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

2. 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

3. 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

4. All Rx groups should have Equal no. of patients: ◦ Young/ Old (different physiology) ◦ Male/ Female (different physiology) ◦ Mild/ Severe/ Complicated (otherdiseases) Only Randomization can achieve this !

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

6. All treatment groups should have ◦ Statistical requirements met properly Only Randomization can achieve this !

7. Randomization Definition: Randomization is a process based on Chance allocation of subjects to different treatments planned in a clinical trial

8. 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 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 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...

9. Purpose Randomization produces patient groups which are: Balanced with respect to factors which caninfluence outcome of a trial Allows to make a strong Causal connectionbetween treatment and their effects

10. 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

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

12. 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.

14. 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

15. Computer Generated Random Number Table Computer Generated Random Number Table

16. 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……..

17. . 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

18. 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

19. 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

20. 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

21. Blocked Randomization Disadvantages 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

22. 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

23. 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 SexAgeBlock 1Block 2Block 3 F40-60ABABBBAAAABB F> 60BAABABBABBAA M40-60BAABABBABBAA M> 60AABBBAABBABA

24. 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

25. 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

26. 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

27. 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 CharacteristicTreatment A Treatment B Site 178 Site 2109 ER+56 ER–1211 Premenopausal89 Postmenopausal98 Total17

28. 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.

29. 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

30. 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.

31. RPW-Randomized Play the Winner Design Treatment balls taken Treatment balls taken A B One ball is randomly selected One ball is randomly selected Patient takes Treatment Patient takes Treatment At the start, 2 treatments representing 2 coloured balls are taken in a bag with closed mouth B B

32. RPW-Randomized Play the Winner Design At the end, if treatment was successful that respective coloured ball is added to the bag Every incoming patient has a better chance of selecting better treatment ball Every incoming patient has a better chance of selecting better treatment ball Despite ethical appeal, RPW designs are not used commonly in clinical trials Despite ethical appeal, RPW designs are not used commonly in clinical trials Successful treatment balls are added to the bag

33. Debate Debate 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

34. Conclusion 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)

35. 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

36. 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

37. Patient Bias P atient's knowledge that patient is receiving a "new" treatment may substantially affect patient's subjective assessment P atient's knowledge of treatment may affect outcome of study

38. 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

39. 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

40. 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

41. 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

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

43. 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

44. Allocation Concealment Safeguards assignment sequence before and until allocation Can always be successfully implemented in randomized clinical trials

45. Allocation Concealment Methods: Sequentially numbered, opaque, sealed envelopes Pharmacy-controlled allocations Coded identical containers or kits Central randomization systems (telephone or web based)

46. 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

47. 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

48. 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

49. 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

50. 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.

51. 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

52. 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

53. 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

54. 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)

55. 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

56. 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)

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