration of all important issues.