1. Study Design Clinical Epidemiology Concepts and Glossary

2. Types of research Observational –Descriptive –Analytic Experimental

3. Descriptive Research Case reports Case series Cross sectional studies –simple cross-sectional studies determining, for example, how common (prevalence) is a condition? More complex cross-sectional involving comparisons are dealt with under analytic research. Longitudinal studies –Subjects must be followed up one or more times to determine their prognosis or outcome

4. Analytic Research Ecological studies Cross-Sectional, two-group studies Case control studies (retrospective) –Nested case control studies Cohort studies (prospective) –Historical cohort studies

5. Intervention Studies Controlled trials –Concurrent (parallel) controls Randomized Not randomized –Sequential controls Self controlled Crossover Studies without controls

6. Systematic Review Systematic reviews can help practitioners keep abreast of the medical literature by summarizing large bodies of evidence and helping to explain differences among studies on the same question. A systematic review involves the application of scientific strategies, in ways that limit bias, to the assembly, critical appraisal, and synthesis of all relevant studies that address a specific clinical question. A meta-analysis is a type of systematic review that uses statistical methods to combine and summarize the results of several primary studies.

7. Meta Analysis Meta-analysis is not an exact science. In putting many studies together, invariably some assumptions have to be made. Different methods of calculations are therefore developed using different assumptions. Those who use meta- analysis should therefore be familiar with the theories behind these methods.

8. Steps of Meta Analysis The first step is to create the Effects Table. This effects table is then used for all subsequent procedures. The second step is to decide whether it is legitimate to combine the list of studies, so that some estimation of homogeneity is carried out. If the list is heterogeneous, then the reasons is sought, and the list is rearranged so that homogenous sub-lists are selected and used. The third step is to combine the studies to produced a summary conclusion. A weighted averaged Effect and its variance is produced.

9. Meta Analysis difference between two Means Treatment GroupPlacebo Group Study NumberMeanSDNumberMeanSD 1345.964.241136.824.72S1 1754.744.641515.075.38S2 1372.042.591402.513.22S3 1842.72.321793.22.46S4 1746.094.861695.815.14S5 7544.725.337364.765.29S6 20910.18.120910.97.9S7 11512.823.0511223.013.32S8

10. Meta Analysis OR Study Id Treatment GroupPlacebo Group Treatment DeathSurviveDeathSurvive S12817651151Diet S27021538109Drug S3371194079Drug S4286327Drug S50303 Drug S66121882194Drug S74116555151Diet

11. Meta Analysis OR( Match Design ) (+, +)(-, +)(+, -)(-, -)StudyDiet 2518617S1A 44351534S2A 53192122S3B 26251019S4A 73354948S5B 58393766S6B 26471016S7A 42321829S8B 56421425S9B 2325813S10A 71412142S11B

12. Meta Analysis HR LogHRSELogHRVarLogHRStudy -0.1350.079949.88036E-05S1 -0.2570.07340.00017956S2 -0.4610.04920.00242064S3 0.2030.04010.00160801S4 -0.7980.12030.00041209S5 -0.3240.09330.00017689S6 -0.5510.05770.00332929S7 -0.6820.10840.00007056S8 -0.3340.13850.00148225S9 -0.3840.04720.00222784S10

13. Meta Analysis: Example 2 StudyTreatedControl MeanSDnMeanSDn 10.301.261620.421.28175 20.170.90150.830.9820 30.201.10300.451.1232 40.171.38270.421.3625 Diana B Petitti: P117 Summary mean difference ~(0.00, 0.44)

14. Meta Analysis: Example 2 TreatmentControl European Stroke Prevention Study Group (1987): OR=0.64 Events182264 Nonevents1068986 United Kingdom Transient Ischemic Attack Aspirin Trial: OR=0.82 Events348204 Nonevents1273610 Summary OR=0.72 (0.63, 0.84) Diana B. Petitti: P101