A non-parametric approach to predict the recruitment for randomized clinical trials: an example in elderly inpatient settings.

ABSTRACT:

Background

Accurate prediction of subject recruitment, which is critical to the success of a study, remains an ongoing challenge. Previous prediction models often rely on parametric assumptions which are not always met or may be difficult to implement. We aim to develop a novel method that is less sensitive to model assumptions and relatively easy to implement.

Methods

We create a weighted resampling-based approach to predict enrollment in year two based on recruitment data from year one of the completed GRIPS and PACE clinical trials. Different weight functions accounted for a range of potential enrollment trajectory patterns. Prediction accuracy was measured by Euclidean distance for enrollment sequence in year two, total enrollment over time, and total weeks to enroll a f

SUBMITTER: Villasante-Tezanos A 

PROVIDER: S-EPMC11363376 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature