RANDOMIZATION IN CLINICAL TRIAL,

RECRUITMENT,INCLUSION AND EXCLUSION

CRITERIA

Dr Urmila M. Aswar,

Sinhgad Institute of Pharmacy, Narhe, Pune -41

Randomization

Randomization is the process of

assigning clinical trial participants totreatment groups. Randomization giveseach participant a known (equal) chanceof being assigned to any of the groups.Successful randomization requires thatgroup assignment cannot be predicted inadvance.

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 explanationsfor 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 thegroups due to factors other than the intervention.

Randomization aims to obviate the third possibility.

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

Simple Randomization

1. Coin Tossing for each trial participant

2. Sequence of Random Numbers from statistical textbooks

3. Computer generated sequence

Egs

The most common and basic method of simple randomization is flipping acoin. For example, with two treatment groups (control versus treatment),the side of the coin (i.e., heads - control, tails - treatment) determines theassignment 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 morepatients in a less expensive arm, or to place more patients in an armwhere there is concern about effects and side effects, i.e. an arm in whichmore data are needed.

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

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

• 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.

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

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 = 3 x 2 = 6 .

• It produce comparable groups with regard to certain characteristics (e.g., gender, age, race, disease severity), thus produces valid statistical tests

• The block size should be relative small tomaintain balance in small strata.

• Increased number of stratification variables orincreased number of levels within strata leadsto fewer patients per stratum.

• Subjects should have baseline measurementstaken before randomization.

• Large clinical trials don’t use stratification

Unequal Randomization • Most randomized trials allocate equal numbers of patients to

experimental and control groups.

• This is the most statistically efficient randomization ratio as itmaximizes statistical power for a given total sample size.

• However, this may not be the most economically efficient orethically/practically feasible. When two or more treatmentsunder evaluation have a cost difference it may be moreeconomically efficient to randomize fewer patients to theexpensive 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, withonly a modest loss in statistical power.

Ratio to be used

• When one arm of the treatment saves lives andthe other such as placebo/medical care only doesnot much to save them in the oncology trials.The subject survival time depends on whichtreatment they receive. More extreme allocationmay be used in these trials to allocate fewerpatients into the placebo group.

• Generally, randomization ratio of 3:1 will loseconsiderable statistical power, more extremethan 3:1 is not very useful, which leads to muchlarger sample size.

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

Issues leading to Blinding

• Most investigators know about treatments effectiveness andselect it for particular groups of patients. As a result,Investigators channel particular groups of patients toparticular treatments (channeling effect )

• There is a risk of the investigators subconsciously losing theirobjectivity in their assessments of treatment effects simplybecause of their knowledge about treatment.

• There is a risk of having other forms of BIAS, which can besatisfactorily controlled by proper blinding .

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

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

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

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

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.).

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.

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.

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

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

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

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.

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

Disadvantages: Double Blinding is

not always feasible??When intervention is surgery- It is unlikely that

sham surgery would be considered ethical in astudy.

• It would be hard to blind a patient to the therapygiven in an exercise study.

• it might not be possible to blind a patient whilecomparing utility of different invasive procedures

Double Blind Studies: DifficultiesSide 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.

Complete Blinding

• Patient and the investigator, all members of theclinical project team of the sponsor including CRA,statistician, programmer, and data coordinator areblinded.

• 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.

Complete Blinding:Techniques

• Analysis uses coded treatment groups

• Analysis uses coded side effects (e.g., side

effects coded using non-standard scheme, withonly 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)

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.

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.

Assessment of blindness

• Ask the participant and cross asking the clinical staff.

• 50% of answers exceed.

Recruitment of Study Participants

• 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.

• 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 SpeechPerception.

• The inclusion criteria specified for the experimental groupwere (a) right-handed children and adolescents, (b) nativespeakers of American English, and (c) stuttering orphonological processing disorders. The comparison (control)group consisted of normally developing right-handed childrenand adolescents who were native speakers of AmericanEnglish. Exclusion criteria were (a) language use in the homeother than American English, (b) speech reception thresholdsgreater than 25 dB, and (c) contraindications to magneticresonance scanning. In a similar fashion, systematic reviewersspecify inclusion and exclusion criteria for synthesizingstudies, but the criteria are usually much broader.

Inclusion and exclusion criteria

• Inclusion and exclusion criteria are theconditions that must be met in order toparticipate in a clinical trial, or the standardsused to determine whether a person may beallowed to participate in a clinical trial. Themost important criteria used to determineappropriateness for clinical trial participationinclude age, sex, the type and stage ofa disease, treatment history, and othermedical conditions.