BMJ  2008;336:1106-1110 (17 May), doi:10.1136/bmj.39500.677199.AE

Analysis

Rating quality of evidence and strength of recommendations

Grading quality of evidence and strength of recommendations for diagnostic tests and strategies

¹ Department of Epidemiology, Italian National Cancer Institute Regina Elena, 00144 Rome, Italy, ² CLARITY Research Group, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada L8N 3Z5, ³ Norwegian Knowledge Centre for the Health Services, PO Box 7004, 0130 Oslo, Norway, ⁴ Centre for Evidence-Based Medicine, Department of Primary Health Care, University of Oxford, Oxford OX3 7LF, ⁵ Department of Medicine, McMaster University, 1200 Main Street West, Hamilton, Ontario, Canada L8N 3Z5, ⁶ Department of Medicine, Duke University and Durham VA Medical Center, Durham, NC 27705, USA, ⁷ Basel Institute of Clinical Epidemiology, University Hospital Basel, Hebelstrasse 10, 4031 Basel, Switzerland, ⁸ Screening and Test Evaluation Program, School of Public Health, University of Sydney, Department of Nephrology, Children’s Hospital at Westmead, Sydney, Australia, ⁹ Knowledge and Encounter Research Unit, Department of Medicine, Mayo Clinic College of Medicine, Rochester, MN 55905, USA, ¹⁰ Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, University of Amsterdam, Amsterdam 1100 DE, Netherlands

Analysis, doi: 10.1136/bmj.39490.551019.BEAnalysis, doi: 10.1136/bmj.39489.470347.ADAnalysis, doi: 10.1136/bmj.39493.646875.AE

The GRADE system can be used to grade the quality of evidence and strength of recommendations for diagnostic tests or strategies. This article explains how patient-important outcomes are taken into account in this process

The first 150 words of the full text of this article appear below.

Summary points As for other interventions, the GRADE approach to grading the quality of evidence and strength of recommendations for diagnostic tests or strategies provides a comprehensive and transparent approach for developing recommendations Cross sectional or cohort studies can provide high quality evidence of test accuracy However, test accuracy is a surrogate for patient-important outcomes, so such studies often provide low quality evidence for recommendations about diagnostic tests, even when the studies do not have serious limitations Inferring from data on accuracy that a diagnostic test or strategy improves patient-important outcomes will require the availability of effective treatment, reduction of test related adverse effects or anxiety, or improvement of patients’ wellbeing from prognostic information Judgments are thus needed to assess the directness of test results in relation to consequences of diagnostic recommendations that are important to patients

In this fourth article of the five part series, we describe how guideline developers are . . . [Full text of this article]

Testing makes a variety of contributions to patient care

Example question for replacement test

Test accuracy is a surrogate for patient-important outcomes

Using indirect evidence to make inferences about impact on patient-important outcomes

Judgments about quality of underlying evidence

Study design
Study limitations (risk of bias)
Directness

Arriving at a bottom line for study quality

Arriving at a recommendation

Conclusion

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