Estimating enrollment potential for a clinical trial is a typical part of the feasibility process. Yet, patient enrollment remains one of the greatest challenges in the clinical research industry. In fact, most trials end up doubling their original timelines to meet enrollment goals, and 48% of sites under-enroll study volunteers (Tufts, 2013).
To help prevent poor-enrolling protocols, we share takeaways from the free eBook, Improving Site-Sponsor Relationships: Proactive Strategies for Transparent Clinical Trials.
Improving accuracy of enrollment predictions during feasibility
What sites should analyze when completing feasibility questionnaires, in regard to enrollment potential:
- Is the indication feasible for your site?
- Is there a precedence of the disease across various data sources?
- Do you have the patient population to draw from?
- Of the full patient population, how many would actually want to be involved in this type of trial?
- If you once had a huge patient pool, have those patients since gone on treatments?
- How is your past enrollment performance on similar studies?
With this information, sites can provide an enrollment analysis and demonstrate how consistently they have performed in terms of their ability to achieve timely First Patient In (FPI), as well as overall enrollment targets. Many sponsors prefer sites provide objective evidence of performance over an estimate alone.
How sponsors can help sites improve enrollment estimates during feasibility:
- Explain the goal of the questionnaire to the site and what you’re looking for
- Use data collected from sites for prior projects and track their capabilities in a database to eliminate the need for sites to complete redundant information each time
- Give sites enough time to complete the questionnaire
This enables sites to use the time they spend during the feasibility stages for more value-added activities, such as conducting more robust enrollment validation efforts that truly drive study success.
How sites can ensure they don’t open trials that won’t enroll:
1. Do a break-even analysis
How many patients would you need in order for it to make sense to take on the study?
Create a summary of worst case, best case and realistic recruitment scenarios and a summary of suggested changes to the eligibility criteria that would make the protocol likely to enroll more patients.
2. Don’t overestimate your enrollment potential
Be realistic and conservative in your estimate – sponsors and CROs would rather have sites underestimate than overestimate. Inflated enrollment estimates from sites are a huge problem for sponsors/CROs. If sites only enroll half the patients they predicted, the sponsor/CRO has to quickly add sites to increase enrollment.
3. Know when to walk away
Serial trial openers who are addicted to opening trials end up competing against themselves. After all, recruiting one subject can be worse than no subjects at all. However, more trials are not always better. Smart sites know when to walk away from a study, including when they don’t have an adequate number of patients.
How sponsors and sites can build their relationships for the long-term:
As honesty is the best policy with sponsors and will help a site’s chance of being considered for future studies, sites should communicate the following:
- Tell the sponsor of any competing studies that would interfere with enrollment
- Tell the sponsor about whether or not patients are available
- Tell the sponsor why you decline a study
- Ask the sponsor why you weren’t selected for a study
- Don’t just tell the sponsor what you think they want to hear
Sponsors can improve communication with sites by doing the following:
- Have a point person who can answer sites’ questions
- Tell sites where you are in the site selection process
- Share changes to inclusion/exclusion (I/E) criteria with sites and let them update their enrollment numbers
- Let sites that don’t get selected know why they weren’t chosen
- Tell sites candidly how they can improve and what you are looking for
Sponsors should build trust with sites by being clear that, just because they don’t have enough patients to get selected for this trial, it doesn’t mean they won’t be selected in the future. In turn, this can help sites realize the need to provide realistic and accurate estimates rather than feeling they need to inflate them just to get selected.
Revisiting enrollment estimates after feasibility
Many times, the initial enrollment estimate is based off of preliminary abstracts and not a final protocol. With this may come the full I/E criteria, in which case there will likely be changes to original enrollment estimates. It is important to update estimates upon receiving this information, so the sponsor can plan accordingly. However, sites should not be penalized for changing their enrollment estimates when they didn’t have enough information in the first place.
How sites can ensure accurate enrollment after they receive changes to the protocol:
- Conduct a more detailed review of the eligibility criteria and conduct further enrollment validation activities (e.g., EMR search, sample chart reviews, etc.) to update enrollment estimates.
- Tell the sponsor if enrollment numbers are reduced due to this new information.
- Supplement your new information by preparing a preliminary recruitment plan to illustrate you are thinking about supplementing your own pool of patients with recruitment from external sources.
What sponsors should analyze with regard to enrollment throughout a trial:
- Did predictions match realities?
- Were there any enrollment trends across sites?
- Did you need to add more sites than originally planned in order to enroll enough patients?
Using this information, sponsors can adjust the I/E criteria for future trial design and enrollment planning. Similarly, sites can use past performance data when considering future trials to open and estimating enrollment to come full circle.
For ideas that can helps sites and sponsors improve their partnerships, download the eBook, Improving Site-Sponsor Relationships: Proactive Strategies for Transparent Clinical Trials.