Which design element helps ensure prognostic factors are balanced across treatment groups?

• A. Blinding.
• B. Stratified analyses after data collection.
• C. Randomization.
• D. Non-random assignment.

Answer: (C)

Balancing baseline characteristics, or prognostic factors, across treatment groups is essential so that differences in outcomes can be attributed to the intervention rather than preexisting differences. Randomization is the design element that achieves this by assigning participants to groups by chance, which distributes both known and unknown prognostic factors evenly across groups on average. This minimizes confounding and makes groups comparable at the start of the trial.

Blinding helps prevent bias in how outcomes are assessed or reported, but it doesn’t ensure that prognostic factors are balanced between groups. Stratified analyses after data collection look for or adjust for imbalances after the fact, which is an analytic step—not a design method to balance groups. Non-random assignment, by contrast, tends to produce systematic differences between groups and increases bias.