gms | German Medical Science

Background: Diagnostic studies aim to estimate the proportion of correctly classified diseased and non-diseased individuals, namely sensitivity and specificity. To evaluate a diagnostic test, its effectiveness is compared to either a reference standard, which defines the true disease status, or to a standard test. If there is no standard test as a comparator, the aim is to demonstrate a pre-specified minimum sensitivity and specificity of the experimental test. If there is a standard test, both tests and the reference standard should be applied in all study participants if it is ethically acceptable and feasible [1]. Otherwise, the two tests should be randomly assigned and the reference standard should be used in all. This results in three study designs: the single-test, and the paired or unpaired two-tests design.

Methods: As in any clinical trial, a sample size calculation should be performed to avoid including too many or too few individuals. However, assumptions for the sample size planning are often uncertain. Reasons for biased estimates in diagnostic accuracy studies are analysed in Rutjes et al. [2]. Long-established methods for adaptive designs with sample size re-estimation from the field of interventional studies [3] have not yet been transferred to diagnostic studies with the particularity of co-primary endpoints.

Results: In this talk, a corresponding approach for the unblinded sample size re-estimation, which is applicable for all three designs, will be presented and illustrated by an example study. Furthermore, the results of a comprehensive simulation study will be presented, and the potential and limitations of the method will be discussed.

Conclusion: Adaptive designs with unblinded sample size re-estimation in diagnostic accuracy studies are a helpful tool to obtain efficient studies and reliable results.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.