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 ( ) 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. Randomized Clinical Trial
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