Clinical Researcher—August 2019 (Volume 33, Issue 7)

PEER REVIEWED

Patrick Sturges, MS, CCRP

The success of a clinical trial depends on a myriad of factors, but none is more important than the clinical research participants. Optimized patient participation, achieved with effective recruitment and retention planning, is a key component to any successful clinical trial. With the emergence of real-world data (RWD) utilization in clinical research, achieving effective recruitment and retention is more plausible than at any other time in the field of clinical research. RWD facilitate a better understanding of the available patient population and improved protocol design. Consequently, recruitment and retention planning is streamlined to allow for optimized patient participation, enhanced adherence to enrollment windows, and close attention to budget parameters.

Background

Recruitment and retention of clinical trial participants are the cornerstones of any clinical trial; in the absence of either one, a clinical trial will fail. A clinical trial’s failure as a result of ineffective recruitment or retention is both an impediment to advances in the treatment of disease and a massive financial burden. A clinical trial unable to recruit or retain subjects cannot acquire the necessary data to support the statistical analysis of the endpoints, which renders the trial meaningless.

In addition, failure to recruit and retain clinical trial participants results in wasted time and money. Based on a previous review of hundreds of clinical trials on ClinicalTrials.gov, 39% of the trials were closed prematurely due to issues with recruitment and retention.{1}

According to data from a recent publication, recruitment/enrollment of clinical trial participants accounts for 32% to 40% of a clinical trial’s budget.{2} Allocation of such a significant portion of the clinical trial budget to recruitment is primarily associated with the frequent requirement to extend recruitment/enrollment windows beyond original estimates.{2} Although ineffective recruitment and retention are caused by a variety of factors, many can be addressed (and potentially eliminated) with enhanced clinical trial planning via utilization of RWD.

RWD are healthcare-related data derived from sources not associated with clinical trials.{3} RWD can include data from electronic health records, physician notes, tumor registries, insurance claims, and mobile devices and/or wearables.{3} RWD encompass a wide area of data, and the key to their utilization is the overall integration of the various sources of the data. The future of healthcare is in sharing of RWD and ensuring a seamless integration of all the platforms where the data are housed.

Taking a Deeper Dive

The effectiveness of recruitment and retention is influenced by numerous factors. For the purposes of this article, the most impactful factors will be discussed. First, clinical trial participation among adults ranges from 5% to 10% across most therapeutic areas, and participation for older adults is as low as 3%.{4,5} Therefore, there is a vast population of potential clinical trial participants left unrecruited into clinical trials.

Second, clinical trial protocols are too complex—the inclusion/exclusion criteria are too restrictive, data are being collected for endpoints having no bearing on the critical endpoints of safety and effectiveness, and there are too many required patient visits, blood draws, and additional tests.{6}

Third, which is linked to protocol complexity, frequent protocol amendments and subsequent re-consenting (when required) negatively impact patient recruitment and retention.{6}

Fourth, the sample size for many clinical trials is typically quite large as compared to the study population being examined. In some instances, clinical trials are either overpowered (more clinical trial participants targeted than needed to achieve statistical significance) or target a larger than necessary recruitment number to support secondary endpoints.{7}

Optimizing the process of recruiting and retaining clinical research participants is a primary focus of stakeholders in the arena of clinical research. In view of the impediments to advances in treatment of disease caused by the wasted time and financial burden resulting from ineffective recruitment and retention, stakeholders are examining methods to improve upon the situation.

Methods currently being explored by stakeholders include:

Leveraging RWD (the focus of this article)
Enhancing patient engagement throughout the entire life cycle of a clinical trial (from design to inception to regulatory and market approval)
Utilization of digital and social media platforms and artificial intelligence and machine learning

It is an exciting time in clinical research with the merging of precision medicine and digital healthcare, coupled with enhanced patient engagement.

The Shape of Things to Come?

In a March 2019 U.S. Food and Drug Administration (FDA) statement,{8} then-Commissioner Scott Gottlieb, MD, discussed the need to modernize clinical trials due to the rapidly changing landscape of precision medicine and digital healthcare. Specifically, the statement addressed the need to increase collaboration and data sharing during clinical trials across industry and academia. Furthermore, the statement described the importance of being able to combine RWD and data from clinical research.

The FDA clearly sees a need to better utilize the technology and data available to clinical researchers. RWD, and the technology associated with how they are shared and utilized, represent a significant piece to the puzzle of solving recruitment and retention issues in clinical trials.

The FDA statement serves as a reinforcement for most sponsors and contract research organizations (CROs) because they are already investing significant resources in methods to modernize clinical trials.{9} Importantly, for the purposes of this article, the investment in, and utilization of, RWD are key focal points for nearly all sponsors and CROs. RWD is beginning to show its value in addressing the issues associated with ineffective clinical trial recruitment and retention.{2,3,9–12)

Sponsors and CROs are seeing the importance of RWD in the design and implementation of their clinical trials. For example, all but one of the 30 organizations surveyed by Lamberti, et al. in 2018 have a RWD department that has been in existence for more than five years, and organizations are beginning to regularly conduct RWD studies to support the development of their clinical trials.{9}

Use with Care

Numerous issues, discussed earlier in this article, drive the lack of adult participation in clinical trials; however, these issues can be mitigated through the utilization of RWD. RWD can address each of the four issues mentioned above (low patient participation in clinical trials, complex protocols, excessive protocol amendments with re-consenting, and bloated sample sizes), provided they are shared and utilized appropriately.

For example, to increase patient participation in clinical trials, RWD can be used to broaden the access to clinical trials. Clinical trials are not always easily accessible to everyone—minority, elderly, low-income, and rural populations often do not have access to clinical trials. However, utilization of RWD in pragmatic clinical trials (PCTs) can allow primary care physicians, using electronic health records, to give clinical trial access to more people.{10}

While PCTs apply to more late-stage studies, randomized controlled trials (RCTs) apply to early- and mid-stage studies. RCTs can also benefit from RWD in the area of patient recruitment. Specifically, RWD can be used to explore inclusion/exclusion criteria for a study under development, and to ensure the criteria are identifying patients. If patients are not identified in the analysis of the RWD, an organization can easily revise the inclusion/exclusion criteria to ensure patients are identified. Thus, once a protocol is implemented, it will be guaranteed that a given patient population exists. In fact, some RWD analysis platforms have a tool for examining the projected number of patients that will likely be identified for a given study.

However, while the above use of RWD addresses subject participation at the level of the study type and protocol design, it does not address other issues with recruitment—namely, complex protocols, excessive protocol amendments, and re-consenting. Utilization of RWD fosters a less complex environment in clinical trials requiring fewer amendments.

Because RWD are actual raw healthcare data, they can be analyzed in a variety of ways—to identify the best way to design a protocol and to ensure protocol amendments are essentially absent from a study (this would also eliminate the need for re-consenting). Of course, protocol amendments and re-consenting would still have to occur if there were unavoidable changes required (e.g., FDA-required changes during the study or updated safety information).

Finally, sample sizes in many clinical trials are excessive. Organizations tend to overestimate the population of subjects needed for statistical significance, and additional subjects often are targeted for the sole purpose of supporting unnecessary endpoints.

Using RWD, organizations can refine their targeted patient population. In fact, RWD can be used to show what the results of a large RCT might be. Specifically, RWD can be used to support a single experimental treatment arm trial. In this example, RWD can be utilized to determine the outcomes of a similar patient population using different treatments already approved for use.{3}

In one of the most significant developments in the use of RWD, a global health research network used RWD to show it could use the available data (and analysis platform) to replicate a large RCT in cardiovascular outcomes for two different diabetes treatments.{12}

The future of recruitment and retention planning in clinical trials will most certainly include the widespread utilization of RWD.

Disclaimer

This article is solely the work of the author and not the author’s institution. Accordingly, any of the author’s opinions expressed herein are independent of the author’s institution.

References

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Stapff PM. 2018. Using real world data to assess cardiovascular outcomes of two antidiabetic treatment classes. World J Diabetes 9(12):252–7.