Facilitating the Use of Large Simple Trials (LST)
A large simple trial (LST) is a type of randomized clinical trial (RCT) ideally suited to answer many important clinical questions and because it typically answers only one or 2 questions in a broader patient population, is generally more efficient and less expensive than other large RCTs. LSTs have a large sample size and statistical power to detect clinically relevant treatment effects, providing unambiguous results and minimizing the effects of random errors. Yet, LSTs are not often employed; CTTI found that barriers to implementing LSTs for regulatory purposes included 1) concerns that regulators will require more granular data, 2) operational concerns, and 3) lack of incentives and interest. Because optimizing LSTs will increase efficiency and reduce costs compared with current trials, CTTI published a manuscript describing solutions to overcome the associated barriers.
Project Status: Closed
RCTs are the gold standard for evaluating the risks and benefits of medical therapies in an unbiased and reliable way. Over time, large RCTs have become increasingly and prohibitively expensive and complex, and most fail to provide enough evidence to adequately inform medical decision-making, in part, due to the common problem of small sample sizes. Adoption of an LST design may be appropriate for some RCTs (e.g., moderately sized but clinically important treatment effect or prevalent disease) and would increase efficiency and reduce costs. Large trials are typically not considered simple endeavors due to perceived operational challenges, and sponsors are currently not dedicating a large percentage of resources to conduct LSTs.
Many clinical trial sponsors, investigators, and government agencies think the system of clinical trials in the United States could be improved if there were more LSTs which enrolled many (e.g., thousands) patients, had fewer barriers for trial participation, followed a simple and practical protocol, streamlined operational challenges, collected the most relevant data to meet the trial objectives, and used objective measurements and endpoints.
Facilitating the Use of Large Simple Trials (2012-2014)
LSTs will be used more often for appropriate trials conducted for regulatory submissions and other purposes.
Data from the survey and expert meeting indicated experts agreed that trials determining the risk-benefit balance of therapies must have 3 major features: be larger, simpler, and randomized. The US Food and Drug Administration (FDA) have promoted the use of LSTs and issued a 2012 draft guidance to serve 3 main functions: 1. improve the quality of safety assessment without compromising integrity and validity of trial results, 2. ease the burden on investigators and patients participating in a study, and 3. lower trial costs by facilitating the increased use of large, simple trials. However, despite the interest of sponsors and support from regulators, the adoption of LSTs has been limited. The main barrier identified to using LSTs was the perception of ongoing regulatory burden, including the concern that regulators will require more granular data after a trial is completed; yet, survey respondents were willing to support simplified trial designs if they allowed for achievement of regulatory goals. Secondary barriers included the following:
Because large trials are inherently not simple, experts suggested that it may be more reasonable to consider strategies for streamlining clinical trials, including being more thoughtful about site selection, having a more focused case report form (CRF), streamlining data collection and safety reporting, monitoring and following up more efficiently, and using registries where appropriate. Many of these suggestions can be guided by solutions proposed in the CTTI QbD project. Other suggested approaches are described in the LST publication, and examples of large trials that have been successfully streamlined are included in the Expert Meeting presentations.
Role | Name |
Affiliation![]() |
---|---|---|
Team Member | Robert Califf | Duke University |
Team Member | Zubin Eapen | Duke University |
Team Leader | Patrick Archdeacon | Food and Drug Administration |
Team Leader | Cheryl Grandinetti | Food and Drug Administration |
Team Member | Robert Temple | Food and Drug Administration |
Team Leader | Carolyn Petersen | Individual Patient/Caregiver |
Team Leader | David Gordon | National Institutes of Health |
Team Leader | Gail Pearson | National Institutes of Health |
Team Member | Michael Lauer | National Institutes of Health |
Team Leader | Preston Klassen | Orexigen |