1. AHRQ Annual Meeting 2009: "Research to Reform: Achieving Health System Change" September 14, 2009 Yngve Falck-Ytter, M.D. Case Western Reserve University, Cleveland, Ohio Holger Schünemann, M.D., Ph.D. Chair, Department of Clinical Epidemiology & Biostatistics Michael Gent Chair in Healthcare Research McMaster University, Hamilton, Canada

2. Disclosure In the past 5 years, Dr. Falck-Ytter received no personal payments for services from industry. His research group received research grants from Three Rivers, Valeant and Roche that were deposited into non-profit research accounts. He is a member of the GRADE working group which has received funding from various governmental entities in the US and Europe. Some of the GRADE work he has done is supported in part by grant # 1 R13 HS016880-01 from the Agency for Healthcare Research and Quality (AHRQ).

3. Content Part 1  Introduction Part 2  Why revisiting guideline methodology? Part 3  The GRADE approach  Quality of evidence Part 4  The GRADE approach  Strength of recommendations

4. Q to audience  Involved in giving recommendations?  Using any form of grading system?  Familiarity with GRADE:  Heard about GRADE before this conference?  Read a GRADE article published by the GRADE working group?  Attended a GRADE presentation?  Attended a hands-on GRADE workshop?

5. Reassessment of clinical practice guidelines  Editorial by Shaneyfelt and Centor (JAMA 2009)  “Too many current guidelines have become marketing and opinion-based pieces…”  “AHA CPG: 48% of recommendations are based on level C = expert opinion…”  “…clinicians do not use CPG […] greater concern […] some CPG are turned into performance measures…”  “Time has come for CPG development to again be centralized, e.g., AHQR…”

6. Evidence-based clinical decisions Research evidence Patient values and preferences Clinical state and circumstances Expertise Equal for all Haynes et al. 2002

7. Oxford Centre of Evidence Based Medicine; http://www.cebm.net 7 Before GRADE Level of evidence I II III IV V Source of evidence SR, RCTs Cohort studies Case-control studies Case series Expert opinion A Grades of recomend. B C D

8. Where GRADE fits in Prioritize problems, establish panel Systematic review Searches, selection of studies, data collection and analysis Assess the relative importance of outcomes Prepare evidence profile: Quality of evidence for each outcome and summary of findings Assess overall quality of evidence Decide direction and strength of recommendation Draft guideline Consult with stakeholders and / or external peer reviewer Disseminate guideline Implement the guideline and evaluate GRADE

9. GRADE uptake

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11. Disclosure Dr. Schünemann receives no personal payments for service from the pharmaceutical industry. The research group he belongs to received research grants from the industry that are deposited into research accounts. 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 documents editor for the American Thoracic Society and co-chair of the GRADE Working Group.

12. Content  Why grading  Confidence in information and recommendations Intro to:  Quality of evidence  Strength of recommendations

13. Please discuss the difference between consensus statements and guidelines? Be prepared to discuss your answer 13

14. There are no RCTs!  Do you think that users of recommendations would like to be informed about the basis (explanation) for a recommendation or coverage decision 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” 14

15. 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

16. Confidence in evidence  There always is evidence  “When there is a question there is evidence”  Better research  greater confidence in the evidence and decisions

17. Who can explain the following?  Concealment of randomization  Bias, confounding and effect modification  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

18. 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

19. Reasons for grading evidence? Appraisal of evidence has become complex and daunting  People draw conclusions about the  quality of evidence and strength of recommendations  Systematic and explicit approaches can help  protect against errors, resolve disagreements  communicate information and fulfil needs  Change practitioner behavior  However, wide variation in approaches GRADE working group. BMJ. 2004 & 2008

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

21. What to do?

22. Recommendations vs statements! 22

23. Limitations of older systems & approaches  confuse quality of evidence with strength of recommendations

24. Levels of evidence

25. Recommendations

26. Limitations of older systems & approaches  confuse quality of evidence with strength of recommendations  lack well-articulated conceptual framework  criteria not comprehensive or transparent  focus on single outcomes

27. GRADE Quality of Evidence In the context of a systematic review  The quality of evidence reflects the extent to which we are confident that an estimate of effect is correct. In the context of making recommendations  The quality of evidence reflects the extent to which our confidence in an estimate of the effect is adequate to support a particular recommendation.

28. What makes you confident in health care decisions 28

29. Confident in the evidence? A meta-analysis of observational studies showed that bicycle helmets reduce the risk of head injuries in cyclists. OR: 0.31, 95%CI: 0.26 to 0.37 A meta-analysis of observational studies showed that warfarin prophylaxis reduces the risk of thromboembolism in patients with cardiac valve replacement. RR: 0.17, 95%CI: 0.13 to 0.24 29

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31. 31 GRADE: Quality of evidence The extent to which our confidence in an estimate of the treatment effect is adequate to support a particular recommendation. GRADE defines 4 categories of quality:  High  Moderate  Low  Very low

32. I B IIVIII Quality of evidence across studies Outcome #1 Outcome #2 Outcome #3 Quality: High Quality: Moderate Quality: Low

33. Determinants of quality  RCTs start high  Observational studies start low

34. 34 What is the study design?

35. Determinants of quality What lowers quality of evidence? 5 factors: Methodological limitations Inconsistency of results Indirectness of evidence Imprecision of results Publication bias

36. Assessment of detailed design and execution (risk of bias) For RCTs:  Lack of allocation concealment  No true intention to treat principle  Inadequate blinding  Loss to follow-up  Early stopping for benefit Methodological limitations Inconsistency of results Indirectness of evidence Imprecision of results Publication bias

37. Schulz KF et al. JAMA 1995 37 Allocation concealment 250 RCTs out of 33 meta-analyses Allocation concealment:Effect (Ratio of OR) adequate1.00(Ref.) unclear0.67 [0.60 – 0.75] not adequate0.59 [0.48 – 0.73] * * significant

38. 5 vs 4 chemo-Rx cycles for AML

39. Studies stopped early becasue of benefit

40. Jadad AR et al. Control Clin Trials 1996 40 What about scoring tools? Example: Jadad score Was the study described as randomized?1 Adequate description of randomization?1 Double blind?1 Method of double blinding described?1 Description of withdrawals and dropouts?1 Max 5 points for quality

41. Cochrane Risk of bias graph in RevMan 5 41

42.  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I2 Methodological limitations Inconsistency of results Indirectness of evidence Imprecision of results Publication bias

43. 43 Heterogeneity Neurological or vascular complications or death within 30 days of endovascular treatment (stent, balloon angioplasty) vs. surgical carotid endarterectomy (CEA)

44.  Indirect comparisons  Interested in head-to-head comparison  Drug A versus drug B  Tenofovir versus entecavir in hepatitis B treatment  Differences in  patients (early cirrhosis vs end-stage cirrhosis)  interventions (CRC screening: flex. sig. vs colonoscopy)  comparator (e.g., differences in dose)  outcomes (non-steroidal safety: ulcer on endoscopy vs symptomatic ulcer complications) Methodological limitations Inconsistency of results Indirectness of evidence Imprecision of results Publication bias

45. Small sample size  small number of events  wide confidence intervals  uncertainty about magnitude of effect Methodological limitations Inconsistency of results Indirectness of evidence Imprecision of results Publication bias

46. Imprecision Any stroke (or death) within 30 days of endovascular treatment (stent, balloon angioplasty) vs. surgical carotid endarterectomy (CEA)

47.  Reporting of studies  publication bias  number of small studies Methodological limitations Inconsistency of results Indirectness of evidence Imprecision of results Publication bias

48. All phase II and III licensing trial for antidepressant drugs between 1987 and 2004 (74 trials – 23 were not published)

49. 49 Quality assessment criteria Lower if… Quality of evidence High Moderate Low Very low Study limitations (design and execution) Inconsistency Indirectness Imprecision Publication bias Observational study Study design Randomized trial Higher if… What can raise the quality of evidence?

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51. 51 Quality assessment criteria Lower if…Higher if… Quality of evidence High Moderate Low Very low Study design Randomized trial Observational study Study limitations Inconsistency Indirectness Imprecision Publication bias Large effect (e.g., RR 0.5) Very large effect (e.g., RR 0.2) Evidence of dose-response gradient All plausible confounding would reduce a demonstrated effect

52. 52 Conceptualizing quality Further research is very unlikely to change our confidence in the estimate of effect High Low 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 Moderate Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate Very lowAny estimate of effect is very uncertain

53. PICOPICO Clinical question Rate importance Select outcomes Very low Low Moderate High Formulate recommendations: For or against (direction) Strong or weak (strength) By considering:  Quality of evidence  Balance benefits/harms  Values and preferences Revise if necessary by considering:  Resource use (cost) Quality rating outcomes across studies Outcome Critical Important Critical Not important Grade down or up OutcomeImportant Overall quality of evidence

54. GRADE evidence profile

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56. Strength of recommendations Desirable effects health benefits less burden savings Undesirable effects harms more burden costs

57. Developing recommendations

58. 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

59. Quality of evidence & strength of recommendation  GRADE separates quality of evidence from 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

60. What makes Guidelines Evidence-Based in 2009? Standardized Reporting of Clinical Practice Guidelines: A Proposal from the Conference on Guideline Standardization Checklist for reporting: 18 items Ann Intern Med. 2003 14. Recommendations and rationale - state the recommended action precisely. Indicate the quality of evidence and the recommendation strength.

61. What makes Guidelines Evidence-Based in 2009? Standardized Reporting of Clinical Practice Guidelines: A Proposal from the Conference on Guideline Standardization Checklist for reporting: 18 items Ann Intern Med. 2003 16. Patient preferences - describe the role of patient preferences when a recommendation involves a substantial element of personal choice or values.

62. A COPD guideline – do you want your review used like this?

63. Another COPD guideline

64. And another COPD guideline

65. What to do?

66. Current state of recommendations 66

67. Current state of recommendations  Reviewed 7527 recommendations  1275 randomly selected  Inconsistency across/within  31.6% did not recommendations clearly  Most of them not written as executable actions  52.7% did not indicated strength 67

68. Yale Guideline Corpus  1. Identify the critical recommendations in guideline text using semantic indicators  2. Use consistent semantic and formatting indicators throughout the publication  3. Group recommendations together in a summary section  4. Do not use assertions of fact as recommendations.  5. Clearly and consistently assign evidence quality and recommendation strength in proximity  distinguish between the distinct concepts of quality of evidence and strength of recommendation. 68

69. Challenges in wording recommendations  Need to express (two) levels  Need to express direction  Differences across languages  Need codes (letters, symbols, numbers)

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71. Categories of recommendations Although the degree of confidence is a continuum, we suggest using two categories: strong and weak/conditional.  Strong recommendation: the panel is confident that the desirable effects of adherence to a recommendation outweigh the undesirable effects.  Weak recommendation: the panel concludes that the desirable effects of adherence to a recommendation probably outweigh the undesirable effects, but is not confident. Recommend   Suggest  ?  ?

72. Implications of a strong recommendation  Patients: Most people in your situation would want the recommended course of action and only a small proportion would not  Clinicians: Most patients should receive the recommended course of action  Policy makers: The recommendation can be adapted as a policy in most situations

73. Implications of a weak/conditional recommendation  Patients: The majority of people in your situation would want the recommended course of action, but many would not  Clinicians: Be prepared to help patients to make a decision that is consistent with their own values  Policy makers: There is a need for substantial debate and involvement of stakeholders

74. 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

75. 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

76. How would you make decisions? 76

77. Judgements about the strength of a recommendation  No precise threshold for going from a strong to a weak recommendation  The presence of important concerns about one or more of these factors make a weak recommendation more likely.  Panels should consider all of these factors and make the reasons for their judgements explicit.  Recommendations should specify the perspective that is taken (e.g. individual patient, health system) and which outcomes were considered (including which, if any costs).

78. Evidence Profile Oseltamivir for treatment of H5N1 infection: - -

79. Oseltamivir for Girl with Avian Flu Summary of findings:  No clinical trial of oseltamivir for treatment of H5N1 patients.  4 systematic reviews and health technology assessments (HTA) reporting on 5 studies of oseltamivir in seasonal influenza.  Hospitalization: OR 0.22 (0.02 – 2.16)  Pneumonia: OR 0.15 (0.03 - 0.69)  3 published case series.  Many in vitro and animal studies.  No alternative that is more promising at present.  Cost: ~ $45 per treatment course

80. What are the factors that determine your decisions? 80

81. GRADE: Factors influencing decisions and recommendations  Quality of Evidence  Balance of desirable and undesirable consequences  Values and preferences  Cost 81

82. Determinants of the strength of recommendation

83. Factors that can weaken the strength of a recommendation. Example: DecisionExplanation Lower quality evidence □ Yes □ No Uncertainty about the balance of benefits versus harms and burdens □ Yes □ No Uncertainty or differences in values □ Yes □ No Uncertainty about whether the net benefits are worth the costs □ Yes □ No Table. Decisions about the strength of a recommendation Frequent “yes” answers will increase the likelihood of a weak recommendation

84. Oseltamivir – Avian Influenza

85. 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 (????? recommendation, very low quality evidence). Schunemann et al. The Lancet ID, 2007

86. Are values important? Should resources be considered? 86

87. 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

88. Other explanations Remarks: Despite the lack of controlled treatment data for H5N1, this is a strong recommendation, in part, because there is a lack of known effective alternative pharmacological interventions at this time. The panel voted on whether this recommendation should be strong or weak and there was one abstention and one dissenting vote.

89. Systematic review Guideline development PICOPICO Outcome Formulate question Rate importance Critical Important Critical Not important Create evidence profile with GRADEpro Summary of findings & estimate of effect for each outcome Rate overall quality of evidence across outcomes based on lowest quality of critical outcomes RCT start high, obs. data start low 1.Risk of bias 2.Inconsistency 3.Indirectness 4.Imprecision 5.Publication bias Grade down Grade up 1.Large effect 2.Dose response 3.Confounders Rate quality of evidence for each outcome Select outcomes Very low Low Moderate High Formulate recommendations: For or against (direction) Strong or weak (strength) By considering:  Quality of evidence  Balance benefits/harms  Values and preferences Revise if necessary by considering:  Resource use (cost) “We recommend using…” “We suggest using…” “We recommend against using…” “We suggest against using…” Outcomes across studies

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