- Frederick A Spencer, professor of medicine1,
- Alfonso Iorio, associate professor of clinical epidemiology and biostatistics12,
- John You, assistant professor of medicine12,
- M Hassad Murad, associate professor of medicine3,
- Holger J Schünemann, professor and chair of clinical epidemiology and biostatistics12,
- Per O Vandvik, associate professor of medicine45,
- Mark A Crowther, professor of medicine and molecular medicine16,
- Kevin Pottie, associate professor of family medicine and epidemiology and community medicine7,
- Eddy S Lang, senior researcher8,
- Joerg J Meerpohl, deputy director of German Cochrane Centre9,
- Yngve Falck-Ytter, assistant professor of medicine10,
- Pablo Alonso-Coello, senior researcher11,
- Gordon H Guyatt, professor of medicine and clinical epidemiology and biostatistics2
- 1Department of Medicine, McMaster University, Hamilton ON L8N 4A6, Canada
- 2Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton
- 3Division of Preventive Medicine, Mayo Clinic, Rochester, Minnesota, USA
- 4Department of Medicine, Inlandet Hospital Trust, GjØvik, Norway
- 5Norwegian Knowledge Centre for Health Services, Oslo, Norway
- 6Department of Molecular Medicine, McMaster University, Hamilton
- 7Departments of Family Medicine and Epidemiology and Community Medicine, University of Ottawa, Ottawa, Canada
- 8Division of Emergency Medicine, University of Calgary, Calgary, Canada
- 9German Cochrane Center, Institute of Medical Biometry and Medical Informatics, University Medical Center, Freiburg, Germany
- 10Department of Medicine, Case Western Reserve University, Cleveland, USA
- 11Iberoamerican Cochrane Centre, CIBERESP-IIB Sant Pau, Barcelona, Spain
- Correspondence to: F A Spencer fspence{at}mcmaster.ca
The GRADE system provides a framework for evaluating how risk of bias, publication bias, imprecision, inconsistency, and indirectness may reduce confidence in estimates of relative effects of interventions on outcomes. However, GRADE and all other systems for rating confidence in effect estimates do not fully address uncertainty in baseline risk and its impact on confidence in absolute estimates of treatment effect. In this article the authors examine factors that may reduce confidence in estimates of baseline risk and thus estimates of absolute treatment benefit
The GRADE system provides a framework for assessing confidence in estimates of the effect (“quality of evidence”) of alternative management strategies on outcomes that are important to patients.1 2 3 4 5 6 The GRADE system includes consideration of risk of bias, publication bias, imprecision, inconsistency, and indirectness and their impact on confidence in estimates of benefits and harms. The evaluation of each of these issues has, thus far, focused almost exclusively on their potential impact on estimates of relative effect. Because, in most instances, estimates of relative effect of a therapy are similar across different baseline risks, one can apply these relative estimates to the best estimates of overall baseline risk or, if available, estimates from subgroups that differ in baseline risk.
Using the GRADE approach, guideline panellists multiply the best estimate of relative effect by the best available estimate of baseline risk to obtain an estimate of absolute effect (see box). Limitations of the evidence with respect to risk of bias, publication bias, imprecision, inconsistency, or indirectness may reduce confidence in estimates of the relative risk reduction and affect the strength of guideline recommendations.
Estimates of absolute effect
When patients and clinicians are trading off desirable and undesirable consequences of an intervention they require estimates of absolute effect. For instance, patients with atrial fibrillation need to trade …
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