Quadruple P
 Stop or Go?
 Apostel VI
 ECV Implementation
 HTA Longterm conseq.
 HTA Preference study
 HyRAS (Hypitat followup)
 Implementatie Tour
 Triple P
 WOMB study

 Cancer in pregnancy
 Doula study
 ECV tocolysis
 ECV Uterine relaxation
 Keizerlijk litteken
 STAN followup
 VET study
 Wat bevalt beter

IMPACT study

Improving Participation in Clinical Trials: A Health Technology Assessment (HTA) study


The randomized clinical trial is considered to be the best research tool to evaluate the effectiveness of medical intervention. One of the most commonly reported problems with the conduct of randomised trials is that recruitment is usually slower than expected, with many trials failing to reach their planned sample size within the timescale and funding originally envisaged.

Campbell et al. showed that less than one-third of 114 trials recruited their original target within the time originally specified, and abound one-third needed prolonged recruitment time. In the 1970s Lasagna stated that ‘in any trial, the incidence of the disease studied will be reduced to 10% of the original estimate’, this is currently known as Lasagna’s law. This law also seems to hold in Dutch primary care research.

If the target sample size is not achieved, the trial has less statistical power to detect potentially important differences between the groups and make the results less useful.

In addition, if recruitment has to be extended to reach the required sample size, the trial will cost more and take longer, delaying the use of the results in clinical practice. Moreover as the total amount of funding is limited, fewer trials can be conducted overall with the limited funding and resources available, and hence less information will be available.

Identifying reasons for lack of recruitment is important to both improve the quality of the study results as well as to improve efficient use of research grants.

Reasons for lack of recruitment can be found at the level of the patients, the doctor or the organisation level and will involve issues on trial design and trial organisation also play a role. These reasons might be different across different specialties, due to the nature of the disease or the population of patients.
A rule which can help to predict a (un)successful recruitment is currently not available. We aim to identify predictors for (un)successful patient recruitment at the level of the patient, the doctor and the organizational level.

We will perform two cohort studies and one case control study. The first cohort will consist of a set of multicenter trials performed in the obstetrics consortium: a questionnaire will be send to all gynaecologists recruiting for these trials to identify predictors (aggregated at level of department) for a high percentage randomized patients in a department. In a case control-study nested in this cohort we will interview patients who refused or consented participation to identify patient related factors.

In a second cohort study, we will study trials that were prospectively registered in the Dutch Trial Register. Using a questionnaire survey we will study whether issues on hospital organization, trial organization, planning and trial design were predictive for successful recruitment (80% of the patients recruited within the planned time).

These predictors can be used to assess the feasibility of new trials prior to funding and they can be used by the principal investigator to identify openings for improvements of feasibility in recruitment of patients. Predictors for (un)successful recruitment should be coupled to evidence-based interventions to optimize recruitment in trials.

Based on this we will develop a set of recommendations and a checklist that can be used by individual trialist to improve participation in clinical trials.

Project members

K. Oude Rengerink, MSc, AMC Amsterdam

Dr. L. Hooft, AMC Amsterdam

Dr. B.C. Opmeer, AMC Amsterdam

Prof. B.W. Mol, AMC Amsterdam


For more information about the study, please contact Katrien Oude Rengerink, K.OudeRengerink@amc.uva.nl

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