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GRADE: assessing the quality of evidence for diagnostic recommendations
  1. Holger J Schünemann1,
  2. Andrew D Oxman2,
  3. Jan Brozek3,
  4. Paul Glasziou4,
  5. Patrick Bossuyt5,
  6. Stephanie Chang6,
  7. Paola Muti3,
  8. Roman Jaeschke1,
  9. Gordon H Guyatt1
  1. 1
    McMaster University, Hamilton, Ontario, Canada
  2. 2
    Norwegian Knowledge Centre for the Health Services, Oslo, Norway
  3. 3
    Italian National Cancer Institute Regina Elena, Rome, Italy
  4. 4
    University of Oxford, Oxford, UK
  5. 5
    University of Amsterdam, Amsterdam, Netherlands
  6. 6
    Agency for Healthcare Research and Quality, Rockville, Maryland, USA

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    Making a diagnosis is the bread and butter of clinical practice, but in today’s world of many tests, the process has become complex. Guidelines for making an evidence-based diagnosis abound, but those making recommendations about diagnostic tests or test strategies must realise that clinicians require support to make diagnostic decisions that they can easily implement in daily practice. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group has developed a rigorous, transparent, and increasingly adopted approach for grading the quality of research evidence and strength of recommendations to guide clinical practice. This Notebook summarises GRADE’s process for developing recommendations for tests.1

    Clinicians are trained to use tests for screening and diagnosis, identifying physiological derangements, establishing a prognosis, and monitoring illness and treatment response by assessing signs and symptoms, imaging, biochemistry, pathology, and psychological testing techniques.2 Sensitivity, specificity, positive predictive value, likelihood ratios, and diagnostic odds ratios are among the challenging terms that diagnostic studies typically deliver to clinicians, and all have to do with diagnostic accuracy. Not only do clinicians have difficulties remembering the definitions and calculations for these terms, these concepts are often complex to apply to individual patients. Many clinicians order a test despite uncertainty about how to interpret the result, and they also contribute to testing errors …

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