AGA Practice Guidelines Committee Meeting, Chicago May 31, 2009 Yngve Falck-Ytter, M.D.

1. Adopting the GRADE approach for clinical practice guidelines in gastroenterology – benefits and challenges AGA Practice Guidelines Committee Meeting, Chicago May 31, 2009 Yngve Falck-Ytter, M.D. Assistant Professor of Medicine Case Western Reserve University Director of Hepatology, VA Medical Center

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 • Why revisiting guideline methodology? • GRADE approach • Quality of evidence • Strength of recommendations • Why societies have adopted GRADE

4. Content (continued) Part 2 – practical consideration • Ideal vs. practical ad hoc approaches • Funding guideline work

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 Clinical state and circumstances Patient values and preferences Expertise Research evidence Equal for all Haynes et al. 2002

7. Confidence in evidence • There always is evidence • “When there is a question there is evidence” • Evidence alone is never sufficient to make a clinical decision • Better research  greater confidence in the evidence and decisions

8. 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

9. Reasons for grading evidence? • People draw conclusions about the • quality of evidence and strength of recommendations • Systematic and explicit approaches can help to • protect against errors, resolve disagreements • communicate information and fulfill needs • be transparent about the process • Change practitioner behavior • However, wide variation in approaches GRADE working group. BMJ. 2004 & 2008

11. Which grading system? P: In patients with acute hepatitis C …I : Should anti-viral treatment be used … C: Compared to no treatment … O: To achieve viral clearance? Evidence Recommendation Organization B Class I AASLD (2009) II-1 -/- VA (2006) 1+ A SIGN (2006) -/- “Most authorities…” AGA (2006)

12. Scenario (2) Should patients with risk factors for viral hepatitis be screened with a hepatitis C antibody (ELISA) test to identify patients with past hepatitis C exposure?

13. Level of evidence in GI CPGs AGA AASLD ACG ASGE 1. Multiple published, well-controlled (?) randomized trials or a well designed systemic (?) meta-analysis AMultiple RCTs or meta-analysis A. RCTs GoodConsistent, well-designed, well conducted studies […] B. RCT with important limitations BSingle randomized trial, or non-randomized studies FairLimited by the number, quality or consistency of individual studies […] 2. One quality-published (?) RCT, published well-designed cohort/ case-control studies C. Obser-vational studies 3. Consensus of authoritative (?) expert opinions based on clinical evidence or from well designed, but uncontrolled or non-rand. clin. trials C Only consensus opinion of experts, case studies, or standard-of-care Poor… important flaws, gaps in chain of evidence… D. Expert opinion

14. What to do?

15. 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

16. Grades of Recommendation Assessment, Development and Evaluation

17. David Atkins, chief medical officera Dana Best, assistant professorb Martin Eccles, professord Francoise Cluzeau, lecturerx Yngve Falck-Ytter, associate directore Signe Flottorp, researcherf Gordon H Guyatt, professorg Robin T Harbour, quality and information director h Margaret C Haugh, methodologisti David Henry, professorj Suzanne Hill, senior lecturerj Roman Jaeschke, clinical professork Regina Kunx, Associate Professor Gillian Leng, guidelines programme directorl Alessandro Liberati, professorm Nicola Magrini, directorn James Mason, professord Philippa Middleton, honorary research fellowo Jacek Mrukowicz, executive directorp Dianne O’Connell, senior epidemiologistq Andrew D Oxman, directorf Bob Phillips, associate fellowr Holger J Schünemann, professorg,s Tessa Tan-Torres Edejer, medical officert David Tovey, Editory Jane Thomas, Lecturer, UK Helena Varonen, associate editoru Gunn E Vist, researcherf John W Williams Jr, professorv Stephanie Zaza, project directorw a) Agency for Healthcare Research and Quality, USA b) Children's National Medical Center, USA c) Centers for Disease Control and Prevention, USA d) University of Newcastle upon Tyne, UK e) German Cochrane Centre, Germany f) Norwegian Centre for Health Services, Norway g) McMaster University, Canada h) Scottish Intercollegiate Guidelines Network, UK i) Fédération Nationale des Centres de Lutte Contre le Cancer, France j) University of Newcastle, Australia k) McMaster University, Canada l) National Institute for Clinical Excellence, UK m) Università di Modena e Reggio Emilia, Italy n) Centro per la Valutazione della Efficacia della Assistenza Sanitaria, Italy o) Australasian Cochrane Centre, Australia p) Polish Institute for Evidence Based Medicine, Poland q) The Cancer Council, Australia r) Centre for Evidence-based Medicine, UK s) National Cancer Institute, Italy t) World Health Organisation, Switzerland u) Finnish Medical Society Duodecim, Finland v) Duke University Medical Center, USA w) Centers for Disease Control and Prevention, USA x) University of London, UK Y) BMJ Clinical Evidence, UK GRADE Working Group

18. GRADE uptake

19. 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 GRADE 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

20. GRADE: Quality of evidence The extent to which our confidence in an estimate of the treatment effect is adequate to support particular recommendation. Although the degree of confidence is a continuum, we suggest using four categories: • High • Moderate • Low • Very low

21. Quality of evidence across studies Outcome #1 Quality: High Outcome #2 Quality: Moderate Outcome #3 Quality: Low I B II V III

22. Determinants of quality • RCTs start high • Observational studies start low • What lowers quality of evidence? 5 factors: • Detailed design and execution • Inconsistency of results • Indirectness of evidence • Imprecision • Publication bias

23. 1. Design and execution • Study limitations (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 For observational studies: • Selection • Comparability • Exposure/outcome

24. Allocation concealment 250 RCTs out of 33 meta-analysesAllocation concealment: Effect (Ratio of OR) adequate 1.00 (Ref.) unclear 0.67 [0.60 – 0.75] not adequate 0.59 [0.48 – 0.73] * • * significant Schulz KF et al. JAMA 1995

25. Cochrane Risk of bias graph in RevMan 5

26. 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

27. Heterogeneity Pagliaro L et al. Ann Intern Med 1992;117:59-70

28. 3. Directness of Evidence • 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)

29. 4. Imprecision Small sample size • small number of events • wide confidence intervals • uncertainty about magnitude of effect

30. Imprecision appreciable benefit appreciable harm RR precise imprecise 0.75 1.00 1.25

31. 5. Reporting Bias (Publication Bias) • Reporting of studies • publication bias • number of small studies • Reporting of outcomes

32. Quality assessment criteria Study design Lower if… Higher if… Quality of evidence Randomized trial Study limitations (design and execution) High (4) Moderate (3) Inconsistency What can raise the quality of evidence? Observational study Low (2) Indirectness Very low (1) Imprecision Publication bias

33. BMJ 2003;327:1459–61 33

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35. Quality assessment criteria Lower if… Higher if… Quality of evidence Study design Study limitations Large effect (e.g., RR 0.5) Very large effect (e.g., RR 0.2) High (4) Randomized trial Moderate (3) Inconsistency Evidence of dose-response gradient Observational study Low (2) Indirectness All plausible confounding would reduce a demonstrated effect Very low (1) Imprecision Publication bias

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

37. Judgments about the overall quality of evidence • Most systems not explicit • Options: • Benefits • Primary outcome • Highest • Lowest • Beyond the scope of a systematic review • GRADE: Based on lowest of all the critical outcomes

38. GRADE evidence profile

39. Going from evidence to recommendations • Deliberate separation of quality of evidence from strength of recommendation • No automatic one-to-one connection as in other grading systems • Example: What if there is high quality evidence, but the balance between benefit and risks are finely balanced?

40. 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.” Although the strength of recommendation is a continuum, we suggest using two categories : “Strong” and “Weak”

41. Desirable and undesirable effects • Desirable effects • Mortality reduction • Improvement in quality of life, fewer hospitalizations/infections • Reduction in the burden of treatment • Reduced resource expenditure • Undesirable effects • Deleterious impact on morbidity, mortality or quality of life, increased resource expenditure

42. 4 determinants of the strength of recommendation Factors that can weaken the strength of a recommendation Explanation • Lower quality evidence The higher the quality of evidence, the more likely is a strong recommendation. • Uncertainty about the balance of benefits versus harms and burdens The larger the difference between the desirable and undesirable consequences, the more likely a strong recommendation warranted. The smaller the net benefit and the lower certainty for that benefit, the more likely is a weak recommendation warranted. • Uncertainty or differences in values The greater the variability in values and preferences, or uncertainty in values and preferences, the more likely weak recommendation warranted. • Uncertainty about whether the net benefits are worth the costs The higher the costs of an intervention – that is, the more resources consumed – the less likely is a strong recommendation warranted.

43. Developing recommendations

44. Implications of a strong recommendation • Patients: Most people in this 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

45. Implications of a weak recommendation • Patients: The majority of people in this 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/decision aids and shared decision making • Policy makers: There is a need for substantial debate and involvement of stakeholders

46. 6 main misconceptions • Isn’t GRADE expensive to realize? • Isn’t GRADE more complicated, takes longer and requires more resources? • Isn’t GRADE eliminating the expert ? • But what about mechanism of disease, diagnosis, cost? • But GRADE does not have an “insufficient evidence to make recommendation” category! (or: the “optional” category), no? • But we only “recommend” – we can’t possibly give weak recommendations!

47. Create evidence profile with GRADEpro Summary of findings & estimate of effect for each outcome Guideline development Rate overall quality of evidence across outcomes based on lowest quality of critical outcomes Rate quality of evidence for each outcome Outcomes across studies Formulate question Rate importance Select outcomes RCT start high, obs. data start low Risk of bias Inconsistency Indirectness Imprecision Publication bias P I C O Outcome Critical High Outcome Critical Moderate Grade down Low Outcome Important Very low Outcome Not important Large effect Dose response Confounders Grade up Panel • 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) Systematic review • “We recommend using…” • “We suggest using…” • “We recommend against using…” • “We suggest against using…”

48. Summary, andWhy institutions adopt GRADE • GRADE is gaining acceptance as international standard • GRADE has criteria for evidence assessment across a range of questions and outcomes • Criteria for moving from evidence to recommendations • Simple, transparent, systematic • Balance between simplicity and methodological rigor

49. Ideal vs. practical ad hoc GRADE approaches Stage Elements Advantage Comment Ideal Systematic review GRADE eTables Qual. of evidence Strength of rec. Follows int. standards Methodolog. most rigorous Easily maintainable Fully transparent process Access to methodologist Access to evidence centers Initially more resource intensive, long-term savings Inter-mediary Ad hoc review GRADE eTables Qual. of evidence Strength of rec. Still retaining major advantages of the of the “ideal approach” Risk of bias higher Access methodologist rec. Only minimal addl. cost Initiation Ad hoc review GRADE eTables Qual. of evidence Strength of rec. Option to fully “upgrade” to an “ideal approach” Foundation of a methodo-logically sound system Risk of bias higher Access methodologist prn No additional cost