Lectures 14 Experimental Methods
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Transcript Lectures 14 Experimental Methods
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
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