Grading quality of evidence and strength of recommendations in clinical practice guidelines: Part 2 of 3. The GRADE approach to grading quality of evidence about diagnostic tests and strategiesThe GRADE approach to grading the quality of evidence and strength of recommendations provides a comprehensive and transparent approach for developing clinical recommendations about using diagnostic tests or diagnostic strategies. Although grading the quality of evidence and strength of recommendations about using tests shares the logic of grading recommendations for treatment, it presents unique challenges. Guideline panels and clinicians should be alert to these special challenges when using the evidence about the accuracy of tests as the basis for clinical decisions. In the GRADE system, valid diagnostic accuracy studies can provide high quality evidence of test accuracy. However, such studies often provide only low quality evidence for the development of recommendations about diagnostic testing, as test accuracy is a surrogate for patient-important outcomes at best. Inferring from data on accuracy that using a test improves outcomes that are important to patients requires availability of an effective treatment, improved patientsÕ wellbeing through prognostic information, or -by excluding an ominous diagnosisreduction of anxiety and the opportunity for earlier search for an alternative diagnosis for which beneficial treatment can be available. Assessing the directness of evidence supporting the use of a diagnostic test requires judgments about the relationship between test results and patient-important consequences. Well-designed and conducted studies of allergy tests in parallel with efforts to evaluate allergy treatments critically will encourage improved guideline development for allergic diseases. What do patients want?The Oxford Dictionary of English defines diagnosis as Ôthe identification of the nature of an illness or other problem by examination of the symptomsÕ (1). In the medical context, this implies evaluation of patient history, examination and review of laboratory and imaging data. In the Oxford Concise Medical Dictionary, the definition is further amended with a remark: Ôunlike therapeutic procedures, diagnostic processes usually do not directly benefit the patient in terms of treatmentÕ (2). This seemingly obvious observation captures the key concept that applying a Ôgood diagnostic testÕ by itself does not imply improved patient outcomes. In a previous article in this series, we emphasized that what patients really want to know are the benefits and downsides of consenting to the diagnostic or therapeutic procedure they have been offered (3). Making an accurate diagnosis, i.e. accurately classifying patients as having or not having a given condition, does not necessarily imply that any of the outcomes important to them will be affected. However, when clinicians think about diagnostic testing, they focus on test performance (accuracy) -how well the test classifies patients correctly as having or not havi...

No abstract

Logic models have long been used to understand complex programs to improve social and health outcomes. They illustrate how a program is designed to achieve its intended outcomes. They also can be used to describe connections between determinants of outcomes, for example, low high-school graduation rates or spiraling obesity rates, thus aiding the development of interventions that target causal factors. However, these models have not often been used in systematic reviews. This paper argues that logic models can be valuable in the systematic review process. First, they can aid in the conceptualization of the review focus and illustrate hypothesized causal links, identify effect mediators or moderators, specify intermediate outcomes and potential harms, and justify a priori subgroup analyses when differential effects are anticipated. Second, logic models can be used to direct the review process more specifically. They can help justify narrowing the scope of a review, identify the most relevant inclusion criteria, guide the literature search, and clarify interpretation of results when drawing policy-relevant conclusions about review findings. We present examples that explain how logic models have been used and how they can be applied at different stages in a systematic review. Copyright © 2011 John Wiley & Sons, Ltd.

The Patient Perspective Workshop included over 100 researchers and 18 patient participants from 8 countries. Following preconference reading and short plenary presentations, breakout groups considered work undertaken on measurement of sleep, assessing interventions to develop the effective consumer, and assessing psychological and educational interventions. The workshop explored the best way to identify other outcome domains (and instruments) that should be measured in observational or interventional studies with broader intentions than simply altering outcomes captured in the traditional "core set" plus fatigue. Four sleep questionnaires showed promise and will be the subject of further study. The Effective Consumer scale (EC-17) was reviewed and the concept Effective Consumer was well received. Participants thought it worthwhile to measure the skills and attributes of an effective consumer and develop an intervention that would include education in all of the scale's categories. Assessment of educational and psychological interventions requires a wider set of instruments than is currently used; these should relate to the purpose of the intervention. This principle was extended to include wider measures of the impact of disease on life, as indicated in the International Classification of Functioning, Disability and Health. Life impact measure sets covering domains appropriate to different rheumatic conditions and focused on different interventions might be defined by future OMERACT consensus. Measurement instruments within these domains that are valid for use in rheumatic conditions can then be identified and, in the case of psychological and educational interventions, chosen to fit with the purpose of the intervention.

This is the third and last article in the series about the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to grading the quality of evidence and the strength of recommendations in clinical practice guidelines and its application in the field of allergy. We describe the factors that influence the strength of recommendations about the use of diagnostic, preventive and therapeutic interventions: the balance of desirable and undesirable consequences, the quality of a body of evidence related to a decision, patients' values and preferences, and considerations of resource use. We provide examples from two recently developed guidelines in the field of allergy that applied the GRADE approach. The main advantages of this approach are the focus on patient important outcomes, explicit consideration of patients' values and preferences, the systematic approach to collecting the evidence, the clear separation of the concepts of quality of evidence and strength of recommendations, and transparent reporting of the decision process. The focus on transparency facilitates understanding and implementation and should empower patients, clinicians and other health care professionals to make informed choices.

A group from the Cochrane Collaboration, Campbell Collaboration, and the World Health Organization Measurement and Evidence Knowledge Network has developed guidance on assessing health equity effects in systematic reviews of healthcare interventions. This guidance is also relevant to primary research

The final report from the WHO Commission on the social determinants of health recently noted: 'For policy, however important an ethical imperative, values alone are insufficient. There needs to be evidence on what can be done and what is likely to work in practice to improve health and reduce health inequities.' This is challenging, because understanding how to reduce health inequities between the poorest and better-off members of society may require a greater use of subgroup analysis to explore the differential effects of public health interventions. However, while this may produce evidence that is more policy relevant, the requisite subgroup analyses are often seen as tantamount to statistical malpractice. This paper considers some of the methodological problems with subgroup analysis, and its applicability to considerations of equity, using both clinical and public health examples. Finally, it suggests how policy needs for information on subgroups can be met while maintaining rigour.

No abstract