Experimental Studies

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

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

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

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

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

Randomized Clinical Trial Design of a Randomized Clinical Trial

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

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

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

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

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

Effect of Comparability Not Randomized Randomized

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

Selection of Subjects (cont.): Stratified Randomization

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)

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