7.2 - Assessing Accrual

7.2 - Assessing Accrual

It is unfortunate that some clinical trials are terminated early due to low accrual, which is a waste of resources and time for all those involved. Investigators often overestimate the accrual rate because they may not account for (1) the restrictions imposed by the eligibility criteria and (2) the refusal by some eligible patients to participate.

A famous saying which speaks to the challenges associated with recruitment among clinical trialists is “The incidence of a disease diminishes when you initiate a study on it.” (source unknown)

Run-in periods or extended baseline periods are helpful in assessing which eligible patients will adhere to the protocol. For example, patients can be administered a placebo during the run-in period and monitored for treatment compliance. At the completion of the run-in period, those patients who meet the treatment compliance criteria are then randomized to treatment, whereas those who do not are discontinued in the study. Another advantage of incorporating a run-in period is that it may provide the opportunity for patients to be stabilized via a standard medication prior to randomization.

One criticism of incorporating a run-in period is that it could decrease the external validity of the trial because in the real world some patients will not be very compliant. Thus, a trial based on very compliant patients may overestimate the effectiveness of the treatment.

Sometimes it is possible to conduct a formal survey of patients prior to the onset of a trial to determine the proportion that would consider participation. This might indicate to the researcher the approximate proportion of patients that would consider participating and enable realistic timetables for completing trials..

In any event, it is extremely important to monitor accrual on a regular basis throughout the course of a trial. An accrual graph with target and the actual number of recruited patients helps monitor the process. This task typically falls on the statistician. Here is an example of a plot monitoring the accrual of patients.

TimeStudy End# PatientsTargetActual

The target assumes a constant accrual of patients. There was a lag in the number of patients at the beginning that were recruited but it caught up with the target for recruitment by the end of the study. This struggle in the number of patients recruited is very typical. Recruitment is always a struggle. Everyone on the research team needs to help with this process.


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