Predicting enrollment performance of investigational centers in phase III multi-center clinical trials

Rutger M. van den Bor*, Diederick E. Grobbee, Bas J. Oosterman, Petrus W J Vaessen, Kit C.B. Roes

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Failure to meet subject recruitment targets in clinical trials continues to be a widespread problem with potentially serious scientific, logistical, financial and ethical consequences. On the operational level, enrollment-related issues may be mitigated by careful site selection and by allocating monitoring or training resources proportionally to the anticipated risk of poor enrollment. Such procedures require estimates of the expected recruitment performance that are sufficiently reliable to allow centers to be sensibly categorized. In this study, we investigate whether information obtained from feasibility questionnaires can potentially be used to predict which centers will and which centers will not meet their enrollment targets by means of multivariable logistic regression analysis. From a large set of 59 candidate predictors, we determined the subset that is optimal for predictive purposes using Least Absolute Shrinkage and Selection Operator (LASSO) regularization. Although the extent to which the results are generalizable remains to be determined, they indicate that the prediction accuracy of the optimal model is only a marginal improvement over the intercept-only model, illustrating the difficulty of prediction in this setting.

Original languageEnglish
Pages (from-to)208-216
Number of pages9
JournalContemporary Clinical Trials Communications
Publication statusPublished - 1 Sept 2017


  • Feasibility studies
  • Risk-based monitoring
  • Site performance prediction
  • Site questionnaires
  • Trial accrual
  • Trial recruitment


Dive into the research topics of 'Predicting enrollment performance of investigational centers in phase III multi-center clinical trials'. Together they form a unique fingerprint.

Cite this