Measures of Effect: An Introduction

1. Measures of Effect: An Introduction Philip la Fleur, RPh MSc(Epidem) Deputy Director, Center for Life Sciences plafleur@kazcan.com Epidemiology Supercourse Astana, July 2012

2. Come to Ottawa, Canada and get “Out and About”

3. Canadian Agency for Drugs and Technologies in Health (www.cadth.ca) Emerg Med J 2003;20:164-168 

4. Objectives Understand how to calculate and interpret and articulate measures of effect and morbidity • 2x2 Table • Risk • Odds • Relative Risk • Odds Ratio • Relative Risk Reduction and Absolute Risk Reduction • Number needed to Treat and Number needed to Harm

5. Summary

6. 1. 2x2 Table

7. Risk • Probability that an event will occur (Last 2001) • E.g. that a person will die within one year • Risk in Exposed = a/(a+b) • Risk in unexposed, “Baseline risk” = c/(c+d)

8. Odds • The ratio of the probability of occurrence of an event to that of non-occurrence • E.g. odds of smokers developing a chronic cough • Odds in Exposed = a/b • Odds in unexposed, “Baseline odds” = c/d

9. Risk Versus Odds 0.80 4.0 ⌂⌂⌂⌂/⌂ 0.67 2.0 ⌂⌂/⌂ 0.50 1.0 ⌂/⌂ 0.20 0.25 ⌂/⌂⌂⌂⌂ 0.10 0.11 ⌂/⌂⌂⌂⌂⌂⌂⌂⌂⌂ Conversion: Odds = Risk/(1-Risk) Risk = Odds / (1 + Odds)

10. Would you swim here?

11. Develop a Question: PICO Population: children under 5 years of age Intervention (exposure): Swimming in the Ishim River Comparator (control): Not swimming in the Ishim river Outcome: Otitis Media Question: What is the risk that a child under 5 will develop an ear infection after swimming in the Ishim river?

12. Odds Ratio

13. Odds Ratio Odds of getting infection for swimmers: 40/60 = 0.67 Odds of getting infection for non-swimmers: 5/95 = 0.052

14. Relative Risk

15. Relative Risk Risk of getting infection for swimmers: 40/100 = 0.4 Risk of getting infection for non-swimmers: 5/100 = 0.05

16. OR versus RR Key Messages • Odds and Odds Ratios are difficult to conceptualize but statisticians prefer them in some situations because of their mathematical properties • Odds Ratios always exaggerate the relative risk, but when baseline risk is low (e.g. <10%), the OR approximates the relative risk • Relative Risk is a more intuitive measure and is becoming more common in medical literature

17. Objectives Understand how to calculate and interpret and articulate measures of effect and morbidity • 2x2 Table • Risk • Odds • Relative Risk • Odds Ratio • Relative Risk Reduction and Absolute Risk Reduction • Number needed to Treat and Number needed to Harm

18. 2. Relative Risk Reduction and Absolute Risk Reduction Objectives • Learn how to interpret risk of events in the control (baseline group) and intervention groups (treatment group) from published studies. • Understand the concepts of relative risk reduction and absolute risk reduction and how they usually differ from one population to another.

20. Trial 1: High Risk Patients • New drug for acute myocardial infarction to reduce mortality • First studied in a high risk population: • 40% mortality at 30 days among untreated • e.g., elderly, heart failure, anterior wall infarction Ref: http://www.cche.net/usersguides/ebm_tips.asp

21. Trial 1: High Risk Patients • New drug for acute myocardial infarction to reduce mortality • First studied in a high risk population: • 40% mortality at 30 days among untreated • e.g., elderly, heart failure, anterior wall infarction • 30% mortality among treated • How would you describe the effect of the new drug? Ref: http://www.cche.net/usersguides/ebm_tips.asp

22. Trial 1: High Risk Patients Ref: http://www.cche.net/usersguides/ebm_tips.asp

23. Trial 2: Low Risk Patients • New drug for acute myocardial infarction to reduce mortality • Later studied in a lower risk population: • 10% mortality at 30 days among untreated • e.g., younger, uncomplicated inferior wall infarction Ref: http://www.cche.net/usersguides/ebm_tips.asp

24. Trial 2: Low Risk Patients • New drug for acute myocardial infarction to reduce mortality • Later studied in a lower risk population: • 10% mortality at 30 days among untreated • e.g., younger, uncomplicated inferior wall infarction • 7.5% mortality among treated • How would you describe the effect of the new drug? Ref: http://www.cche.net/usersguides/ebm_tips.asp

25. Trial 2: Low Risk Patients Ref: http://www.cche.net/usersguides/ebm_tips.asp

27. Summary Points for Relative Risk Reduction and Risk Difference • Relative risk reduction is often more impressive than absolute risk reduction. • The lower the risk in the control group, the larger the difference between relative risk reduction and absolute risk reduction.

28. Objectives Understand how to calculate and interpret and articulate measures of effect and morbidity • 2x2 Table • Risk • Odds • Relative Risk • Odds Ratio • Relative Risk Reduction and Absolute Risk Reduction • Number needed to Treat and Number needed to Harm

29. 3. Number Needed to TreatNumber Needed to Harm Objectives • Learn how to calculate Number Needed to Treat (NNT) from an estimate of risk difference. • Increase awareness of the range of NNTs associated with common interventions.

30. Definitions • Number Needed to Treat (NNT): • Number of persons who would have to receive an intervention for 1 to benefit. • Number Needed to Harm(NNH): • Number of persons who would have to receive an intervention for 1 to be experience a adverse event.

31. Calculating NNT If a disease has a mortality of 100% without treatment and therapy reduces that mortality to 50%, how many people would you need to treat to prevent 1 death?

32. Estimate NNT Ref: http://www.cche.net/usersguides/ebm_tips.asp

33. Estimate NNT Ref: http://www.cche.net/usersguides/ebm_tips.asp

34. Estimate NNT Ref: http://www.cche.net/usersguides/ebm_tips.asp

35. Calculation NNT= 100/ARR (where ARR is %) or NNT= 1/ARR (where ARR is proportion) NNH= 100/ARI (where ARI is %) Or NNH = 1/ARI (where ARI is proportion)

36. NNTs from Controlled Trials 1 100 2.9 1.9 9.8 7.3 2.5 40 12 9.2 2.8 36 Ref: http://www.cche.net/usersguides/ebm_tips.asp

37. Population: hypertensive 60-year-oldsOutcome: stroke over 5 yearsDepiction of Results in Control Group Ref: http://www.nntonline.net/

38. Population: hypertensive 60-year-oldsOutcome: stroke over 5 yearsDepiction of Results in Treatment Group Ref: http://www.nntonline.net/

39. Bottom Line • It is easy to mis-estimate baseline risk and effects of therapy • NNT is easily calculated from the absolute risk reduction (ARR) • Awareness of threshold NNT can help anticipate the risk reduction to look for in a therapy.

40. Summary

41. References/Slide Sources • LastJM. A Dictionaryof Epidemiology, 4th ed. Oxford UniversityPress, 2001 • Guyatt G et al. Users’ Guides tothe Medical Literature, 2nd ed. McGraw Hill, 2008 • Guyatt G. TipsforTeachers of EvidenceBased Medicine. LectureonOdds and Risk. • Grimes and Schulz. MakingSense of Odds and Odds Ratios. Obs & Gyn 2008(111):423-6 • SomeSlidesforRiskReduction and NNT are from: Alexandra Barratt, Peter C. Wyer, Rose Hatala, Thomas McGinn, Antonio L. Dans, SheriKeitz, Virginia Moyer, Gordon Guyatt, Robert Hayward, fortheEBM TeachingTipsWorkingGroup (www.cche.net) • SmileyDiagramsfrom: Dr. Chris Cates EBM Website: www.nntonline.net