Randomization & Blinding

Randomization & Blinding Dr. Aparna Walanj Clinical Research Head Ethika Clinical Research Center

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 Randomization

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 Why Randomize?

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 !

All Rx groups should have Equal no. of patients: • fasting/ taking excess coffee etc • with relevant factors Only Randomization can achieve this !

All treatment groups should have • Statistical requirements met properly 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 Patients 1,2,3,4,5,6,7,8,9,10,11,12, 13,14,15,16,17,18,19,20,21 22,23,24,25,26,27,28,29,30 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

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 Inappropriate Methods

Simple Randomization • Permuted Block Randomization • Stratified Block Randomization • Dynamic (adaptive) random allocation Forms of 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. Simple Randomization

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 Random number tables

Computer Generated Random Number Table

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 Computer Generated Random nos.

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 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 Block 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

Disadvantages 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 Blocked 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 Block 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.. 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 Stratified 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 Dynamic Randomization

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 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

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 Dynamic 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. Response Adaptive Randomization

One ball is randomly selected Treatment balls taken Patient takes Treatment A B 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 Successful treatment balls are added to the bag Every incoming patient has a better chance of selecting better treatment ball RPW-Randomized Play the Winner Design Despite ethical appeal, RPW designs are not used commonly in clinical trials

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 Debate

RAR cannot substitute for true randomization in confirmatory trials It is important to keep allocation probabilities even for statistical sensitivity to be maximum (Department of Biostatistics and Medical Informatics, Chicago) Conclusion

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 What is 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 bias • Care Provider bias • Laboratory bias • Analysis and Interpretation bias 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 Patient 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 Care Provider 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 Laboratory 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& Interpretationbias

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 AnalysisandInterpretationbias

Allocation Concealment: to counter selection bias before randomization • Blinding: Masking of treatment after randomization How to minimize Bias?

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) Allocation Concealment

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 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 Hierarchyof Blinding

•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 Open Label 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. Single Blind Studies

Randomization & Blinding