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Randomization Process of assigning clinical trial participants to
treatment groups
Gives each participant a known (usually equal) chance of being assigned to any of the groups
Successful randomization requires that group assignment cannot be predicted in advance
Why Randomize? If, at end of a clinical trial, difference in outcomes
occurs between two treatment groups (say, intervention and control) possible explanations for this difference would be:
Intervention exhibits a real effect
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
All Rx groups should have
Equal no. of patients:◦ Young/ Old (different physiology)
◦ Male/ Female (different physiology)
◦ Mild/ Severe/ Complicated (other diseases)
Only Randomization can achieve this !Only Randomization can achieve this !
All Rx groups should have
Equal no. of patients:
◦ fasting/ taking excess coffee etc
◦ with relevant factors
Only Randomization can achieve this !Only Randomization can achieve this !
All treatment groups should have ◦ Statistical requirements met properly
Only Randomization can achieve this !Only Randomization can achieve this !
Randomization
Definition:Randomization is a process based on Chance allocation of subjects to different treatments planned in a clinical trial
Randomization
Treatments
A-Drug A
B-Drug B
C-Drug C
D-Placebo P
Treatments
A-Drug A
B-Drug B
C-Drug C
D-Placebo P
Patients1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,2122,23,24,25,26,27,28,29,30
Patients1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,2122,23,24,25,26,27,28,29,30
Randomization decides which patient will get what treatment...
Purpose Randomization produces patient groups which
are:
Balanced with respect to factors which can influence outcome of a trial
Allows to make a strong Causal connection between treatment and their effects
Inappropriate 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
Forms of Randomization
Simple Randomization
Permuted Block Randomization
Stratified Block Randomization
Dynamic (adaptive) random allocation
Simple Randomization
Coin Tossing for each trial participant (not usually performed, as issues of concealment,
validation and reproducibility arise )
Random Numbers Tables from statistical textbooks
Computer generated sequence of random nos.
Random number tables Choose randomly a row and block
Suppose the sequence is 71146
Give even numbers treatment A and odd numbers treatment B
Treatment schedule will be BBBAA
Random number table may not give equal numbers in the 2 treatment arms
Computer Generated Random nos.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……
Three Groups: (criterion:{1,2,3}~A, {4,5,6}~B, {7,8,9}~C; ignore 0’s) BCAACABBABAABA……
Two Groups: different randomization ratios(eg.,2:3):(criterion:{0,1,2,3}~A, {4,5,6,7,8,9}~B) BBAABABBABAABAA……..
Computer Generated Random nos.. Each digit (1,2,3 etc) has the probability of occurring 1/10,
Each pair(11,15,26) has the probability of occurring 1/100,
Each triplicate (221,125,458) has the probability of occurring 1/1000
We can begin at any place in the Random table and still the probabilities will remain the same
Permuted Block Randomization Used for small studies to maintain good treatment balance
among groups
In a two group design, Blocks having equal numbers of As and Bs (A = intervention and B = control, for example) are used, with the order of treatments within the block being randomly permuted
Block Randomization
With a block size of 4 for two groups(A,B), there are 6 possible permutations and they can be coded as:
1=AABB, 2=ABAB, 3=ABBA, 4=BAAB, 5=BABA, 6=BBAA
Each number in the random number sequence in turn selects the next block, determining the next four participant allocations (ignoring numbers 0,7,8 and 9)
e.g. Sequence 67126814…. will produce BBAA AABB ABAB BBAA AABB BAAB
Blocked Randomization
Blocks are allotted to different centers
All treatments are present in every block
Equal treatments are present in every group
No. of patients in different treatment groups remains same
Blocked Randomization
DisadvantagesDisadvantages
Block 1 Block 3 ABBA BABA Block 1 Block 3 ABBA BABA
• Last treatment may reveal itself due to a particular drug effect like colored urine or loose stools etc.
• Investigator can be made blind to the block length/ blocks of different lengths can be made
Stratified Block Randomization
◦Stratification simply means having separate block randomisation schemes for each combination of characteristics (‘stratum’)
Typical examples of such characters are◦ severity of disease condition◦ age group◦ sex of patient
Stratified Randomization E.g. In a trial of Chemotherapy for abdominal cancer, stratification factors may be as shown in below
table
Set of permuted blocks is generated for Female & 40-60 yrs, another set for Female & > 60 yrs, and so on..
Stratification Blocks
Sex Age Block 1 Block 2 Block 3
F 40-60 ABAB BBAA AABB
F > 60 BAAB ABBA BBAA
M 40-60 BAAB ABBA BBAA
M > 60 AABB BAAB BABA
Stratified Randomization Advantages
◦Stratification can add to the credibility of a trial, as it ensures treatment balance on these known prognostic factors, allowing easy interpretation of outcomes without adjustment
◦Increases the power to detect differences
Disadvantages◦Delays randomization reaching different centers
◦Misclassification of patients to different strata may alter the result at end of study
Dynamic Randomization
When factors requiring randomization are too many, some groups may have less patients in the end
Hence minimization is done to bring back the balance and increase efficiency of the study
Dynamic Randomization In Simple/ Block randomization allocation sequences
are set up, before start of trial
In contrast, dynamic randomization allocates patients to treatment group by checking allocation of similar patients already randomized, and allocating next treatment group "live" to balance treatment groups across all stratification variables
Example of randomization using the minimization method in a trial of chemotherapy for breast cancer, with stratification factors of clinic site, estrogen receptor status (ER+ or ER–) and menopausal status
Characteristic Treatment A Treatment B
Site 1 7 8
Site 2 10 9
ER+ 5 6
ER– 12 11
Premenopausal 8 9
Postmenopausal 9 8
Total 17 17
Dynamic Randomization The next participant (no. 35) is Site 2, ER+, postmenopausal
Subtotals for treatment allocation to this profile of characteristics are 10 + 5 + 9 = 24 for Treatment A and 9 + 6 + 8 = 23 for Treatment B (note subjects are counted more than once)
Participant no. 35 would therefore be allocated to Treatment B
When the tallies on A and B are equal within a profile, the next participant is randomly allocated.
Dynamic Randomization
Advantages: Provides good balance of prognostic factors & increases
efficiency of trial
Disadvantages: Future treatments are decided by earlier treatments, so
not ideal randomization
Communication by Internet/ Fax/ telephone becomes necessary as next patient may be at a different site
Response Adaptive Randomization
As per individual and group ethics, each patient should receive best possible treatment
Response adaptive randomization is done
E.g. RPW, urn model etc.
RPW-Randomized Play the Winner Design
Treatment balls takenTreatment balls taken
A B
One ball is randomly selected
One ball is randomly selected
Patient takesTreatment
Patient takesTreatment
At the start, 2 treatments representing 2 coloured balls are taken in a bag with closed mouth
B B
RPW-Randomized Play the Winner Design At the end, if treatment was successful that respective coloured ball is added to the bag
Every incomingpatient has a better
chance ofselecting bettertreatment ball
Every incomingpatient has a better
chance ofselecting bettertreatment ball
Despite ethical appeal, RPW designs arenot used commonly in clinical trials
Despite ethical appeal, RPW designs arenot used commonly in clinical trials
Successful treatment balls are added to thebag
DebateDebate
Many argue that in absence of definitive evidence in favour of one treatment over another, it is neither efficient nor ethically appropriate to assign patients in a different ratio
With use of early stopping rules, benefits from a response-adaptive design relative to equal allocation are greatly lessened; hence ethical need for adaptation is obviated
Conclusion
RAR cannot substitute for true randomizationin confirmatory trials
It is important to keep allocation probabilities even for statistical sensitivity to be maximum
(Department of Biostatistics and Medical Informatics, Chicago)
35
What is Bias?In lay terms “prejudice or leaning of one’s
opinion favoring one side”
In terms of CR, “systematic error that enters clinical trial and distorts the data obtained”
Bias occurs as a consequence of :◦trial design used, ◦tests used, ◦people involved
Goal of a clinical trial is to attempt to eliminate most, if not all biases
Bias
Bias is said to have occurred if results observed reflect other factors in addition to/ instead of effect of treatment given:
Some potential sources of bias:Patient biasCare Provider biasLaboratory biasAnalysis and Interpretation bias
Patient Bias Patient's knowledge that patient is receiving a "new" treatment
may substantially affect patient's subjective assessment
Patient's knowledge of treatment may affect outcome of study
Care Provider Bias
Care provider's knowledge of which Rx a patient is receiving may affect how provider
– deals with patient – treats patient
These differences may give patient information (even if incorrect) about treatment, which then may affect
outcome of study
Laboratory Bias Knowledge of which treatment patient received may
affect way in which test is run or interpreted
Subjectively graded lab results (pathology slides, photographs, ECG, etc.) may be affected
Analysis & Interpretation bias
Knowledge of treatment group may affect results of data analysis by
– Seeking explanation of an "anomalous” finding when one is found contrary to study hypothesis
– Accepting a "positive" finding without fully exploring data
Analysis and Interpretation bias Knowledge of treatment group may affect decisions made
by external monitors of a study by
– Terminating a study for adverse events because they fit expectations of the monitors
– Terminating a study for superiority of treatment because it fits expectations of the monitors
How to minimize Bias?
Allocation Concealment: to counter selection bias before randomization
Blinding: Masking of treatment after randomization
Allocation Concealment Procedure for protecting the randomization process so
that treatment to be allocated is not known before patient is entered into study
Concentrates on preventing selection bias
Allocation Concealment
Safeguards assignment sequence before and until allocation
Can always be successfully implemented in randomized clinical trials
Allocation Concealment
Methods:
Sequentially numbered, opaque, sealed envelopes
Pharmacy-controlled allocations
Coded identical containers or kits
Central randomization systems (telephone or web based)
Blinding
Blinding relates to the masking of treatments after randomization — from patient, investigator or outcome assessor
Blinding (also called masking or concealment of treatment)
Intended to avoid bias caused by subjective judgment in reporting, evaluation, data processing, and analysis due to knowledge of treatment
Blinding Blinding concentrates on preventing study personnel &
participants from determining group to which participants have been assigned
Safeguards the sequence after allocation
Cannot always be implemented
Hierarchy of Blinding
Open label: no blinding
Single blind: patient blinded to treatment
Double blind: patient and assessors (who often are also the health care providers and data collectors) blinded to treatment
Complete blind: everyone involved in the study blinded to treatment
Open Label Studies • Pilot studies • Dose ranging studies
However, even these applications may be biased by knowledge of treatment given & may result in
• toxicity over (or under) reported • efficacy over estimated
Even a small fraction of patients assigned at random to placebo will reduce these potential problems
Single Blind Studies
Blind patient to treatment given
Health care providers and assessors usually know actual treatment given
Justification for single blind is usually that
double-blind is "impractical" because of need to adjust medication, medication affecting laboratory values, potential side effects, etc.
Double Blind Studies Subjects & Investigators are kept from knowing
who is assigned to which treatment
Minimizes both potential patient bias & potential assessor bias
Should be used whenever possible, which is whenever it is ethically permissible to blind a patient
Double Blinding: Techniques Coded treatments
Placebo for each possible treatment - tablets identical in physical appearance - tablets with similar taste & smell - Carrier for IV infusions in active medication used as placebo
Other treatments "shammed" as far as possible: – minimal power ultrasound therapy when testing effect of physical therapy in back pain – breathing exercises when assessing effect of conditioning exercises
Double Blinding: always feasible??
Situations when double blinding might not be possible It might not be ethically permissible to blind a patient. As an
example, it is unlikely that sham surgery would be considered ethical in a study
It might not be possible to blind a patient. For example, it would be hard to blind a patient to the therapy given in an exercise study
It may not be possible to blind a patient while comparing utility of different invasive procedures
Double Blind Studies: stumbling blocks
Side effects (observable by patient) are much harder to blind
Side effects are one of the major ways in which blinding is broken
Ethical problems in using placebos to induce side effects in patients
Side effects of all potential therapies should be combined into a single list, so that knowledge of side effects would not indicate therapy (at least to patient)
Complete/ Triple Blinding
Patient, Investigator and those who analyze study outcomes or those who monitor the study safety
Probably the best approach which can be used, but requires two groups for data processing, one group to encode data and one group to perform analysis
Normally only available in major drug company studies, and not routinely used even then
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)