Clinical trials its types and designs

Clinical Trials:
Its types and designs
From Devesh Aggarwal
M.Pharmacy
Department of Pharmacology
ISF College of Pharmacy.
Moga,Punjab

*
1. Introduction
2. Brief history
3. Types of clinical trials
4. Design of clinical trials
a) Observational designs
i. Cohort design
ii. Cross sectional design
iii. Case control study design
b) Experimental designs
i. RCT
ii. NON RCT

*
*Definition given by WHO
*A clinical trial is any research study that prospectively
assigns human participants or groups of humans to one or
more health-related interventions to evaluate the effects on
health outcomes.
*Interventions include but are not restricted to drugs, cells and
other biological products, surgical procedures, radiological
procedures, devices, behavioural treatments, process-of-care
changes, preventive care, etc.

*
*The concepts behind clinical trials are ancient.
*The first proper clinical trial was conducted by the
physician James Lind in 1747.
*he included diet with acidic food at crew members of ship
affected with scurvy. Crew divided in 6 groups including
control group.

*Dates
*In 1863, physician Austin Flint gave patients a fake
remedy, for rheumatism later known as placebo effect.
*1927 – The Bureau of Chemistry was renamed the Food,
Drug, and Insecticide Administration (later known as the
FDA ). This government division oversaw clinical
research and eventually had to approve all drugs sold in
the U.S.
*1964 – After World War II, the research community saw
a need for ethical codes. The Declaration of Helsinki
created by the World Medical Association offered
guidelines to physicians who used human subjects in
their research.

Phase I Phase II Phase III Phase IV
Objectives Determine the
metabolic and
pharmacological
actions and the
maximally tolerated
dose
Evaluate
effectiveness,
determine the short-
term side effects and
identify common risks
for a specific
population and
disease
Obtain additional
information about
the effectiveness
on clinical
outcomes and
evaluate the overall
risk-benefit ratio in
a demographically
diverse sample
Monitor ongoing
safety in large
populations and
identify additional
uses of the agent
that might be
approved by the
FDA
Factors to
be
identified:
• Bioavailability
• Bioequivalence
• Dose
proportionality
• Metabolism
• Pharmacodynamics
• Pharmacokinetics
• Bioavailability
• Drug-disease
interactions
• Drug-drug
interactions
• Efficacy at various
doses
• Pharmacodynamics'
• Pharmacokinetics
• Patient safety
• Drug-disease
interactions
• Drug-drug
interactions
• Dosage intervals
• Risk-benefit
information
• Efficacy and
safety for
subgroups
• Epidemiological
data
• Efficacy and
safety within
large, diverse
populations
• Pharmacoecono
mics
Data focus: • Vital signs
• Plasma and serum
levels
• Adverse events
• Dose response and
tolerance
• Adverse events
• Efficacy
• Laboratory data
• Efficacy
• Adverse events
• Efficacy
• Pharmacoecono
mics
• Epidemiology
• Adverse events

Phase I Phase II Phase III Phase IV
Design
features:
• Single, ascending
dose tiers
• Unblinded
• uncontrolled
• Placebo controlled
comparisons
• active controlled
comparisons
• well-defined entry
criteria
• Randomized
• Controlled
• 2-3 treatment arms
• broader eligibility
criteria
• Uncontrolled
• observational
Duration Up to 1 month Several months Several years Ongoing (following
FDA approval)
Population: Healthy volunteers or
individuals with the
target disease (such as
cancer or HIV)
Individuals with target
disease
Individuals with
target disease
Individuals with
target disease, as
well as new age
groups, genders, etc.
Sample size: 20 to 80 200 to 300 Hundreds to
thousands
Thousands
Example: • Study of a single dose
of drug X in normal
subjects
• Double-blind study
evaluating safety
and efficacy of drug
X vs. Placebo in
patients with
hypertension
• Study of drug X vs.
Standard treatment
in hypertension
study
• Study of
economic benefit
of newly-
approved drug X
vs. Standard
treatment for
hypertension

*
Observational
(non experimental)
cohort
Case
control
cross-
sectional
Experimental
RCT
Non RCT

*
*A population at risk for the disease events is followed over time for the
occurrence of disease and events.
*This study used to estimate how often disease or life events happen in a
certain population.
*These are the best method for determining the incidence and natural
history of a condition.
Population
(Sample)
Exposed
(smoking)
Disease
(Lung cancer)
No disease
Unexposed
Disease
(Lung cancer)
No disease

*
• A group of people is chosen who do not
have the outcome of interest (for
example, myocardial infarction).
• The investigator then measures a variety
of Variables that might be relevant to the
Development of the condition.
Prospective
• These use data already collected for other
purposes. The methodology is the same
but the study is performed.
• Outcome is already developed.
Retrospective

*
*Prospective
*Studies carried out from present time to future
*Can be tailored to collect specific exposure rate
*But long wait for events to occur
*Expensive
*Prone to high dropout rates
* Retrospective
* Look at medical events from past to present
* Information is available immediately
* Difficulty in tracing subjects and doubt on quality of recorded
information

*
*Is a type of observational study that are primarily used to determine
prevalence.
*Prevalence equals the number of cases in a population at a given
point in time.
*All the measurements on each person are made at one point in time.
Cohort Cross sectional
Study group Population at risk Entire population
Common measures Risks and rates Prevalence

*
*The prevalence of a health outcome is simply the proportion of
individuals with the health outcome in a population.
Example
*P1= a/a+b= 50/250 = 20.0% prevalence of CHD among people who are
not active.
*P0= c/c+d = 50/750 = 6.7% prevalence of CHD among people who are
active.
Prevalence
Cases
Total
Population
Present CHD Absent CHD Total
Not active 50a 200b 250
Active 50c 700d 750
Total 100 900 1000

*
*An observational study that compares patients who have a disease or
outcome of interest (cases) with patients who do not have the disease or
outcome (controls), and looks back retrospectively to compare how
frequently the exposure to a risk factor is present in each group
Study base
Cases
50
exposed
40
unexposed
10
Controls
50
exposed
15
unexposed
35
Odds ratio
(no of exposed cases)/(no of unexposed cases)
(no of exposed control)/(no of unexposed controls)

*
*Case control studies are usually retrospective.
*In this study the only outcome is presence or absence of the disease
or whatever criteria was chosen to select the cases.
*Aim to identify predictors of an outcome
*Permit assessment of the influence of predictors on outcome via
calculation of an odds ratio
*Can only look at one outcome
*Bias is an major problem
Odds Ratio : 40/10x35/15 = 4 x 2.33= 9.33odds of exposure for cases
is 9.33 times that of controls
Exposure is associated with 9x greater chance of disease.

• Efficient- saves time and energy
• Used for rare diseases, small sample sizes
• Can generate hypothesis for future study
• Susceptible to bias-recall, reporting
• Prone to methodological errors
• Selection of an appropriate comparison group may be difficult
*
*

*
*Interventional study (clinical trial) A type of clinical study in
which participants are assigned to groups that receive one or
more intervention/treatment (or no intervention) so that researchers
can evaluate the effects of the interventions on health-related
outcomes.
Interventional study
True experimental designs
Quasi-experimental designs

*
Also called nonrandomized interventional study design
*In non randomly assigned control group studies, at least two separate
groups are evaluated—
*One of which receives the intervention of interest and another that
serves as a control or comparison group.
That means it is used to estimate the causal impact of an intervention
on its target population without random assignment.

*When the act of random allocation may reduce the effectiveness of
the intervention (occurs when the effectiveness of the intervention
depends on the participant’s active participation which is
influenced by their beliefs and preferences)
*When it would be unethical to do random allocation
*When it is impractical to do random allocation (e.g. Cost or
convenience factors)
*When there are legal or political obstacles to random allocation
* When researchers can’t manipulate the independent variables
* When researchers can’t randomly assign participants to groups.
* Quasi independent variable is a naturally occurring variable and
can’t be manipulated or eliminated.
*

*
• One group pre-test post-test design
• Non equivalent control group design
• Interrupted time series design

*
* : Sample of violent adolescent women
* : anger management class
* : aggressive behaviour 1 year pre/post treatment
If aggressive behaviour is lower at T2 than T1, can we conclude this
decrease is caused by the treatment?
Time 1 Intervention Time 2
01 X 02
Measures
Treatment
Example

*
Target
population
selection
Pre test
Pre test
Intervention X
Activity as
usual
Post test
Post test

*
*Time series analysis is simply a set of measurements of a variable taken
at various points in Time.
*Essentially, the investigator measures the outcome of interest several
times before initiating the experiment to establish a baseline value and
trend in the data. After the intervention, the investigator will again
measure the outcome several times to establish the impact of the
intervention.
: Mood of students during semester
T1 T2 T3 T4 T5 T6 T7 T8 T9
A B C D X E F G H
Example

*
* An epidemiological experiment in which subjects in a population
are randomly allocated into groups, usually called study and control
groups, to receive or not receive an experimental preventive or
therapeutic
*Patients are randomly assigned to the study all groups that help in
avoiding bias in patient
Study
population
Intervention
group
Control group
Outcome
No
outcome
Outcome
No
outcome

*
*Comparative
*One treatment is directly compared to another to establish
superiority.
*Minimises bias
*Randomisation minimises allocation bias and selection bias
*Blinding minimises performance bias
*Minimises confounding factors
*Randomisation makes groups comparable according both known
and unknown factors
*Statistical reliability
*Statistical test of significance is readily interpretable when the
study is randomised

*
*Might demand vast samples size, which require more resources from
the investigators
*Sometimes allocation of participants may be predictable and result in
selection bias when the study groups are unmasked
*Trials are of longer duration and more expensive
*Results may not always mimic real life treatment situation (e.g.
Inclusion / exclusion criteria; highly controlled setting)
*Ethical limitations: some research cannot be ethically performed as
an RCT (classically, RCT of the effects of parachutes on the survival
of sky-divers)

Randomized Controlled Clinical Trial includes Diagnostic,
Therapeutic, Prophylactic
e.g. Evaluation of nitrates in reducing cardiovascular mortality
Randomized Controlled Field Trial: It is similar to an Randomized
Controlled Clinical Trial except that the intervention is preventive
and not therapeutic.
e.g. In this, the efficacy of a preventive intervention such as a
new vaccine is tested in one study group and the other group
receives a placebo or standard
Preventive Trial: Trial of primary preventive measures
e.g. Vaccines
Risk Factor Trial: Investigator intervenes to interrupt the usual
sequence in the development of disease for those individuals who
have risk factor for developing the disease
e.g. Primary prevention of CHD using simvastatin to lower
serum cholesterol

*
*According to level of blinding
• In open RCT, everybody involved in the
trial knows which intervention is given to
each participant
Open RCT
• Patient or evaluator is blinded as to
treatment, but not bothSingle blind
• Neither patient nor outcome evaluator
knows to which treatment patient was
assigned
Double blind
• Patient, physician, and data analyst are
blinded as to treatment identityTriple blind

*
Parallel
Cross-over
Cluster
Factorial

*
*A parallel study is a type of clinical study where treatment and
controls are allocated to different individuals.
* In this two groups of treatments, a and b, are given so that one
group receives only a while another group receives only b.
Evaluation of
outcomes
Study
population
Treatment A
Treatment B

*
*This is unlike a crossover study where at first one group receives
treatment A, followed by treatment B later, while the other group
receives vice versa
* Key element of this design is randomization
*One treatment group, and one treatment-as-usual group.
*Two active treatment groups. One of the groups might receive
an active comparator (a treatment that’s known to be effective).
⁎ One treatment group, and one treatment-as-usual group. Two active
treatment groups. One of the groups might receive an active
comparator (a treatment that’s known to be effective).
⁎ However, these studies generally require large number of patients
for the analysis
*

*
*In these types of studies each patient serves as his own control. Each
patient gets both treatments.
*Each patient receive first treatment then washout time is provided
then other treatment is provided to the same.
Study population
Treatment A
Treatment B
Washout
Period
Treatment A
Treatment B

*
*Type of randomized controlled trial wherein groups of participants
(as opposed to individual participants) are randomized and made into
clusters.
10 hospitals
Cluster randomisation
(5xcluster of 2)
Intervention 5 hospitals Control 5 hospitals
Total study population, N=1000
Intervention, N=500 Control, N=500
Fig: flow chart representing cluster design

*
*Studies involving two or more factors while randomizing are
called factorial
*Factorial design permits researchers to investigate the joint effect
of two or more factors on a dependent variable.
*Used when it is desired to study the influence of a number of
factors on the treatments compared as well as their interaction with
different treatments factors on a dependent variables l designs

*
• An N of 1 trial is a clinical trial in which a
single patient is the entire trial, a single case
study.
• In which one participant receives the
experimental and the control interventions.
1. N-of-one
trials
• A massive clinical trial assessing the value of
the therapeutic interventions by enrolling
10,000 or more subjects.
2. Mega trials

• It is a statistical analysis where the number of
participants is not specified by the investigators
beforehand.
• Instead, the investigators continue recruiting
participants until a clear benefit of one of the
interventions is observed.
3. Sequential
trials

*
*Randomization is the random allocation of treatment, which means
all participants have the same chance of being assigned to each of the
study groups. The allocation, therefore, is not determined by the
investigators, the clinicians, or other study participants
The basic benefits of randomization include
• Eliminates selection bias.
• Balances arms with respect to prognostic variables (known and
unknown).
• Forms basis for statistical tests, a basis for an assumption-free
statistical test of the equality of treatments

*
*Any systematic deviation from true results.
*It may be any error in the design, conduct or analysis of a study that
results in distortion of truth.
Experiment
Untruth
Untruth
Truth

*
Study design
treatment
Data collection
Data analysis and publication
Sources of Bias
Investigator
Participant
Statistician
Literature
Instrument

*
*Mann, C.J., 2003. Observational research methods. Research
design II: cohort, cross sectional, and case-control
studies. Emergency medicine journal, 20(1), pp.54-60.
*Grimes, D.A. and Schulz, K.F., 2002. Bias and causal
associations in observational research. The Lancet, 359(9302),
pp.248-252.
*www.who.int/topics/clinical_trials/en

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