This document discusses experimental study designs, specifically randomized clinical trials. It describes key aspects of randomized trials including multiple experimental groups, blinding techniques, objectives related to public health and clinical practice, and historical examples. Randomized trials are identified as the ideal design for evaluating new interventions by comparing outcomes between randomized treatment groups to eliminate selection bias. Key aspects covered include selection and stratification of subjects, data collection on variables like treatment received, outcomes, and prognostic profiles, as well as blinding techniques.

1. Experimental Studies
BY
DR MUHAMMAD TAUSEEF JAVED
CONSULTANT MINISTRY OF HEALTH
MAKKAH
&
IPH LAHORE

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. • 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:
Studies with Comparison (cont.)

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

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