Clinical trials : journal of the Society for Clinical Trials
-
There are many benefits of data sharing, including the promotion of new research from effective use of existing data, replication of findings through re-analysis of pooled data files, meta-analysis using individual patient data, and reinforcement of open scientific inquiry. A randomized controlled trial is considered as the 'gold standard' for establishing treatment effectiveness, but clinical trial research is very costly, and sharing data is an opportunity to expand the investment of the clinical trial beyond its original goals at minimal costs. ⋯ The Data Share website offers researchers easy access to de-identified data files with the goal to promote additional research and identify new findings from completed CTN studies. To maximize the utility of the website, ongoing collaborative efforts are needed to standardize the core measures used for data collection in the CTN studies with the goal to increase their comparability and to facilitate the ability to pool data files for cross-study analyses.
-
The clinical trials community has a never-ending search for dependable and reliable ways to improve clinical research. This exploration has led to considerable interest in adaptive clinical trial designs, which provide the flexibility to adjust trial characteristics on the basis of data reviewed at interim stages. Statisticians and clinical investigators have proposed or implemented a wide variety of adaptations in clinical trials, but specific approaches have met with differing levels of support. Within industry, investigators are actively exploring the benefits and pitfalls associated with adaptive designs (ADs). For example, a Drug Information Association (DIA) working group on ADs has engaged regulatory agencies in discussions. Many researchers working on publicly funded clinical trials, however, are not yet fully engaged in this discussion. We organized the Scientific Advances in Adaptive Clinical Trial Designs Workshop to begin a conversation about using ADs in publicly funded research. Held in November of 2009, the 1½-day workshop brought together representatives from the National Institutes of Health (NIH), the Food and Drug Administration (FDA), the European Medicines Agency (EMA), the pharmaceutical industry, nonprofit foundations, the patient advocacy community, and academia. The workshop offered a forum for participants to address issues of ADs that arise at the planning, designing, and execution stages of clinical trials, and to hear the perspectives of influential members of the clinical trials community. The participants also set forth recommendations for guiding action to promote the appropriate use of ADs. These recommendations have since been presented, discussed, and vetted in a number of venues including the University of Pennsylvania Conference on Statistical Issues in Clinical Trials and the Society for Clinical Trials annual meeting. ⋯ There is a growing interest in the use of adaptive clinical trial designs. However, a number of logistical barriers need to be addressed in order to obtain the potential advantages of an AD. Currently, the pharmaceutical industry is well ahead of academic trialists with respect to addressing these barriers. Academic trialists will need to address important issues such as education, infrastructure, modifications to existing funding models, and the impact on Data and Safety Monitoring Boards (DSMB) in order to achieve the possible benefits of adaptive clinical trial designs.
-
Clinical trials (CTs) are the mechanism by which research is translated into standards of care. Low recruitment among underserved and minority populations may result in inequity in access to the latest technology and treatments, compromise the generalizability, and lead to failure in identification of important positive or negative treatment effects among under-represented populations. ⋯ This study is the first to directly compare ineligibility and refusal rates and reasons captured prospectively in AA and White cancer patients. The data are consistent with earlier studies that indicated that AA patients more often are deemed ineligible and, when eligible, more often refuse participation. However, differences in reasons for ineligibility and refusal by race have implications for a cancer center to participate in CTs appropriate for the population of patients served. On a broader scale, consideration should be given to modifying eligibility criteria and other design aspects to permit broader participation of minority and other underserved groups.
-
Randomized Controlled Trial
Increasing trial efficiency by early reallocation of placebo nonresponders in sequential parallel comparison designs: application to antidepressant trials.
The sequential parallel comparison (SPC) design was proposed to improve the efficiency of psychiatric clinical trials by reducing the impact of placebo response. It consists of two consecutive placebo-controlled comparisons of which the second is only entered by placebo nonresponders from the first. Previous studies suggest that in antidepressant trials, nonresponse to placebo can already be predicted after 2 weeks of follow-up. This would allow to reduce the first phase of the SPC design to further increase its efficiency. ⋯ This study suggests that SPC designs are highly efficient alternatives to a conventional RCT in indications where placebo response is high and substantial treatment effects are established after a relatively short follow-up period (i.e., after the first SPC design phase). We conclude that SPC designs can reduce sample size requirements and increase success rates of antidepressant trials.
-
Consider a comparative, randomized clinical study with a specific event time as the primary end point. In the presence of censoring, standard methods of summarizing the treatment difference are based on Kaplan-Meier curves, the logrank test, and the point and interval estimates via Cox's procedure. Moreover, for designing and monitoring the study, one usually utilizes an event-driven scheme to determine the sample sizes and interim analysis time points. ⋯ The procedure discussed in this article can be a useful alternative to the standard PHs method in the survival analysis.