Project:

Large Simple Trials

overview icon Overview

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

“NIH staff scientists have been actively engaged in CTTI’s Large Simple Trial  (LST) Project, helping, for example, to organize and moderate a multi-stakeholder CTTI meeting held May 13-14, 2013. CTTI deliberations almost certainly informed a New England Journal of Medicine Perspective essay on randomized registry trials. The CTTI work has also stimulated and informed NIH’s...” (Read the full quote in CTTI's 2013 Annual Report.)

Michael Lauer, MD, Director, Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH)

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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)

  • To obtain a deeper understanding of stakeholders’ perceived barriers to using LSTs
  • To facilitate an informed discussion of practices and challenges in conducting LSTs
  • To issue recommendations for future approaches that will facilitate the appropriate and efficient use of LSTs

LSTs will be used more often for appropriate trials conducted for regulatory submissions and other purposes.

  • Implementing LSTs can improve clinical trial data that informs medical decision-making. Increasing the number of enrolled subjects in a particular trial enhances the statistical power of the results; thus, problems associated with small sample sizes (i.e., ambiguous results, lack of statistical differences, uninterpretable data, the effect of random errors) are eliminated.
  • Optimization of LST operations would lead to increased efficiency and reduced costs of clinical trial conduct.
  • With a larger sample size of subjects, there are opportunities to streamline data collection so that only the most relevant data are recorded to meet trial objectives and the amount of nonserious adverse event data can be reduced, thereby reducing the burden on investigators.

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:

  • An overly complicated informed consent process
  • The desire to acquire as much information as possible from one trial
  • The perception that the NIH focuses mainly on basic science
  • Cultural barriers and stakeholder desire
  • Patient recruitment and compliance
  • Lack of harmonization in regulations
  • Expensive academic incentives
  • Lack of consistency with clinical practice

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.

Project Team Members

Role Name Affiliationsort descending
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