2. Randomization
Randomization is the process of
assigning clinical trial participants to
treatment groups. Randomization gives
each participant a known (equal) chance
of being assigned to any of the groups.
Successful randomization requires that
group assignment cannot be predicted in
advance.
3. Need of Randomization
• If, at the end of a clinical trial, a difference in
outcomes occurs between two treatment groups
(say, intervention and control) possible explanations
for this difference would include:
• the intervention exhibits a real effect;
• the outcome difference is solely due to chance
• there is a systematic difference (or bias) between the
groups due to factors other than the intervention.
Randomization aims to obviate the third possibility.
4. Criteria for randomization
1. Unpredictability
• Each participant has the same chance of receiving any of
the interventions.
• Allocation is carried out using a chance mechanism so that
neither the participant nor the investigator will know in
advance which will be assigned.
2. Balance
• Treatment groups are of a similar size & constitution,
groups are alike in all important aspects and only differ in
the intervention each group receives
3. Simplicity
• Easy for investigator/staff to implement
5. Simple Randomization
1. Coin Tossing for each trial participant
2. Sequence of Random Numbers from
statistical textbooks
3. Computer generated sequence
6. Egs
The most common and basic method of simple randomization is flipping a
coin. For example, with two treatment groups (control versus treatment),
the side of the coin (i.e., heads - control, tails - treatment) determines the
assignment of each subject.
Shuffled deck of cards (e.g., even - control, odd - treatment)
Throwing a dice (e.g., below and equal to 3 - control, over 3 - treatment).
The computer generated sequence:
4,8,3,2,7,2,6,6,3,4,2,1,6,2,0,…….
Two Groups (criterion:even-odd):
AABABAAABAABAAA……
Disadvantages: ….
Advantages of unequal randomization include the opportunity to place more
patients in a less expensive arm, or to place more patients in an arm
where there is concern about effects and side effects, i.e. an arm in which
more data are needed.
7. Block randomization
• The block randomization method is designed to
randomize subjects into groups that result in equal
sample sizes.
• The block size is determined by the researcher and
should be a multiple of the number of groups (i.e., with
two treatment groups, block size of either 4, 6).
• Example: Two treatments of A, B and Block size of 2 x
2= 4
• Possible treatment allocations within each block are
• (1) AABB, (2) BBAA, (3) ABAB, (4) BABA, (5) ABBA, (6)
BAAB
8. Block Randomization Design With 3 Blocks of
Size 4, Treatments of A & B
• Obs Block Size
• 1 1
B
• 2 1
A
• 3 1
B
• 4 1
A
• 5 2
A
• 6 2
B
• 7 2
B
• 8 2
A
• 9 3
B
• 10 3
B
• 11 3
A
• 12 3
A
9. • Block size depends on the number of
treatments.
• The block size is not stated in the protocol so
the clinical and investigators are blind to the
block size.
10. DISADV
• If blocking is not masked in open-label trials,
the sequence becomes somewhat
predictable (e.g. 2n= 4):
• B A B ? Must be A.
• A A ? ? Must be B B
11. Stratified Randomization
• Trial may not be valid if it is not well balanced
across prognostic factors.
• SR means block within block For example, Age
Group: < 40, 41-60, >60; Sex: M, F
• For 6 patients in a block, Total number of strata =
3x2=6.
• It produce comparable groups with regard to
certain characteristics (e.g., gender, age, race,
disease severity), thus produces valid statistical
tests
12. • The block size should be relative small to
maintain balance in small strata.
• Increased number of stratification variables or
increased number of levels within strata leads
to fewer patients per stratum.
• Subjects should have baseline measurements
taken before randomization.
• Large clinical trials don’t use stratification
13. Unequal Randomization
• Most randomized trials allocate equal numbers of patients to
experimental and control groups.
• This is the most statistically efficient randomization ratio as it
maximizes statistical power for a given total sample size.
• However, this may not be the most economically efficient or
ethically/practically feasible. When two or more treatments
under evaluation have a cost difference it may be more
economically efficient to randomize fewer patients to the
expensive treatment and more to the cheaper one.
• The substantial cost savings can be achieved by adopting a
smaller randomization ratio such as a ratio of 2:1, with
only a modest loss in statistical power.
14. Ratio to be used
• When one arm of the treatment saves lives and
the other such as placebo/medical care only does
not much to save them in the oncology trials.
The subject survival time depends on which
treatment they receive. More extreme allocation
may be used in these trials to allocate fewer
patients into the placebo group.
• Generally, randomization ratio of 3:1 will lose
considerable statistical power, more extreme
than 3:1 is not very useful, which leads to much
larger sample size.
15. Inappropriate randomization methods
• Assigning patients alternately to treatment group is not
random assignment
• Assigning the first half of the population to one group is not
random assignment
• Assignments by methods based on patient characteristics
such as date of birth, order of entry into the clinic or day of
clinic attendance, are not reliably random
16. Issues leading to Blinding
• Most investigators know about treatments effectiveness and
select it for particular groups of patients. As a result,
Investigators
channel particular groups of patients to
particular treatments (channeling effect )
• There is a risk of the investigators subconsciously losing their
objectivity in their assessments of treatment effects simply
because of their knowledge about treatment.
• There is a risk of having other forms of BIAS, which can be
satisfactorily controlled by proper blinding .
17. Bias
Bias is said to have occurred if the results observed reflect other
factors in addition to the effect of the treatment.
Conscious and subconscious factors.
Occur at conduct of trail, data analysis and interpretation of data.
Some potential sources of bias:
•
•
•
•
•
Patient bias
Care Provider bias
Assessor bias
Laboratory bias
Analysis and Interpretation bias
18. 1. Patient Bias
•
The patient's knowledge that he is receiving a "new"
treatment may substantially affect the patient's subjective
assessment
• There is a subject and disease interaction
19. 2. Care Provider Bias
• The care provider's knowledge of which treatment a patient
is receiving may affect the way the provider
– deals with the patient
– treats the patient
• These differences may give the patient, information (even if
incorrect) about the treatment the patient is receiving, affect
the outcome of the study
20. 3. Assessor Bias
• The assessor's knowledge of which treatment the patient
is receiving may affect the way the assessor assesses
outcome
• such a bias would directly affect the validity of the
conclusions of the study
• if the assessment is done while the patient is still
receiving treatment, this may provide the patient with
information about the treatment being received
21. 4. Laboratory Bias
• The knowledge of which treatment the patient received may
affect the way in which the test is run or interpreted, or be
retested.
• Subjectively graded results (pathology slides, photographs,
ECG, etc.).
22. Analysis and Interpretation bias
• Knowledge of the treatment group may affect the results of the
analysis of the data by
– seeking an explanation of an "anomalous” finding when one is
found contrary to the study hypothesis
– accepting a "positive" finding without fully exploring the data
• Knowledge of the treatment group may affect the decisions made
by external monitors of a study by
– Terminating a study for adverse events because they were
expecting it.
– Terminating a study for superiority of treatment because they were
expecting it.
23. Blinding
All of these potential problems can be avoided
if everyone involved in the study is blinded to
the actual treatment the patient is receiving.
Blinding (also called masking or concealment
of treatment) is intended to avoid bias caused
by subjective judgment in reporting, evaluation,
data processing, and analysis due to knowledge
of treatment.
24. Hierarchy of Blinding
• Open label: no blinding
• Single blind: patient blinded to treatment
• Double blind: Patient and Physician (and data collectors)
blinded to treatment
• Complete blind: Everyone involved in the study blinded to
treatment
25. Open Label Studies
•
•
•
•
•
•
•
These may be useful for
• Pilot studies
• dose ranging studies
Open label studies are not recommended for comparative trials,
under certain circumstances, OLS are conducted.
e.g. in order to provide some potentially promising medications to
the patients with severely debilitating or life-threatening disease.
Safety and effectiveness of a new surgical procedure, comparision of
devices, changes in life style trials conducted in an open-label
fashion.
Eg Multiple Risk Factor Intervention Trial for CAD.
Adv:
Disadv:
Eg CA bypass VS medical treatment study
26. Single Blind Studies
• Single blind studies are usually done to blind the patient to the
treatment given. Health care providers and assessors usually
know the actual treatment given
• Justification is usually that double-blind is "impractical" because
of need to adjust medication, medication affecting laboratory
values, potential side effects, critical condition of the patient etc.
Eg Zn therapy to relieve taste disorder
• A single blind (Physician) study can also be used when it is
unacceptable ethically to give a placebo treatment to a patient,
and in such a case, the assessor (not the patient) should be the
one blinded to the treatment
27. Double Blind Studies
• When both the subjects and the investigators are kept from
knowing who is assigned to which treatment, the experiment is
called double blind.
• Serve as a standard by which all studies are judged, since it
minimizes both potential patient biases and potential assessor
biases
• Should be used whenever possible.
28. Double Blinding:Techniques
•
•
•
•
Coded treatment groups
Placebo for each possible treatment.
Tablets identical in physical appearance.
Tablets with similar taste and smell : use of Quassin for taste
masking.
• IV infusions would normally be the same carrier as used for
active medications.
• Other treatments "shammed" as far as possible:
eg. Minimal power ultrasound therapy when testing effect of
physical therapy in back pain.
Eg Vit C trial : double blind trial was broken
29. Disadvantages: Double Blinding is
not always feasible??
When intervention is surgery- It is unlikely that
sham surgery would be considered ethical in a
study.
• It would be hard to blind a patient to the therapy
given in an exercise study.
• it might not be possible to blind a patient while
comparing utility of different invasive procedures
30. Double Blind Studies: Difficulties
Side effects:
• Side effects (observable by patient) are much harder to blind
• in general, there are significant ethical problems using placebos to
induce side effects in patients.
• a way to avoid it is that the side effects of all the potential
therapies be combined into a single list, so that knowledge of side
effects would not indicate therapy (at least to patient).
Efficacy:
• A truly effective treatment can be recognized by its efficacy in
patients.
• Some new treatments ARE VERY EFFECTIVE and when this
happens, it is becomes clear which treatment a patient is
receiving, at least for the health care providers involved in the trial.
31. Complete Blinding
• Patient and the investigator, all members of the
clinical project team of the sponsor including CRA,
statistician, programmer, and data coordinator are
blinded.
• May require two groups for data processing, one group
to encode the data/analysis and one group to perform
the analysis
• Normally only available in major drug company studies,
and not routinely used.
32. Complete Blinding:Techniques
• Analysis uses coded treatment groups
• Analysis uses coded side effects (e.g., side
effects coded using non-standard scheme, with
only numeric codes available at time of analysis)
• Analysis uses coded laboratory tests (e.g., name
of test coded numerically at time of analysis,
using non-standard code)
33. Coding of drugs
•
•
•
•
Assigning a random number.
As many as different code.
Participants: unique code.
If only one code is used: disclose for 1 will
disclose for all.
• Many side effect in many people: decode
• Efficient coding: sd not confuse the prescriber
and stocking of drugs.
34. Unblinding of study
• The carton must contain slip of drug inside it.
• Should not be disclosed to patients while
storage.
• Official unblinding may be necessary during
emergency.
35. Assessment of blindness
• Ask the participant and cross asking the
clinical staff.
• 50% of answers exceed.
37. • Diffficult task: sufficient number of patients in
reasonable amount of time.
• Eg 39 ONCOLOGY TRIAL: Only 2 trial recruited
successfully.
• Factors: depends on type and size of trial,
length of time available, the setting, single
centric/ multicentric trial etc.
38. • National Institute of Neurological Disorders and Stroke’s (n.d.)
notice recruiting participants for a clinical trial titled Study of
• Brain Activity During Speech Production and Speech
Perception.
• The inclusion criteria specified for the experimental group
were (a) right-handed children and adolescents, (b) native
speakers of American English, and (c) stuttering or
phonological processing disorders. The comparison (control)
group consisted of normally developing right-handed children
and adolescents who were native speakers of American
English. Exclusion criteria were (a) language use in the home
other than American English, (b) speech reception thresholds
greater than 25 dB, and (c) contraindications to magnetic
resonance scanning. In a similar fashion, systematic reviewers
specify inclusion and exclusion criteria for synthesizing
studies, but the criteria are usually much broader.
39. Inclusion and exclusion criteria
• Inclusion and exclusion criteria are the
conditions that must be met in order to
participate in a clinical trial, or the standards
used to determine whether a person may be
allowed to participate in a clinical trial. The
most important criteria used to determine
appropriateness for clinical trial participation
include age, sex, the type and stage of
a disease, treatment history, and other
medical conditions.