Types of clinical trials designs were discussed including parallel designs, crossover designs, factorial designs, cluster designs, and adaptive designs. The key factors in choosing a clinical trial design are treatment duration and chronology of events, trial cost, and subject convenience. Commonly used designs include parallel, crossover, factorial, and equivalence/non-inferiority designs. The randomized, double-blind, placebo-controlled, parallel design is often considered the best to determine efficacy. Different designs can answer different therapeutic questions.

1. Types of Clinical trials designs
Dr/ Eman Mortada
Professor
In public health and preventive medicine

2. Parallel designs
Crossover designs
Factorial design
Cluster design
Adaptive design
Superiority vs. noninferiority vs. equivalence
Lecture Outline

3. Treatment duration and Chronology of events:
Chronological effects may be very important in any trial
design and Carry over effects
Trial cost: Very lengthy trials may not be routinely
feasible due to prohibitive costs involved.
Subject convenience: Lengthy trials requiring multiple
visits and involving washout periods
Factors in choosing clinical trials designs
The quality of a clinical trial and its results heavily
depend on a well chosen clinical trial design.

4. Commonly Used Designs
 Parallel
 Cross Over
 Factorial
 Group/Cluster
 Equivalence/Non-inferiority
 The randomized, double-blind, placebo-controlled, parallel
design is considered to be the best to determine efficacy
 Different experimental designs can be used to answer
different therapeutic questions

5. Traditional Study designs

6. 1- RCT with parallel Design
❑ The most common clinical trial design
❑ A parallel design includes independent
study groups and each group receives a
different treatment regimen or intervention
❑ Parallel design is more useful for studying
conditions which are prone to change
over time (pain, acute exacerbations of a
disease, remissions)
❑ Complete randomized design in which each
patient receives one and only one treatment
in a randomized fashion.

7. Population
Sample
Intervention
Group
Control
Group
Assessment (T0)
Intervention
Group
Control
Group
Assessment (T1)
Randomization
RCT with parallel Design(cont’d)
Treatment
A
Treatment
B

8. Defined
Population
New
Treatment
Improved
Not
Improved
Placebo
Improved
Not
Improved
Randomization
e.g. In patients suffering from major depressive disorder,
does treatment with drug significantly reduce symptoms
compared to placebo?
Depressed patients

9. Assessed for
eligibility
Run-In
Period
R
A
N
D
O
M
I
Z
E
Unsatisfactory
Dropped
B
A
Satisfactory
Problem: Non-compliance by patient may seriously impair
efficiency and possibly distort conclusions
Possible Solution: Assign all eligible patients a placebo to be
taken for a “brief” period of time. Patients who are “judged”
compliant are enrolled into the study. This is often referred to
as the “Placebo Run-In” period.
Run-In Design

10. RCT with parallel Design(cont’d)
Advantages:
• Simple and easy to implement
• Universally accepted
• Applicable to acute conditions
• Analysis is less complicated and
interpretation of the results is
straightforward
Disadvantage:
• Inter-subject variation is not being
correlated.
▪ randomized,
▪ parallel-group
▪ controlled clinical
trial design is
generally considered
as the gold standard,
but in some situations it
is difficult to use this
design

11. 2- RCT with Cross-Over Designs
 Randomization of order in which treatments are received
 Subjects are randomized to sequences of treatments (A then B
or B then A)
 Uses the patient as his/her own control(Within patient
comparison)

12. Recruited
samples
Treatment A
Treatment B
Outcome 1
Outcome 2
Treatment B
Treatment A
Period 1
Randomization
Period 2
Randomization the series of treatments
Washout
period
RCT with Cross-over design(cont’d)

13. RCT with Cross over design(cont’d)
Group A Group B
WASH OUT PERIOD
Drug A
Drug B
Drug B
Drug A
RANDOMIZATION
⚫ A crossover
design is a
modified
randomized
block design
in which each
block receives
more than one
treatment at
different
periods.

14. Concept of Wash-out period
Often a “wash-out” period (rest period between 2 treatment periods)
is used to avoid a “carry over” effect / residual effects (the effect of
treatment in the first period affecting outcomes in the second period)
✓ It permits the effect of previous treatment to wane off.
✓ It depends upon the nature of the drug.
✓ It should be long enough for the treatment effect to wear off so that
there is no carryover effect of previous treatment to next.

15. Cross-Over Designs is appropriate for:
❑ Chronic conditions that are stable over time and
❑ for interventions that last a short time within the patient
and that do not interfere with one another.
Examples:
❑ Treatment of chronic pain
❑ Mouth wash treatment for gingivitis
The fundamental assumptions of crossover trials is that patients
usually have a chronically stable condition that will not vary
between when they are taking the first and second treatments.
Therefore, crossover trials are short-term trials.

16. Types of Cross-Over Design
Dr: Eman Mortada
1- Planned: planned reversal of
intervention and control treatments
2- Unplanned crossovers: intervention
participants do not comply, control
participants obtain the treatment

17. Cross-Over Designs(cont’d)
Advantage:
 This method is only subject to within-subject variability not
between-subject variability
 more accurate than simple experiments.
 reduced sample sizes
Disadvantages:
 “Carry over effects” may alter the response to subsequent
treatments.
 Inappropriate for certain acute diseases (where a condition
may be cured during the first period)
 Increased no. of study periods leads to subject drop outs
before second period& longer duration.

18. Split person design
Drug A Drug B
❑Occasionally, it is possible to administer the two interventions at
the same time.Very similar to that of the cross-over trial, except
there is no equivalent to the periods or to the wash-out although a
carry-over (now termed carry-across) effect is likely to be present.
❑ E.g. Comparison of hearing aids for hearing loss
Paired Organs

19. Parallel design vs Cross over design
Parallel design Cross over design
Groups assigned different
treatments
Each patient receives both
treatments
Shorter duration Longer
Larger sample size Smaller
No Carryover effect Carryover effect
Acute diseases In stable diseases
used in chronic not acute diseases

20. Latin Square Design
 Latin-square design differs from cross-over design in terms of
the number of studied treatments.
 Latin-square design is used when more than two treatments
are compared in the same trial.
 For example when three treatments are considered in the
trial, the corresponding Latin-square involves three treatment
periods and two wash-out periods occurring between each
treatment period for each of the three groups of patients
Design for three or more treatment

21. 2× 2 Factorial design
+
Drug A Drug B Drug A+B Neither Drug
3. Factorial Designs
❑It is the extension of parallel design
❑Two or more experimental treatments are evaluated
simultaneously through the use of varying combinations of the
treatments against a control.
❑It allows evaluation of the interaction that may exist between two
treatments (sometimes called effect modification)

22. 22
subject
Treatment
A
Treatment
B
Placebo
Placebo
Treatment
B
Placebo
Clinical Trial with Factorial Design

23. Factorial Design(cont’d)
A &B B
A NONE
Treatment A
+ -
+
-
Treatment
B

24. randomized
aspirin
Beta carotene
Beta carotene
placebo
Aspirin
placebo
Beta carotene
Beta carotene
placebo
Factorial Design:
The Physician’s Health Study
• Physicians randomized to:
❑ aspirin (to prevent cardiovascular disease)
❑ beta-carotene (to prevent cancer)
❑ aspirin and beta-carotene
❑ neither (placebo)

25. Factorial Designs(cont’d)
 Advantages:
 If no interaction, can perform two experiments with less
patients than performing two separate experiments
 Can examine interactions if this is of interest
 Disadvantages:
 Added complexity, impact on compliance or recruitment
 potential for adverse effects due to “poly-pharmacy”
Interaction: The effect of treatment A differs depending upon
the presence or absence of intervention B and vice-versa.

26. 4- Cluster design
❑ Randomization is done at cluster level rather than individual
level.
Randomization can be performed on intact social units- family, school,
worksites, athletic teams, etc.
❑ For assessment of non-therapeutic interventions such as lifestyle
intervention or new educational programs for smoking cessation.
❑ Examples:
❑ Community trials on fluoridation of water
❑ Breast self examination programs in different clinic setting
❑ Smoking cessation intervention trial in different school district

27. Clustering
School
Department Department
Class
S S
S S
S
S
Class
S S
S S
S
S
Class
S S
S S
S
S
Class
S S
S S
S
S
Class
S S
S S
S
S
Class
S S
S S
S
S

28. Randomisation of
Hospital/Clinic
New Intervention
All patients at
hospital/clinic
receive control
All patients at
hospital/clinic
receive new
intervention
Control group
Groups (clinics, communities) are randomized
to treatment or control

29. Advantages:
• Sometimes logistically more feasible
• Avoid contamination
• Allow mass intervention, thus “public health trial”
Disadvantages:
• Many units must participate to overcome unit-to-unit
variation,
thus requires larger sample size
• Need cluster sampling methods
Cluster Randomization(cont’d)

30. 5- Adaptive Designs
 FDA defines an adaptive trial as a
study that includes prospectively
planned opportunity for modification
of one or more specified aspects of the
study design and hypotheses based on
the interim data analysis, to decide
how to modify aspects of the study
without undermining the validity and
integrity of the trial.

31. 5- Adaptive Designs

32. When and Where? Trials with:
 High levels of uncertainty/unknowns (e.g. novel interventions)
 Design characteristics (e.g., power)
 Long FU: adaptation is feasible and medical practice can change
 Invasive procedures or expensive evaluations
 Serious diseases; high risk treatments
 Vulnerable populations

33. Possible Adaptations in Adaptive Designs
❖ Population (eligibility criteria)
❖ Outcomes (measure, timing, order of primary/secondary,
components of composite)
❖ Sample size
❖ Visit schedule
- Shorten/lengthen follow-up time
- Change number or timing of visits
❖ Treatments
Dose/duration
Concomitant meds
❖ Hypotheses tested
- Non-inferiority to superiority or vice versa

34. Adaptive design(cont’d)
 Advantage:
 More efficient data collection
 Shorter study duration
 Less number of patients
 Increasing a probability of success in achieving the study
objectives
 Disadvantages:
1. It does not protect against bias introduced by changes in the
types of patients entering into trial overtime.
2. Misinterpretation of the interim analysis

35. Study designs on Hypothesis testing

36. Basic Concept concerning Testing of
Hypothesis
 H0: : states that differences are due to chance or no difference
between experimental and control treatments .
 H0: T=C or H0: T-C=0
 HA : states that there are differences between treatments, suggest
that results are due to factors other than chance.
 HA: TC HA: T-C0
Test the null hypothesis against the alternative.
Rejecting H0 allows us to conclude the new treatment is
better than the standard.

37. Type I Error
A Type I error is rejecting H0 when it is true.
Stat. test detected a group difference when there is no real
difference between groups
❑ Reality: No relationship
❑ Decision: Reject the null
❑ Analogy: Find an innocent man
guilty of a crime
 Type I error - Concluding that the
new drug is better than the
standard (HA) when in fact it is no
better (H0).

38. Type II Error
A Type II error is accepting H0 when it is false=FN.
❑ Reality: Relationship
❑ Decision: Accept the null
❑ Analogy: Find a guilty man innocent
of a crime
❑ Type II error - Failing to conclude
that the new drug is better (HA) when
in fact it is. Effective drug is deemed
to be no better.
Stat. test failed to detect a difference when there is a real
difference between groups

39. Study designs on Hypothesis testing
Superiority trial
Equivalence trial
Non-inferiority trial

40. 1. Superiority Trials
 The experimental treatment is better than the control treatment.
 Hypothesis: New intervention is better.
 Prove that E is better than C
 A trial with the primary objective of showing that the test drug
is superior to a comparative agent (active or placebo control)
Null hypothesis – no difference between New drug & standard ttt
( )
0
0
:
0 =
−

− Std
New
Std
New
H 



Alternative hypothesis - New drug is better than standard ttt
0
: 
− Std
New
A
H 

 Superiority trial: most classical design

41. the test
drug
comparative
agent
is superior
to
Superiority Trials
Superiority trial: most classical design

42.  The experimental treatment is not inferior to the control
treatment.
 Show that E is not (much) worse than C
 “A trial with the primary objective of showing that the
test drug is not clinically inferior to a comparative agent
(standard therapy or placebo control).”
2. Non-Inferiority Trials

43. the test
drug
a comparative
agent
is not clinically inferior
to
2. Non-Inferiority Trials

44. Potential reasons to do non-inferiority
study
New intervention has some other advantage that
would recommend it if efficacy similar (non-inferior)
to current standard therapy
◼ Cost
◼ Toxicity
◼ Invasiveness
• e.g., cheaper, safer (less toxic), easier to use (pill vs.
enema), more readily available (oral rehydration vs.
IV fluids); commercial

46. 3. Equivalence Trial
❑ The experimental treatment and the control treatment are similar.
❑ Show that E is equivalent to C
❑ A trial with the primary objective of showing that the test drug can
reach the same therapeutic effect as that of a standard therapy (or
an active agent) or they are therapeutically equivalent
❑ To confirm the absence of meaningful difference between the ttts
❑ To determine whether a (new) intervention is neither worse nor
better than another (established) intervention

47. 3. Equivalence Trial
absence of meaningful
difference between the ttts
the test
drug
a standard
therapy
the same
therapeutic effect

48. Equivalence studies have important uses
in clinical trials:
 They are used for comparing similar treatment compounds.
They are used for comparing the efficacy of the same
treatment compound in differing formulations or in different
cohorts of patients.
.

49. Issue with traditional hypothesis For an
equivalence design
✓ H0 : there is a difference between the two treatments.
✓ HA: there's no difference between the two treatments.
H0 assumes the difference, if H0 is rejected, we accept the
alternative hypothesis Ha and claim equivalence.
✓ Type I error is to show no difference when there is one.
✓ And the Type II error is to show a difference when there isn't
one

52. How are noninferiority trials
different from other trials?
Superiority Equivalence Noninferiority
Objective
To determine if one
treatment is superior
to another
To determine if an
experimental treatment
and an active reference
treatment are similar in
effect within a prestated
range
To determine that an
experimental treatment is
not clinically worse than
an active reference
intervention by more than
a small, preset margin
Null
Hypothesis
There is no
difference between
the two
interventions.
One treatment is superior
to the other
The experimental
treatment is equivalent to
the comparator within the
prestated margin
Alternate
Hypothesis
One treatment is
superior to the other
One treatment is superior
to the other
The experimental
treatment is no worse than
the comparator with
respect to the prestated
margin

53. Study designs on small population

54. Study designs for small populations
Defined as <50 possible patients recruited in 5years
with multicentre∕ multinational recruitment.
1. Rare diseases
2. Unique study populations (e.g. Astronauts)
3. Individually tailored therapies
4. Environments that are isolated
5. Emergency situations
6. Public health urgency
7. Restricted resources coupled with an important
need

55. A- Sequential Design
 Here the participants are sequentially enrolled in the study and
are assigned a treatment (usually at random).
 The efficiency, safety and efficacy of the experiment is
improved by changing the rules as the study progresses.
 Various for sequential designs are:
1. Up & down methods (Most Common)
2. Bayesian methods

56. Sequential Design...
Abandon the Study
If low dose is ineffective and
High dose is effective
If low dose is effective and
High dose has ADRs
If both low dose and
High dose are ineffective
Low dose High dose
Up & down method

57. B- Rolling design
• Design that can roll on continually by introducing new
treatment options from the evidence accumulated, dropping
those of either proven efficacy or if found not to be effective.
• Make use of intermediate endpoints (in contrast to the
traditionally used endpoints that require longer patient
follow-up).

58. Intervention A Intervention B Control Group
10/25/2021
Discontinue
Intervention B
Subsequent recruitment
favours beneficial
profiles
Randomized
recruitment to
control arm
continues
Drug A Drug B Std. drug

59. Period Effects
 Differences between treatment groups over
passages of time.
 Period effects occur because patients are
observed at least twice and their condition may
change between the first and second observation.
 Period effects increase within-person variability,
which reduces the power of the design and
decreases the advantage of a cross-over design
study

60. Period Effect Variables
 Depressed patients may be less depressed during the 2nd
treatment period simply because depression tends to improve
over time.
 Learned effects
 Development of tolerance or resistance
 Changes in the disease state
 Psychological variables: pain syndromes, exacerbation of
exzema, multiple sclerosis acute flare ups, etc.

61. Sequence Effects
 Changes in the effectiveness of the drug treatment
produced by the order in which the drugs were
administered.
 Appear statistically as interactions. Interactions
affect the interpretation of the results because the
magnitude of the treatment differences is not
consistent.

62. Carry-over effect
 When the effects of the drug given during the
first period persists into the second period.
 Carryover effects only affect the treatment
response in the 2nd time period.
 Can be eliminated by using a washout period
between treatments. This allows the patient to
return to baseline levels before the 2nd treatment
is started.

63. Carry-over effects
 The ability to remove the influence of carryover effects
through the use of a washout period differentiates carry-
over and period effects.
 Period effects represent long term or permanent changes in
the subject that are unlikely to be eliminated with a
washout period.
 Carry-over effects represent temporary changes secondary
to continued presence of the drug in the system, such as for
a drug with a long half-life persisting into the 2nd
treatment period, but the effects of the drug with a short
half-life not persisting

64. Which study design best describes
this scenario?
 In light of the growing obesity epidemic,
researchers seek to determine whether fruit juice is
associated with weight gain in children.
Specifically, the investigators want to evaluate
whether fruit juice has similar effects on weight
compared to water. Children in the same household
are randomized to the same intervention for fear
that the drinks can be easily mixed up in a
household with more than one child participating in
the study.

65. Dr / Eman Mortada

66. What did you learn today?
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67. Dr. Eman Mortada