Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

1. Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics Michael Gent Chair in Healthcare Research Professor of Clinical Epidemiology, Biostatistics and Medicine McMaster University, Hamilton, Canada Baltimore, May 5, 2009 How Can We Assist Practitioners to Assess and Implement Meaningful Therapies for Their Patients: The Example of the GRADE Approach

2. Disclosure In the past three years, Dr. Schünemann received no personal payments for service from the pharmaceutical industry. During that time, his research group received research grants and - until April 2008 - fees and/or honoraria that were deposited into research accounts from Chiesi Foundation, Pfizer, UnitedBioSource and Lily, as lecture fees related to research methodology. He is documents editor for the American Thoracic Society. Institutions or organizations that he is affiliated with likely receive funding from for-profit sponsors that are supporting infrastructure and research that may serve his work. He is a GRADE Working Group Member

3. Content • Key principles of guidance documents • GRADE approach • Quality of evidence • Strength of recommendations

4. Case scenario A 13 year old girl who lives in rural Indonesia presented with flu symptoms and developed severe respiratory distress over the course of the last 2 days. She required intubation. The history reveals that she shares her living quarters with her parents and her three siblings. At night the family’s chicken stock shares this room too and several chicken had died unexpectedly a few days before the girl fell sick. Interventions: antivirals, such as neuraminidase inhibitors oseltamivir and zanamivir

5. Relevant healthcare question? Clinical question: Population: Avian Flu/influenza A (H5N1) patients Intervention:Oseltamivir (or Zanamivir) Comparison: No pharmacological intervention Outcomes: Mortality, hospitalizations, resource use, adverse outcomes, antimicrobial resistance WHO Avian Influenza GL. Schunemann et al., The Lancet ID, 2007

6. There are no RCTs! • Do you think that users of recommendations would like to be informed about the basis (explanation) for a recommendation if they were asked (by their patients)? • I suspect the answer is “yes” • If we need to provide the basis for recommendations, we need to say whether the evidence is good or not so good; in other words perhaps “no RCTs”

7. Hierarchy of evidence • STUDY DESIGN • Randomized Controlled Trials • Cohort Studies and Case Control Studies • Case Reports and Case Series, Non-systematic observations BIAS Expert Opinion

8. Can you explain the following? • Concealment of randomization • Blinding (who is blinded in a double blinded trial?) • Intention to treat analysis and its correct application • Why trials stopped early for benefit overestimate treatment effects? • P-values and confidence intervals

9. Hierarchy of evidence • STUDY DESIGN • Randomized Controlled Trials • Cohort Studies and Case Control Studies • Case Reports and Case Series, Non-systematic observations BIAS Expert Opinion Expert Opinion Expert Opinion

10. Evidence Recommendation B Class I A 1 IV C Organization AHA ACCP SIGN Which grading system? Recommendation for use of oral anticoagulation in patients with atrial fibrillation and rheumatic mitral valve disease

11. Recommendations vs statements!

12. The GRADE approach Clear separation of 2 issues: 1) 4 categories of quality of evidence: very low, low, moderate, or high quality? • methodological quality of evidence • likelihood of bias • by outcome and across outcomes 2) Recommendation: 2 grades - weak or strong (for or against)? • Quality of evidence only one factor *www.GradeWorking-Group.org

13. Grades of Recommendation Assessment, Development and Evaluation GRADE Working Group CMAJ 2003, BMJ 2004, BMC 2004, BMC 2005, AJRCCM 2006, Chest 2006, BMJ 2008

14. About GRADE • Since 2000 • Researchers/guideline developers with interest in methodology • Aim: to develop a common, transparent and sensible system for grading the quality of evidence and the strength of recommendations • Evaluation of existing systems

15. GRADE Uptake • World Health Organization • Allergic Rhinitis in Asthma Guidelines (ARIA) • American Thoracic Society • British Medical Journal • American College of Chest Physicians • UpToDate • American College of Physicians • Cochrane Collaboration • National Institute Clinical Excellence (NICE) • Infectious Disease Society of America • European Society of Thoracic Surgeons • Clinical Evidence • Agency for Health Care Research and Quality (AHRQ) • Over 20 major organizations

16. Limitations of existing systems • confuse quality of evidence with strength of recommendations • lack well-articulated conceptual framework • criteria not comprehensive or transparent • GRADE unique • breadth, intensity of development process • wide endorsement and use • conceptual framework • comprehensive, transparent criteria • Focus on all important outcomes related to a specific question and overall quality

17. Determinants of quality • RCTs start high • observational studies start low • 5 factors that can lower quality • limitations of detailed design and execution • inconsistency • indirectness • reporting bias • Imprecision • 3 factors can increase quality • large magnitude of effect • all plausible confounding may be working to reduce the demonstrated effect or increase the effect if no effect was observed • dose-response gradient

18. 1. Design and Execution • limitations • Randomization • lack of concealment • intention to treat principle violated • inadequate blinding • loss to follow-up • early stopping for benefit The evidence for the effect of sublingual immunotherapy in children with allergic rhinitis on the development of asthma, comes from a single randomised trial with no description of randomisation, concealment of allocation, and type of analysis, no blinding, and 21% of children lost to follow-up. These very serious limitations would limit our confidence in the estimates of effect and likely lead to downgrading the quality of evidence.

19. 1. Design and Execution • From Cates , CDSR 2008 CDSR 2008

20. 1. Design and Execution Overall judgment required

21. 2. Consistency of results • Look for explanation for inconsistency • patients, intervention, comparator, outcome, methods • Judgment • variation in size of effect • overlap in confidence intervals • statistical significance of heterogeneity • I2

22. 3. Directness of Evidence • indirect comparisons • interested in A versus B • have A versus C and B versus C • differences in • patients • interventions • outcomes

23. Directness of Evidence

24. Directness of Evidence

25. Directness of Evidence

26. Directness of Evidence

27. 4. Publication Bias • Publication bias • Cave! Only few small studies A systematic review of topical treatments for seasonal allergic conjunctivitis showed that patients using topical sodium cromoglycate were more likely to perceive benefit than those using placebo. However, only small trials reported clinically and statistically significant benefits of active treatment, while a larger trial showed a much smaller and a statistically not significant effect. These findings suggest that smaller studies demonstrating smaller effects might not have been published.

28. 5. Imprecision • small sample size • small number of events • wide confidence intervals • uncertainty about magnitude of effect Observational studies examining the impact of exclusive breastfeeding on development of allergic rhinitis in high risk infants showed a relative risk of 0.87 (95% CI: 0.48 to 1.58) that neither rules out important benefit nor important harm (Mimouni Bloch 2002).

29. What can raise quality?3 Factors • large magnitude can upgrade one level • very large two levels • common criteria • everyone used to do badly • almost everyone does well • The parachute example: if we’d look at the observational evidence, we’d find a very large effect and the evidence probably would be high quality for preventing death • dose response relation (higher dose of brain radiation in childhood leukemia leads to greater risk of late malignancies) • Residual confounding unlikely to be responsible for observed effect

30. Quality assessment criteria

31. Strength of recommendation • “The strength of a recommendation reflects the extent to which we can, across the range of patients for whom the recommendations are intended, be confident that desirable effects of a management strategy outweigh undesirable effects.” • Strong or weak/conditional

32. Quality of evidence & strength of recommendation • Linked but no automatism • Other factors beyond the quality of evidence influence our confidence that adherence to a recommendation causes more benefit than harm • Systems/approaches failed to make this explicit • GRADE separates quality of evidence from strength of recommendation

33. Developing recommendations

34. Factors determining strength of recommendation

35. Judgments about the strength of a recommendation - oseltamivir for treatment of patients hospitalised with avian influenza (H5N1)

36. Recommendations vs statements!

37. Example: Oseltamivir for Avian Flu Recommendation: In patients with confirmed or strongly suspected infection with avian influenza A (H5N1) virus, clinicians should administer oseltamivir treatment as soon as possible (strong recommendation, very low quality evidence). Values and Preferences Remarks: This recommendation places a high value on the prevention of death in an illness with a high case fatality. It places relatively low values on adverse reactions, the development of resistance and costs of treatment. Schunemann et al., The Lancet ID, 2007

38. Conclusion • Clinicians need appropiate summaries • quality of evidence • strength of recommendations • explicit rules • transparent, informative • GRADE • four categories of quality of evidence • two grades for strength of recommendations • transparent, systematic by and across outcomes • wide adoption