2. Clinical Trials
A clinical trial : prospectively planned experiment for the
purpose of evaluating potentially beneficial therapies or
treatments
In general, these studies are conducted under as many
controlled conditions as possible so that they provide
definitive answers to pre-determined, well-defined questions
3. Why Clinical Trials?
1. Most definitive method to determine whether a
treatment is effective.
Other designs have more potential biases
One cannot determine in an uncontrolled setting
whether an intervention has made a difference in
the outcome.
4. Why Clinical Trials?
2. Help determine incidence of side effects and
complications.
3. Theory not always best path
5. TYPES
3 ways of classification
Researchers behavior
Clinical observational study
Interventional study
Purpose based
Prevention trials
Screening trials
Diagnostic trials
Treatment trials
Supportive care trials
6. TYPES
Weather trial design allow changes based on data
accumulated
Fixed trial
Adaptive clinical trial
Miscellaneous types
Field trials
Community trials
8. Phase 0Phase 0
Also called Human Micro-dosing studies.
Gathers preliminary data Pharmacodynamics
and Pharmacokinetics.
Gives no data on safety or efficacy.
Small number of subjects (10-15).
9. Phase IPhase I
First stage of testing in human subjects (20-100).
Designed to assess the safety, tolerability, PK and PD
of drug.
Dose ranging – Dose escalation.
11. Phase IIIPhase III
Therapeutic confirmatory trials. (300-3000 subjects).
To establish efficacy of the drug against existing
therapy in larger number of patients, method of
usage etc.,.
12. Phase IVPhase IV
Post Marketing Studies (PMS).
Involves safety surveillance.
Determine behavior of drug in real life situations.
Evaluate action of drug in a situation of missed dosage or
over dosage.
13. CLINICAL TRIAL PROTOCOL
Defines and manages trial
Required by the regulatory organizations
Prepared by panel of experts
Provides background about the trial
Specifies trial objectives
Describes trial design
Ensures that trial procedures are consistently carried out
14. COMPONENTS
1. General information
Title of trial
Names and adresses of investigators and sponsors
Identity of trial site
2. Justification and objectives
Reason for execution of trial
Primary hypothesis to be tested
Primary end point
15. COMPONENTS
3. Design
Response variables
(nature of response variable , scoring system)
Efficacy
(magnitude of difference to be detected between treatment and control groups)
4. Duration
Date of beginning
Date of end
Duration of disease under study
Duration of treatment
Drug withdrawal period
Decision rules for terminating a trial
16. COMPONENTS
5. Experimental population
Population in which trial is conducted
Should be representative of target population
Experimental unit
(smallest independent unit to which treatment is randomly allocated)
Composition (e.g. Age , sex , breed)
Inclusion/exclusion criteria
Selection of controls (to allow discrimination of patient outcomes caused
by other factors , fair comparisons)
17. COMPONENTS
Sample size determination
• Level of significance
• Power
Owners informed consent
6.Therapeutic or prophylactic procedure
Dosage
Product formulation and identification
Placebo/standard treatment formulation and identification
Method of administration
Operators safety
18. Bias and Variability
The clinical trial is considered to be the “gold standard” in
clinical research
Clinical trials provide the ability to reduce bias and
variability that can obscure the true effects of treatment
Bias ⇒ affects accuracy
Variability ⇒ affects precision
19. Bias: any influence which acts to make the observed
results non-representative of the true effect of therapy
Examples:
healthier patients given treatment A, sicker patients
given treatment B
treatment A is “new and exciting” so both the
physician and the patient expect better results on A
20. Variability: high variability makes it more difficult to
discern treatment differences
Some sources of variability
Measurement
instrument
Observer
Biologic
within individuals
between individuals
21. Fundamental principle
in comparing treatment groups:
Groups must be alike in all important aspects and only
differ in the treatment each group receives
In practical terms, “comparable treatment groups” means
“alike on the average”
22. Why is this important?
If there is a group imbalance for an important factor
then an observed treatment difference may be due to
the imbalance rather than the effect of treatment
Example:
Drug X versus placebo for osteoporosis
Age is a risk factor for osteoporosis
Older subjects are enrolled in Drug X group
Treatment group comparison will be biased due to
imbalance on age
23. How can we ensure comparability of
treatment groups?
We can not ensure comparability but randomization helps
to balance all factors between treatment groups
If randomization “works” then groups will be similar in all
aspects except for the treatment received
24. Randomization
Allocation of treatments to participants is carried out
using a chance mechanism so that neither the patient
nor the physician know in advance which therapy will
be assigned
Simplest Case: each patient has the same chance of
receiving any of the treatments under study
26. Simple Randomization
• Think of tossing a coin each time a subject is eligible to
be randomized
HEADS: Treatment A
TAILS: Treatment B
• Approximately ½ will be assigned to treatments A and B
27. Problem with Simple Randomization:
May result in substantial imbalance in either
an important baseline factor and/or
the number of subjects assigned to each group
Solution: Use blocking and/or stratified randomization
28. Block Randomization
Arranging experimental units in groups that are similar to
one another
Typically , blocking factor is source of variability that is
not of primary interest to the experimenter
29. The Randomized Block Design
Divides the group of experimental units into n
homogeneous groups of size t
These homogeneous groups are called blocks
The treatments are then randomly assigned to the
experimental units in each block - one treatment to a unit
in each block
30. Stratification Example
To ensure balance on an important baseline factor,
create strata and set up separate randomization
schedules within each stratum
Example: if we want prevent an imbalance on age in
an osteoporosis study, first create the strata “< 75
years” and “≥ 75 years”
then randomize within each stratum separately
Blocking should be also be used within each stratum
32. Blinding
Masking the identity of the assigned interventions
Main goal: avoid potential bias caused by conscious
or subconscious factors
Single blind: patient is blinded
Double blind: patient and assessing
investigator are blinded
Triple blind: committee monitoring
response variables (e.g.
statistician) is also blinded
33. How to Blind
To “blind” patients, can use a placebo
Examples
pill of same size, color, shape as treatment
sham surgery
sham device such as sham acupuncture
34. General Study Designs
Parallel group designs
Type of clinical design which compares two treatments
(A and B) so that one group receives only A while other
group receives only B
R
A
N
D
A
B
C
control
35. Cross-Over Designs
Subjects are randomized to sequences of treatments
(A then B or B then A)
Uses the patient as his/her own control
Often a “wash-out” period (time between treatment
periods) is used to avoid a “carry over” effect (the
effect of treatment in the first period affecting
outcomes in the second period)
Can have a cross-over design with more than 2
periods
37. Cross-Over Designs
Advantage: treatment comparison is only subject to
within-subject variability not between-subject
variability
⇒ reduced sample sizes
Disadvantages:
strict assumption about carry-over effects
inappropriate for certain acute diseases (where a
condition may be cured during the first period)
drop outs before second period
38. General study designs
Sequential trials
It is one whose conduct at any stage depends on the
results so far obtained
Two treatments are compared , experimental units enter
the trial in pairs
Results are analyzed sequentially according to the
outcome in the pairs
39. Sequential Design
Continue to randomize subjects until H0 is either rejected
or “accepted”
A large statistical literature for classical sequential
designs
Developed for industrial setting
40. General study designs
Advantages:
1. Early detection of beneficial treatment effects
2. Require fewer experimental units
3. Significance tests can be conducted repeatedly on
accumulating data
42. Losses to “follow-up”
It refers to subjects who at one point in time were actively
participating in a clinical trial ,but have become lost at the
point of follow-up in trial
Reasons:
• Withdrawal from the trial without informing investigator
• Moved away from the trial site
• Became ill and unable to communicate
43. Compliance
Success of a trial depends on participants acting in
accordance with the instructions of the trial designers;
that is, complying with treatment
Reasons for poor compliance
1. Unclear instructions
2. Forgetfulness
3. Inconvenience of participation
4. Disappointment with results
5. Side effects
44. Terminating a trial
It may be necessary to terminate a trial prematurely if
there are serious adverse side effects in the treatment
group, and such a decision rule should be written into the
trial’s protocol
