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A control event rate used in sample size planning is an assumption, not a fixed fact. Explain the population, follow-up duration and endpoint definition that produced it before relying on a single estimate.
Define the question and assumptions
Separate evidence relevant to the intended population from evidence drawn from materially different settings. Historical rates may reflect different standard care or event ascertainment. A statistician can evaluate sample size and event requirements across a plausible range instead of concealing uncertainty behind one precise number.
Hypothetical study example
In a hypothetical time-to-event study, historical records suggest frequent events but proposed sites have shorter follow-up. The team evaluates low, central and high event scenarios alongside recruitment duration. This reveals that completing enrolment may still leave the study short of the required information.
Design review checks
- Check that source populations and endpoint definitions match the proposed protocol.
- Keep assumptions about event frequency separate from assumptions about loss to follow-up.
- Show recruitment duration and follow-up needs together for each planning scenario.
Record the decision and its limits
Record the evidence supporting the central assumption and the alternatives considered. If a later reassessment is contemplated, plan its method, access controls and decision rules in advance. Choosing an attractive rate after seeing treatment results cannot replace prospective design justification.
Frequently asked questions
- Is the newest publication always the best source?
- No. Similarity in population, measurement and care conditions also matters.
- Does increasing sample size remove every uncertainty?
- No. An unsuitable endpoint assumption or inadequate follow-up can remain problematic in a larger study.