Understanding Experimental Studies: Design and Perspectives

1. Experimental Studies

2. Types of Experimental Studies • Multiple experimental groups • Blinds • single, double, triple

3. Public Health & Clinical Objectives • Modify natural history of disease and express disease prognosis • Prevent or delay death or disability • Improve health of patient or population • Need to use best preventive or therapeutic measures • Randomized trials are ideal design to evaluate effectiveness and side effects of new forms of intervention

4. Historical Perspectives • Sir Francis Galton (1883) - ruminated over the influence of prayer • Joyce and Welldon (1965) found no benefit of prayer • R. C. Byrd (1988) - suggested positive benefits • Washington Post Parade article (2003) - also suggested positive benefits

6. Recent Perspectives • Effect of: • coffee on CHD • carotene on cancers • hormonal therapy on breast cancer • drug-lowering cholesterol on CHD

7. Randomized Trials • Historically, were done accidentally, in other words, “unplanned trials” • Ambroise Pare (1510 - 1590) discovered new treatment for war wounds when original therapy was unavailable • James Lind (1747) studying scurvy • Subjects assigned to groups using a non-biased procedure

8. Design of a Randomized Clinical Trial

9. Selection of Subjects • Well-designed • Eliminate subjectivity • Promote reliability • Replicable, as with laboratory experiments • Accurate

10. Selection of Subjects:Studies without Comparison • Question: If we administer a drug and the patient improves, can we attribute the improvement to the administration of that drug? • Answer:Results can always be improved by omitting controls. - Prof. Hugo Muensch Harvard University

11. Selection of Subjects:Studies with Comparison • Historical controls (comparison group from past) • Data must be abstracted from records not kept for research purposes • Differences may be due to quality of the data • May not be able to substantiate differences • Can be useful for drugs developed against fatal diseases

12. Selection of Subjects: Studies with Comparison(cont.) • Simultaneous Non-Randomized Controls • May introduce bias • Example - BCG vaccination study in NYC in 1975 • Investigators introduced selection bias in the experimental group and controls • A change in the study design that eliminated selection bias, although still not randomized, also eliminated differences observed in final results

15. Selection of Subjects (cont.):Randomization • Best approach • Uses tables of random numbers • Must still eliminate physician bias • Can achieve non-predictability

17. Effect of Comparability Not Randomized Randomized

18. Selection of Subjects (cont.):Stratified Randomization • Useful when concerned that certain variables may affect the outcome • For example, when the prognosis may be much worse for older patients • Want two treatment groups to be comparable in terms of the variables of concern • Initially stratify (layer) the study population according to each variable of concern and then randomize participants to treatment groups within each stratum

19. Selection of Subjects (cont.):Stratified Randomization

20. Data Collection on Subjects:Potential Variables • Treatment: • that was assigned • that was received • Outcome • Explicit criteria required • Comparable measurements required • Prognostic Profile at Entry • If risk factors for a bad outcome are known, assure that treatment groups are reasonably similar for these factors • Data for prognostic factors obtained upon enrollment in study • Masking (Blinding)

21. Data Collection on Subjects(cont.):Masking (Blinding) • Attempt to eliminate biases & preconceptions • Single-blind • Subject masking • Use of placebo • Double-blind • Subject masking and researcher masking • Data collectors and data analysts • Triple-blind • Subject masking, researcher masking and study sponsor masking