CONTRACT RESEARCH
Blinding and Randomization Strategies for Well-Controlled Clinical Studies
Brent Hale
Senior Project Manager, Biostatistics, Cenduit
Modern Randomization Methodologies and Technologies
Prior to the adoption of newer, more advanced systems we use in clinical trials today, bias was a common theme. As noted in the article: “FDA and Clinical Drug Trials: A Short History” by Suzanne White Junod, Ph.D., this was often observed when physicians would treat sicker patients with known controls, while seemingly stronger patients received experimental products. Furthermore, when not blinded, knowledge of a patient’s treatment regimen tended to affect the level of care a health care worker would provide and also influenced their observations.
With the introduction of modern methodologies, such as a randomization and blinding, sponsors have been able to gain much more control over their clinical trial studies. In this article, we’ll review some of the major milestones in technology and strategy that have helped pave the way for a more adequate, well-managed study.
Technology Brings New Benefits
By the early 1990s, biopharma companies and CROs began using technology more frequently and as a result, new methods of randomization were used to maintain the blind to avoid bias, minimize wasted medication and greatly improve the clinical supply chain. Today, these systems are generally referred to as Interactive Response Technology (IRT) systems – which utilize innovative technologies and user interfaces via PC, tablet, phone and similar devices.
An important advantage of IRT is a more efficient supply chain. Using a six-month clinical trial as an example, suppose each patient visits the site once per month of the study. Instead of sending six months of medication per patient to each site, only one or two visits worth per patient could be supplied initially. When a patient is randomized via the IRT, the investigative staff is told the pack number to give the patient for that visit. For subsequent visits, the system knows which visit packs at the site will be valid for the patient and again, tells the staff which pack to dispense. Thus, if a patient discontinues early, hardly any drug is wasted as the remaining packs at the site can still be used by other patients on the same regimen.
Another advantage of IRT randomization is the ability to maintain balance over the duration of a study to ensure accuracy. There are a variety of methods for doing so and these are often referred to as “minimization of imbalance” designs, or simply as “minimization.” The design examples mentioned so far have been very basic, but clinical trials generally involve stratification factors, such as gender, smoking status, age and other considerations. IRT is indispensable in ensuring balance across the study and across various stratification factors by intelligently managing the randomization scheme according to the design and needs of the study.
Minimization of Imbalance Methods
One well-established method for minimization of imbalance is called the “biased coin.” For example, when the first patient enrolls in a study, there is an equal chance of getting drug A or B, much like tossing a coin and coming up with heads or tails. If the first patient is assigned drug A and the second patient gets B, we have balance. But if both patients are assigned drug A, we would have an imbalance with two A’s and zero B’s. For the next randomization, the algorithm would weigh one side of the coin to give a higher probability that it will result in drug B, thereby minimizing the imbalance.
Of course, clinical trials rarely have such simple designs and usually have multiple treatment arms, varying treatment balance ratios, multiple stratification factors and other variables that must be considered. Even for highly complex designs, minimization methods can help to maintain balance. This is generally achieved by using formulas to calculate an imbalance score as each successive patient is enrolled
Treatment Group
Gender (M:F) Smoker (Y:N)
Age Group (Low:High) Imbalance Scores method 1/method 2 Pharmaceutical Outsourcing | 16 | November/December 2016
Table 1. Fixed List at Patient Kit Level A
B
5:2 2:5 3:4
3:5 4:4 4:4
If A If B 6:2 = 4 4:5 = 1 2:6 = 4 4:5 = 1 4:4 = 0 5:4 = 1 16/8
14/3
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