A Practical Guide to Randomization in Clinical Trials

A Practical Guide to Randomization in Clinical Trials
Why it Matters, How it Affects Power and How to Generate a Randomization Lists

Randomization is a central tenet in the design of clinical trials as it allows trialists to ensure their trial generates valid estimates of the effect of their treatment.

However, randomization can take on different forms depending on the practical constraints in a given trial and this can have significant implications on the analysis strategy and the expected power of a trial. 

You will learn about:

• What is Randomization & It’s Importance

• Common Randomization Strategies in Clinical Trials

• Effect of Randomization of Methods and Power

• Randomization Lists and Available Algorithms

A Practical Guide to Randomization in Clinical Trials

A pivotal component for clinical trials is randomization i.e. the random assignment of patients to receive either the experimental treatment(s) or controls.

Without randomization, it can be difficult to ensure statistical comparability for the treatment and thus generate valid statistical estimates. Blinded randomization also prevents operational bias due to trialists’ expectations influencing treatment assignment.

However, randomization can take on different forms depending on the constraints present in a trial or the preferred group characteristics of stakeholders.

For example, some larger interventions such as vaccines may require randomization on the level of region or hospital rather than per-subject. This “cluster randomization” has significant effects on the analysis strategy and resulting expected power for a given total sample size.

Therefore the randomization strategy must be considered carefully and integrated into the study design.

Once a randomization strategy is developed there is still the practical issue of implementation. A common issue is how to generate a randomization schedule that ensures statistical validity and blinding while maintaining certain preferred outcomes e.g. avoiding gender imbalance across groups, accounting for centers.

Randomization list algorithms such as block randomization are a key strategy for creating lists that can be used to generate appropriate group assignments over time.

Watch this tutorial, as we have discussed what randomization is and why it is important, some common types of randomization in clinical trials and their effect on analysis methods and power and how randomization list algorithms can be used to randomize subjects while taking account of issues such as centres or covariate imbalances.

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