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Simple tools for projecting patient recruitment

Poor recruitment to clinical trials is a well-recognised and serious problem. Various predictors of poor recruitment have been identified and of course should be accounted for in trial design. Trial planning however will need a realistic projection of sample recruitment that also allows for random variation – yet available information may be minimal early in the development of a proposal. Such projections are also required when estimating power for survival analyses (the yield of events depends both on numbers and timing of patient accrual) – for example if using the Stata add-on artsurv.

I show here how minimal information, simple formulae and some reasonable assumptions can be combined to estimate both a sensible projection of expected numbers and a plausible range of variation; in turn this variation indicates the extent to which achieving the target sample size may be delayed. Simple calculations also indicate potential gains from restricting eligibility to better-performing sites and the relative lack of benefit from opening better-performing sites first.

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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Silcocks, P. Simple tools for projecting patient recruitment. Trials 14 (Suppl 1), P137 (2013).

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