Type of randomization
- 1. TYPES OF RANDOMIZATION Guided by Dr. Jigna S. Shah Presented by Mr. Bharat Kumar 17MPH202 Department of Pharmacology, Institute of Pharmacy, Nirma university, Ahmedabad.
- 2. Randomization A method based on chance alone by which study participants are assigned to a treatment group. Randomization minimizes the differences among groups by equally distributing people with particular characteristics among all the trial arms. The researchers do not know which treatment is better.
- 4. 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: 1. the intervention exhibits a real effect; 2. the outcome difference is solely due to chance 3. there is a systematic difference (or bias) between the groups due to factors other than the intervention. Randomization aims to obviate the third possibility.
- 5. 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
- 6. Forms of Randomization • Simple Randomization • Block Randomization • Stratified Block Randomization • Dynamic (adaptive) random allocation
- 7. Simple Randomization • Randomization based on a single sequence of random assignments • basic method of simple randomization is flipping a coin • Computer generated sequence • 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.
- 8. Simple Randomization Randomization approach is simple and easy to implement in a clinical research. In large clinical research, simple randomization can be trusted to generate similar numbers of subjects among groups. However, randomization results could be problematic in relatively small sample size clinical research, resulting in an unequal number of participants among groups.
- 9. Block Randomization • The block randomization method is designed to randomize subjects into groups that result in equal sample sizes • used to ensure a balance in sample size across groups over time • Used for small studies to maintain reasonably good 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
- 10. Illustration 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., The sequence 67126814…. will produce BBAA AABB ABAB BBAAAABB BAAB.
- 11. Stratified Block Randomization • The stratified randomization method addresses the need to control and balance the influence of covariates • This method can be used to achieve balance among groups in terms of subjects’ baseline characteristics (covariates). • Typical examples of such factors are age group, severity of condition, and treatment centre. Stratification simply means having separate block randomisation schemes for each combination of characteristics (‘stratum’) • For example, in a study where you expect treatment effect to differ with age and sex you may have four strata: male over 65, male under 65, female over 65 and female under 65
- 12. Dynamic (adaptive) random allocation Simple and block randomization methods are defined, and allocation sequences set up, before the start of the trial. In contrast, dynamic randomization methods allocate patients to treatment group by checking the allocation of similar patients already randomized, and allocating the next treatment group "live" to best balance the treatment groups across all stratification variables. Biased coin randomization and minimisation are two such methods.
- 13. Inappropriate randomisation 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
- 14. Bias Bias is said to have occurred if the results observed reflect other factors in addition to (or even instead of) the effect of the treatment: Some potential sources of bias: • Selection bias • Performance bias • Detection bias • Laboratory bias • Sample size bias
- 15. Selection bias Selection bias is concerned with two main issues: • systematic differences arise between the sampling population and the sample drawn and, • systematic differences arise between treatment groups at the outset of the trial, usually due to individuals either tampering with or predicting the allocation sequence.
- 16. Performance Bias Performance bias is the tendency for participants to change their behavior or responses to questions because they are aware of being in a trial and of their treatment allocation.
- 17. Detection Bias Detection bias is concerned primarily with blinding. In this case, however, the concern is about those collecting the data, not those providing it. The Cochrane Handbook warns that if “outcome assessors are aware of assignments, bias could be introduced into assessments of outcome, depending on who measures the outcomes.”
- 18. 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. • although this is most severe with subjectively graded results (pathology slides, photographs, ECG, etc.), this can also be a problem with "objective tests" such as laboratory assays which may be run subtly differently by the technician.
- 19. Sample size bias Sample size calculations are a deceptively simple tool to minimize bias – an insufficiently large sample size can lead to imprecise estimation, biasing the results downward.
- 20. Blinding Blinding is a procedure in which one or more parties in a trial are kept unaware of which treatment arms participants have been assigned to, in other words, which treatment was received. Blinding is an important aspect of any trial done in order to avoid and prevent conscious or unconscious bias in the design and execution of a clinical trial. 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.
- 21. Types of Blinding • Unblinded or open label : All parties are aware of the treatment the participant receives • Single blind or single-masked : Only the participant is unaware of the treatment they receive • Double blind or double-masked : The participant and the clinicians / data collectors are unaware of the treatment the participant receives • Triple blind : Participant, clinicians / data collectors and outcome adjudicators / data analysts are all unaware of the treatment the participant receives
- 22. Open Label Studies Open Label clinical trials do not attempt to disguise the new drug or treatment, meaning that no standard treatment or placebo is utilized. This leans towards bias, as both the patient and the physician are aware of which groups are receiving what type of treatment. These may be useful for • pilot studies • dose ranging studies However, even these applications may be substantially biased by knowledge of the treatment given and may result in • toxicity over (or under) reported • efficacy over estimated
- 23. Single Blind Studies • The participants in the clinical trial do not know if they are receiving the placebo or the real treatment. • This is done to reduce the risk of errors, since some participants might produce spurious results if they know that they are taking the placebo or medication. • In this model, the experimenter monitoring the participants knows which individuals received the placebo and which ones got the treatment under examination.
- 24. 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" • This is considered to be the superior model of clinical research since it eliminates outcomes that are produced due to placebo effect, as well as observer bias by the experimenter. The fact that the experimenter does not know which group received the placebo or the experimental drug means that the risk of conscious and unconscious observer bias is reduced, making the study more accurate.
- 25. Triple Blinding The treatment or intervention is unknown to (a) the research participant, (b) the individual(s) who administer the treatment or intervention, and (c) the individual(s) who assess the outcomes. The terms blind and masking are synonymous; both terms describe methods that heslp to ensure that individuals do not know which treatment or intervention is being administered. The purpose of triple-blinding procedures is to reduce assessment bias and to increase the accuracy and objectivity of clinical outcomes.
- 26. Reference • “An overview of randomization techniques: An unbiased assessment of outcome in clinical research” J Hum Reprod Sci. 2011 Jan-Apr; 4(1): 8–11, doi: 10.4103/0974-1208.82352 • “Designing a research project: randomised controlled trials and their principles” - J M Kendall • Triple-Blind Study , In: Encyclopedia of Research Design - Neil J. Salkind, DOI: http://dx.doi.org/10.4135/9781412961288.n471 • “Risk and evidence of bias in randomized controlled trials” – Alex Eble and Peter Boone, june 2012 • https://www.biopharmainstitute.com/faq/what-is-the-difference-between- single-blind-and-double-blind-clinical-trials • “Randomization in clinical trial, recruitment , inclusion and exclusion criteria” – Dr Urmila M. Aswar , pune • “The concept of randomization and blinding in clinical trials” – Suraj P Anand