Clinical practice guidelines are statements that include recommendations intended to optimize patient care based on a systematic review of the evidence assessing the benefits and harm of alternative care options. Guideline developers should use an explicit, judicious, and transparent methodology to make trustworthy guidelines. Although there are a variety of frameworks that can help translate enormous medical knowledge into recommendations, the most widely adopted tool for grading the quality of evidence and making recommendations is GRADE (Grading of Recommendations, Assessment, Development and Evaluations). This article is the first translation of a series published in the BMJ with regard to the GRADE Approach for Evidence Based Clinical Practice Guideline Development to provide informative knowledge for moving from evidence to recommendations to Korean guideline developers.
Advantages of GRADE over other systems
| ㆍDeveloped by a widely representative group of international guideline developers |
| ㆍClear separation between the quality of evidence and strength of recommendations |
| ㆍExplicit evaluation of the importance of outcomes of alternative management strategies |
| ㆍExplicit, comprehensive criteria for downgrading and upgrading the quality of evidence ratings |
| ㆍTransparent process of moving from evidence to recommendations |
| ㆍExplicit acknowledgment of values and preferences |
| ㆍClear, pragmatic interpretation of strong versus weak recommendations for clinicians, patients, and policy makers |
| ㆍUseful for systematic reviews and health technology assessments, as well as guidelines |
Adapted from the article of Guyatt et al. BMJ 2008;336:924–6 [1].
See also Appendix 1 (complete translate in Korean).
Quality of evidence and definitions
| ㆍHigh quality—Further research is unlikely to change our confidence in the estimate of effect |
| ㆍModerate quality—Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate |
| ㆍLow quality—Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate |
| ㆍVery low quality—Any estimate of effect is very uncertain |
Adapted from the article of Guyatt et al. BMJ 2008;336:924–6 [1].
See also Appendix 2 (complete translate in Korean).
Factors that affect the strength of a recommendation
| Factor | Examples of strong recommendations | Examples of weak recommendations |
|---|---|---|
| Quality of evidence | Many high quality randomized trials have shown the benefit of inhaled steroids in asthma | Only case series have examined the utility of pleurodesis in pneumothorax |
| Uncertainty about the balance between desirable and undesirable effects | Aspirin in myocardial infarction reduces mortality with minimal toxicity, inconvenience, and cost | Warfarin in low risk patients with atrial fibrillation results in small stroke reduction but increases the bleeding risk and causes substantial inconvenience |
| Uncertainty or variability in values and preferences | Young patients with lymphoma will invariably place a higher value on the life prolonging effects of chemotherapy than on the treatment toxicity | Older patients with lymphoma may not place a higher value on the life prolonging effects of chemotherapy than on the treatment toxicity |
| Uncertainty about whether the intervention represents a wise use of resources | The low cost of aspirin as a prophylaxis against stroke in patients with transient ischemic attacks | The high cost of clopidogrel and of combination dipyridamole and aspirin as prophylaxis against stroke in patients with transient ischemic attacks |
Adapted from the article of Guyatt et al. BMJ 2008;336:924–6 [1].
See also Appendix 3 (complete translate in Korean).