Primer on Statistics for Interventional Cardiologists

1. Primer on Statistics for Interventional CardiologistsGiuseppe Sangiorgi, MDPierfrancesco Agostoni, MDGiuseppe Biondi-Zoccai, MD

2. Why waisting time with statistics? BMJ 2003

3. What you will learn - hopefully! • Introduction • Basics • Descriptive statistics • Probability distributions • Inferential statistics • Finding differences in mean between two groups • Finding differences in mean between more than 2 groups • Linear regression and correlation for bivariate analysis • Analysis of categorical data (contingency tables) • Analysis of time-to-event data (survival analysis) • Advanced statistics at a glance • Conclusions and take home messages

4. What you will NOT learn • Multivariable analysis • Advanced linear regression methods • Logistic regression • Cox proportional hazards analysis • Generalized linear models • Bayesian methods • Propensity analysis • Resampling methods • Meta-analysis • Most popular statistical packages (beyond SPSS)

5. What you will learn • Introduction • Basics • Descriptive statistics • Probability distributions • Inferential statistics • Finding differences in mean between two groups • Finding differences in mean between more than 2 groups • Linear regression and correlation for bivariate analysis • Analysis of categorical data (contingency tables) • Analysis of time-to-event data (survival analysis) • Advanced statistics at a glance • Conclusions and take home messages

6. What to choose? or … fast buttough? Simpleand easy-going

7. Science or fiction? There are three kind of lies: lies, damn lies, and statistics B. Disraeli Knowledge is the process of piling up facts, wisdom lies in their simplification M. Fisher

8. What is statistics? • DEFINITIONS • A whole subject or discipline • A collection of methods • Collections of data • Specially calculated figures

9. What is statistics? • DEFINITIONS • A whole subject or discipline • A collection of methods • Collections of data • Specially calculated figures

10. A collection of methods

11. Statistics is great • Find out stuff • Finding stuff out is fun • Feel like you have done something • It’s small, but it’s something • Understandstuff • When are we being deceived • Support, or illumination?

12. Ultimate goal: appraisal of causation

13. Methods of inquiry Statistical inquiry may be… Descriptive (to summarize or describe an observation) or Inferential (to use the observations to make estimates or predictions)

14. Questions?

15. What you will learn • Introduction • Basics • Descriptive statistics • Probability distributions • Inferential statistics • Finding differences in mean between two groups • Finding differences in mean between more than 2 groups • Linear regression and correlation for bivariate analysis • Analysis of categorical data (contingency tables) • Analysis of time-to-event data (survival analysis) • Advanced statistics at a glance • Conclusions and take home messages

16. What you will learn • Basics • concepts of population and sample • collecting data • study design and protocol • randomization • intention-to-treat vs per-protocol analysis • types of variables • measurement scales

17. What you will learn • Basics • concepts of population and sample • collecting data • study design and protocol • randomization • intention-to-treat vs per-protocol analysis • types of variables and measurement scales

18. Population and sample: at the heartofdescriptive and inferentialstatistics Again: statistical inquiry may be… Descriptive (to describe a sample/population) or Inferential (to measure the likelihood that estimates generated from the sample may truly represent the underlying population)

19. Descriptive statistics 100 100 AVERAGE

20. Descriptive statistics example

21. Descriptive statistics Meredith et al, Am J Cardiol 2007

22. Descriptive statistics example Meredith et al, Am J Cardiol 2007

23. Inferential statistics If I become a scaffolder, how likely I am to eat well every day? Confidence Intervals P values

24. Inferential statistics Mauri et al, New Engl J Med 2007

25. Inferential statistics Mauri et al, New Engl J Med 2007

26. Focus on p values Mauri et al, New Engl J Med 2007

27. Focus on confidence intervals Mauri et al, New Engl J Med 2007

28. Samples and populations This is a sample

29. Samples and populations And this is its universalpopulation

30. Samples and populations example

31. Samples and populations Only 300 patients! Kastrati et al, JAMA 2005

32. Samples and populations This is anothersample

33. Samples and populations And thismightbeits universalpopulation

34. Samples and populations Butwhatif THIS is its universalpopulation?

35. Samples and populations Anyinferencethus depend on ourconfidence in itslikelihood

36. What you will learn • Basics • concepts of population and sample • collecting data • study design and protocol • randomization • intention-to-treat vs per-protocol analysis • types of variables and measurement scales

37. Data collection • Data collection is pivotal and should be planned well before actually performing it • Any variable or item code should be collected in a clear and unequivocal way • A missing code is still a code (eg 999) • Data types can be dozens: • String • Categorical • Ordinal • Data • Time • Interval

38. Data collection • Coherence and safety checks should always be implemented • Multiple data entry should be used to minimize human error • Thorough monitoring and quering are also critical • Currently, the best approach for data collection in the current era are web-based case report forms (CRF) • Despite this, the risk of information bias is always there and should be kept at a minimum as much as possible

39. What you will learn • Basics • concepts of population and sample • collecting data • study design and protocol • randomization • intention-to-treat vs per-protocol analysis • types of variables and measurement scales

40. Designs for various research goals • CASE STUDY/REPORT/SERIES • SURVEY • CROSS SECTIONAL • MATCHED PAIRS (CASE-CONTROL) • HISTORICAL CONTROLS (BEFORE-AFTER) • CONCURRENT CONTROLS • LONGITUDINAL (COHORT) • CROSS-OVER • RANDOMIZED CLINICAL TRIAL • META-ANALYSIS

41. Phases of clinical research ANIMAL PHARMACOLOGY AND TOXICOLOGY PHASE I PHASE II PHASE III PHASE IV CHEMICAL STUDIES REGULATORY APPROVAL PILOT/FEASIBILITY STUDY PIVOTAL STUDY POST-MARKETING STUDY REGISTRATION (CE MARK) MARKETING

42. ENDEAVOR I Phase I FIM 60 month results ENDEAVOR II Double-blind Randomized Trial 48 month results ENDEAVOR II CA Registry Continued Access Safety 48 month results ENDEAVOR III Confirmatory Trial vs. Cypher 36 month results ENDEAVOR IV Confirmatory Trial vs. Taxus 24 month results Single Arm Trial 12 month results ENDEAVOR Japan Real-World Performance and Safety Evaluation – 12 month results E-Five Registry Endeavor vs. Cypher Safety Study 8,800 patient RCT PROTECT Endeavor research program

43. Reviews

44. Preclinicalstudies Joner et al, JACC 2008

45. Case report(s) McFadden et al, Lancet 2004

46. Cross-sectionalstudy

47. Case-controlstudy

48. Before-afterstudy

49. Cohort study (registry) Lee et al, EuroInterv 2007

50. Cohort study (registry) Lee et al, EuroInterv 2007