An Overview of Coronary Drug-Eluting Stents: the Meta-analytic Approach

1. An Overview of CoronaryDrug-Eluting Stents: the Meta-analytic Approach Giuseppe Biondi-Zoccai Ospedale S. Giovanni Battista “Molinette” Università di Torino Convegno Regionale Piemonte “Aggiornamenti in tema di valvulopatie, resincronizzazione e malattia coronarica” - Torino, 14 Novembre 2007 (h 16.30-16.50)

2. Learning goals • Why such a fuzz on meta-analyses? • What is a meta-analysis? • Are meta-analyses useful? • How can I appraise the internal and external validity of a meta-analysis? • What are the meta-analysis results on drug-eluting stents?

3. Learning goals • Why such a fuzz on meta-analyses? • What is a meta-analysis? • Are meta-analyses useful? • How can I appraise the internal and external validity of a meta-analysis? • What are the meta-analysis results on drug-eluting stents?

4. Do you remember 2005?The rosy future… Buzzword = ?

6. Do you remember 2005?The rosy future… Buzzword = Late loss

7. Do you remember 2005?The rosy future…

8. Late 2006 surprise:the death/MI/thrombosis iceberg Buzzword = ?

10. Late 2006 surprise:the death/MI/thrombosis iceberg Buzzword = Thrombosis

11. Late 2006 surprise:the death/MI/thrombosis iceberg

12. Learning goals • Why such a fuzz on meta-analyses? • What is a meta-analysis? • Are meta-analyses useful? • How can I appraise the internal and external validity of a meta-analysis? • What are the meta-analysis results on drug-eluting stents?

13. Exponential increase in PubMed citations PubMed search strategy: ("2001"[PDAT] : "2005"[PDAT]) AND (("systematic"[title/abstract] AND "review"[title/abstract]) OR ("systematic"[title/abstract] AND "overview"[title/abstract]) OR ("meta-analysis"[title/abstract] OR "meta-analyses"[title/abstract]))

14. Famous quotes “If I have seen further it is by standing on the shoulders of giants” Isaac Newton “The great advances in science usually result from new tools rather than from new doctrines” Freeman Dyson

15. Famous quotes “I like to think of the meta-analytic process as similar to being in a helicopter. On the ground individual trees are visible with high resolution. This resolution diminishes as the helicopter rises, and in its place we begin to see patterns not visible from the ground” Ingram Olkin

16. Minimal glossary • Review: viewpoint on a subject quoting different primary authors • Overview: as above • Qualitative review: deliberately avoids a systematic approach • Systematic review: deliberately uses a systematic approach to study search, selection, abstraction, appraisal and pooling • Quantitative review: uses quantitative methods to appraise or synthesize data • Meta-analysis: uses specific statistical methods for data pooling and/or exploratory analysis • Individual patient data meta-analysis: uses specific stastistical methods for data pooling or exploration exploiting individual patient data

17. Systematic review vs meta-analysis • What is a systematic review? • A systematic appraisal of the methodological quality, clinical relevance and consistency of published evidence on a specific clinical topic in order to provide clear suggestions for a specific healthcare problem • What is a meta-analysis? • A quantitative synthesis that, preserving the identity of individual studies, tries to provide an estimate of the overall effect of an intervention, exposure, or diagnostic strategy

18. Individual patient data meta-analysis • Ideally should be a systematic review and meta-analysis based on individual patient data • Major pros: • a unique database containing primary studies is created and used (consistency checks and homogenous variables are created) • the same analytical tools can be used across studies • subgroup analyses can be performed even for groups that were not reported in the original publications • Major cons: • some studies may have to be excluded (publication bias) because original authors may not provide source data • poses major logistical and financial challenges

19. Systematic review and meta-regression • A meta-regression employs meta-analytic methods to explore the impact of covariates or moderators on the main effect measure or on other • All the limitations of non-RCT studies applies, and thus they should mainly be regarded as hypothesis generating

20. Indirect and network meta-analyses • An indirect comparison meta-analysis exploit several randomized trials sharing a common comparator to generate an interaction indirect effect estimates • Network meta-analyses combine estimates from direct and indirect meta-analyses to provide more precise effect estimates

21. Learning goals • Why such a fuzz on meta-analyses? • What is a meta-analysis? • Are meta-analyses useful? • How can I appraise the internal and external validity of a meta-analysis? • What are the meta-analysis results on drug-eluting stents?

22. Meta-analysis: Cons • “Exercise in mega-silliness” • “Mixing apples with oranges” • Not original research • Big RCTs definitely better • Pertinent studies might not be found, or may be of low quality or internal validity • Publication and small study bias • Average effect largely unapplicable to individuals Lau et al, Lancet 1998

23. Cons Smith et al, BMJ 2003

24. Meta-analysis: Pros • Systematic searches for clinical evidence • Explicit and standardized methods for search and selection of evidence sources • Thorough appraisal of the internal validity of primary studies • Quantitative synthesis with increased statistical power • Increased external validity by appraising the effect of an intervention (exposure) across different settings • Test subgroup hypotheses • Explore clinical and statistical heterogeneit Lau et al, Lancet 1998

26. A famous cumulative meta-analysis Antman et al, JAMA 1992

27. Antman et al, JAMA 1992

28. Learning goals • Why such a fuzz on meta-analyses? • What is a meta-analysis? • Are meta-analyses useful? • How can I appraise the internal and external validity of a meta-analysis? • What are the meta-analysis results on drug-eluting stents?

29. Should we trust meta-analyses?It depends on their internal validity!

30. Oxman-Guyatt index of internal validity 1. Where the search methods used to find evidence stated? 2. Was the search for evidence reasonably comprehensive? 3. Were the criteria for deciding which studies to include in the overview reported 4. Was bias in the selection of studies avoided 5. Were the criteria used for assessing the validity of the included studies reported? 6. Was the validity of all studies referred to in the text assessed using appropriate criteria 7. Were the methods used to combine the findings of the relevant studies reported? 8. Were the findings of the relevant studies combined appropriately relative to the primary question the overview addresses? 9. Were the conclusions made by the author(s) supported by the data and/or analysis reported in the overview? Oxman et al, J Clin Epidemiol 1991

31. Biondi-Zoccai et al, BMJ 2006

32. Steg et al, Arch Intern Med 2007

33. Learning goals • Why such a fuzz on meta-analyses? • What is a meta-analysis? • Are meta-analyses useful? • How can I appraise the internal and external validity of a meta-analysis? • What are the meta-analysis results on drug-eluting stents?

34. Synopsis Meta-analyses showing a DES hazard Meta-analyses suggesting DES safety Bavry et al, Am J Med 2006 Camenzind et al, Circ 2007 Kastrati et al, NEJM 2007 Nordmann et al, Eur Heart J 2006 Spaulding et al, NEJM 2007* Stone et al, NEJM 2007* Dibra et al, J Am Coll Cardiol 2007 Holmes et al, Eur Heart J 2006* Mauri et al, NEJM 2007* Pasceri et al, Am Heart J 2007 Stettler et al, Lancet 2007 *likely stemming from the same analysis set STOP! GO!

35. Nordmann et al, Eur Heart J 2006

36. Bavry et al, Am J Med 2006

37. Camenzind et al, Circulation 2007

38. Camenzind et al, Circulation 2007

39. Spaulding et al, NEJM 2007

40. Hazard ratio for death Kastrati et al, NEJM 2007

41. P=0.02 Kastrati et al, NEJM 2007

42. Mauri et al, NEJM 2007

43. Stone et al, NEJM 2007

44. Stone et al, NEJM 2007

45. Meta-analysis on 5 studies-1230 pts with DES implantation for ISR: TLR Dibra et al, J Am Coll Cardiol 2007

46. Cypher versus Taxus meta-analysis Schomig et al, JACC 2007

47. Hazards of mixing and duplicating data Kereiakes et al, JACC 2007

48. Stettler et al, Lancet 2007

49. Rationale of indirect/network meta-analyses OR (A vs C) TREATMENT A TREATMENT C ln ORa-b = ln ORa-c – ln ORb-c OR (A vs B) var (ln ORa-b) = var (ln ORa-c) – var (ln ORb-c) TREATMENT B TREATMENT C OR (B vs C) Biondi-Zoccai et al, Minerva Cardioangiol 2008

50. Rationale of indirect/network meta-analyses Patients randomized to treatment A vs treatment C Patients randomized to treatment B vs treatment C Patients randomized to treatment A vs treatment C Patients randomized to treatment B vs treatment C Large theoretical overlap between patients randomized to A vs C and to B vs C ↓ UNADJUSTED INDIRECT META-ANALYSIS OF A VS B LIKELY RELIABLE Small theoretical overlap between patients randomized to A vs C and to B vs C ↓ UNADJUSTED INDIRECT META-ANALYSIS OF A VS B LIKELY UNRELIABLE (multivariable methods recommended) Biondi-Zoccai et al, Minerva Cardioangiol 2008