1. Study Designs for Health Professionals Ashry Gad Mohamed, MB.ChB, MPH, DrPH Professor of Epidemiology College of Medicine & KKUH

2. Objectives At the end of the presentation each participant should be able to: 1-know main designs for biomedical researches. 2-Select the proper design for each research question. 3-list areas of strength and weakness of each design. 4-interpret the parameters of expression of study results.

3. Descriptive Analytical Case report Case series Cross section Ecological Case control Cohort Observational Experimental Study Designs Animal Experiment Human Intervention Clinical trial

4. Case Report Detailed presentation of a single case Generally report a new or unique finding Previous unknown disease Unexpected link between diseases Unexpected new therapeutic effect Adverse events

5. Case Series Experience of a group of patients with a similar diagnosis Cases may be identified from a single or multiple sources Generally report on new/unique condition May be only realistic design for rare disorders

6. Case Series Advantages Useful for hypothesis generation Informative for very rare diseases with few established risk factors Disadvantages Cannot study cause and effect relationships Cannot assess disease frequency

7. Cross-sectional Study Data collected at a single point in time Describes associations Prevalence

8. Cross-sectional Studies Frequent conditions with long duration of expression (nonfatal, chronic conditions) It measures prevalence, not incidence of disease Not suitable for studying rare or highly fatal diseases or a disease with short duration of expression

9. Prevalence vs. Incidence Prevalence –The total number of cases at a point in time –Includes both new and old cases Incidence –The number of new cases over time

10. Cross-sectional Study Sample of Population Physically active life style Sedentary life style Prevalence of IHD Time Frame = Present

11. Cross-sectional studies Disadvantages Weakest observational design, (it measures prevalence, not incidence of disease). The temporal sequence of exposure and effect may be difficult or impossible to determine Usually don’t know when disease occurred Rare events a problem. Quickly emerging diseases a problem

13. Case-Control Study Patients with CAD Patients w/o CAD Present Past High fish Diet Low fish Diet Cases Controls

14. Case-Control Studies: Strengths Good for rare outcomes: cancer Can examine many exposures Useful to generate hypothesis Fast Cheap

15. Case-Control Studies: Weaknesses Cannot measure –Incidence –Prevalence –Relative Risk Can only study one outcome High susceptibility to bias

16. Analysis of case control study Because population at risk is absent we can not calculate relative risk as it is based on incidence, however it can be estimated by means of odds ratio (OR) which is the ratio of odds of exposure among diseased to the odds of exposure among controls.

17. Exposure for each case and control Disease status Cases Controls Exposure Yes NO BA DC B+DA+C

18. Calculating Odds (number exposed  number unexposed) Odds (Cases) = A/C Odds (controls) = B/D Odds Ratio = (A/C) / (B/D) = AD/BC

19. Disease Status No CHD (Controls) CHD (Cases) 22488 176112 400200 Fish diet No fish Total Odds Ratio= AD BC = 176 X 88 112 X 224 = 0.62 Example

21. Cohort Study Begin with disease-free patients Classify patients as exposed/unexposed Record outcomes in both groups Compare outcomes using relative risk

22. Cohort Study: Strengths Provides incidence data Establishes time sequence for causality Eliminates recall bias Allows for accurate measurement of exposure variables

23. Cohort Study: Weaknesses Exposure may change over time Disease may have a long pre-clinical phase Attrition of study population

24. Measuring the effect of risk factor Relative Risk = (a/a+b) / (c/c+d) Risk factor OutcomeTotal presentabsent Presentaba +b Absentcdc +d Totala +cb+dN

25. Obesity & Diabetes ObesityDiabetesTotal presentabsent Present43369412 Absent29601630 Total72b+d1042 RR= (43/412) / (29/630) =0.104 / 0.046 =2.26

26. Clinical trial

27. Definition a planned experiment on humans. The setting is in health institutions environment. It usually involves patients. Rationale Before a new treatment method is made available to the public it must be studied and tested for safety and effectiveness.

28. Clinical trials provide the “gold standard” of determining the relationship between garlic and cardiovascular disease prevention.

29. Clinical Trial Study sample Treatment Group Control Group Outcomes RandomizeRandomize

30. Allocation of regimens Intervention versus Placebo Current treatment Nothing Randomization Aim Methods

31. Blinding One or more of the people involved in the trial is unaware of the intervention. 1- Open trial 2- Single- blind trial 3- Double blind trial 4-Double blind double dummy trial 5- Triple and quadruple blind

32. Follow up Quantity Quality Compliance

33. Analysis 60 45 15 Intension to treat analysis. 15/ 60 =0.25 =25% Protocol analysis. 15/45 = 0.33 =33%

34. Relative Risk TotaloutcomeGroup Negativepositive a +bbaIntervention c +ddcControl

35. Measures of effect size 1-Relative risk (RR) – Is the ratio of the risk of a given event in one group of subjects compared to another group Experimental Event Rate (EER) ----------------------------------------------- Control Event Rate (CER ) EER: The percentage of intervention group who experienced outcome in question. ( a/(a + b)) CER: The percentage of control group who experienced outcome in question. (c /( c + d))

36. 2 -Relative risk reduction (RRR) – The proportion of the initial or baseline risk which was eliminated by a given treatment/intervention or by avoidance of exposure to a risk factor RRR= (CER – EER) / CER 3-Absolute risk reduction (ARR) – The difference in risk of a given event, between two groups ARR= CER - EER

37. 4-Number Needed to Treat (NNT) It is defined as the number needed to treat in order to prevent one additional adverse event (e.g. death) NNT = 1/ ARR –Its clinical importance depends on Initial probability of the outcome.

38. RR=(18/64) / (29/65) = 0.281/0.446 =0.63 =63% 95% CI= 0.39 – 1.01 Source: N Engl J Med 1992; 326: 1527-1532. InterventionOutcomeTotal Deathsurvival Ligation184664 sclerotherapy293665

39. 2 - Absolute Risk Reduction (ARR): ARR= CER - EER =(29/65) – (18/64) = 0.446 – 0.281 = 0.165 = 16.5% 3-Relative Risk Reduction (RRR) RRR= (CER – EER) / CER =(0.446 – 0.281) / 0.446 =0.165 / 0.446 = 0.37 = 37% i.e. Legation decreases the risk of death by 37%

40. 4-N umber Needed to Treat (NNT): NNT = 1/ ARR = 1 / 0.165 = 6.06 =6 patients You have to treat 6 patients by ligation to save one life

42. Clinical Trials Strengths: –Best measure of causal relationship –Best design for controlling bias –Can measure multiple outcomes Weaknesses: –High cost –Ethical issues may be a problem –Compliance

43. What is the best study design? A young patient who had ventricular tachycardia after an sports activity Hypersensitivity reactions associated with exposure to naproxen and ibuprofen.

44. Thromboembolic Stroke in Young Women and use of oral Contraceptives. Exposure to benzene and non-Hodgkin lymphoma.

45. SCH 503034, a novel hepatitis C virus protease inhibitor, plus pegylated interferon alpha-2b for genotype 1 nonresponders. Risk factors among young women with endometrial cancer.

46. The annual incidence and course of neck pain in the general population. The prevalence of pressure ulcers in hospitalised patients in The Netherlands.

47. Strangulated hernia with ileal perforation due to abdominal trauma in a paediatric patient. Valsartan in a Japanese population with hypertension and other cardiovascular disease.

48. The effects of rosiglitazone on echocardiographic function and cardiac status in type 2 diabetic patients with functional Class I or II Heart Failure. lymphoblastoid interferon-α for chronic hepatitis C.

49. Efficacy of interferon-gamma1b in chronic hepatitis C patients with advanced fibrosis or cirrhosis.