The paper by Heitjan et al [11] provides very interesting and useful review of the methods for
predicting patient enrollment and event counts in clinical trials. The aim of this letter is to …

Background The design of a multi-center randomized controlled trial (RCT) involves multiple
considerations, such as the choice of the sample size, the number of centers and their …

The complexity of clinical trials and multi-state hierarchic structure of different operational
processes require developing new predictive analytic techniques for efficient modeling and …

Patient recruitment and drug supply planning are the biggest challenges for clinical study
design. The innovative statistical technique for modeling patient recruitment in multicentre …

Taking a decision on the feasibility and estimating the duration of patients' recruitment in a
clinical trial are very important but very hard questions to answer, mainly because of the …

To address different uncertainties associated with patient recruitment in multicentre clinical
trials a mixed Poisson model is elaborated (patients arrive at different clinical centres …

A novel analytic methodology for centralized statistical monitoring of the clinical trial interim
enrollment performance is developed. The underlying technique uses a Poisson-gamma …

Randomized clinical trial (RCT) studies are the gold standard for scientific evidence on
treatment benefits to patients. RCT outcomes may not be generalizable to clinical practice if …

A priori estimation of sample size and subject accrual in multi‐site, time‐to‐event clinical
trials is often challenging. Such trials are powered based on the number of events needed to …

In clinical trials, almost all key milestone dates can be defined in terms of time to endpoint
maturation (TTEM). The real time monitoring and accurate prediction of TTEM have a …