Purpose: There is a need to develop hybrid trial methodology combining the best parts of traditional randomized controlled trials (RCTs) and observational study designs to produce real-world evidence (RWE) that provides adequate scientific evidence for regulatory decision-making. Methods: This review explores how hybrid study designs that include features of RCTs and studies with real-world data (RWD) can combine the advantages of both to generate RWE that is fit for regulatory purposes. Results: Some hybrid designs include randomization and use pragmatic outcomes; other designs use single-arm trial data supplemented with external comparators derived from RWD or leverage novel data collection approaches to capture longterm outcomes in a real-world setting. Some of these approaches have already been successfully used in regulatory decisions, raising the possibility that studies using RWD could increasingly be used to augment or replace traditional RCTs for the demonstration of drug effectiveness in certain contexts. These changes come against a background of long reliance on RCTs for regulatory decision-making, which are labor-intensive, costly, and produce data that can have limited applicability in real-world clinical practice. Conclusions: While RWE from observational studies is well accepted for satisfying postapproval safety monitoring requirements, it has not commonly been used to demonstrate drug effectiveness for regulatory purposes. However, this position is changing as regulatory opinions, guidance frameworks, and RWD methodologies are evolving, with growing recognition of the value of using RWE that is acceptable for regulatory decision-making.
External controls have been primarily used in the setting of single‐arm trials of rare diseases; their use in common diseases has not been readily investigated, nor is there guidance on how to best select comparators. Thus, the objective of this study was to emulate a large cardiovascular outcome trial of type 2 diabetes to compare associations of effectiveness with different comparator groups to those reported in the trial. Using the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial, we investigated six comparator groups using three calendar time periods (Early: 1999–2003; Later: 2004–2008, and Contemporaneous: 2009–2013) and two comparators (sulfonylureas and other second‐to‐third‐line antidiabetic drugs). Hazard ratios (HRs) of the three‐point composite cardiovascular outcome were estimated using four variations of the propensity score (adjustment, stratification, fine stratification, and matching) and compared with the LEADER trial (HR, 0.87; 95% confidence interval, 0.78–0.97). When comparing users of liraglutide with users of sulfonylureas, the HRs ranged from 0.57 to 1.03, with estimates in the early period most closely reflecting the LEADER trial (HR, 0.57–0.88). In contrast, the HRs ranged from 0.73 to 0.97 when comparing liraglutide users with users of any second‐to‐third‐line antidiabetic drugs, although the later period generated estimates closest to the LEADER trial (HR, 0.77–0.84). Different methods of adjustment led to generally consistent HRs, aside from the fine stratification in the early period. This study highlights the complex interplay between comparator, temporality, and method of adjustment when selecting comparators using real‐word data. These design choices must be considered in the design of trial emulation studies.
Randomized controlled trials (RCTs) that assess overall survival are considered the “gold standard” when evaluating the efficacy and safety of a new oncology intervention. However, single-arm trials that use surrogate endpoints (e.g., objective response rate or duration of response) to evaluate clinical benefit have become the basis for accelerated or breakthrough regulatory approval of precision oncology drugs for cases where the target and research populations are relatively small. Interpretation of efficacy in single-arm trials can be challenging because such studies lack a standard-of-care comparator arm. Although an external control group can be based on data from other clinical trials, using an external control group based on data collected outside of a trial may not only offer an alternative to both RCTs and uncontrolled single-arm trials, but it may also help improve decision-making by study sponsors or regulatory authorities. Hence, leveraging real-world data (RWD) to construct external control arms in clinical trials that investigate the efficacy and safety of drug interventions in oncology has become a topic of interest. Herein, we review the benefits and challenges associated with the use of RWD to construct external control groups, and the relevance of RWD to early oncology drug development.
Incomplete information provided by the DNA genotypic test is more notable in patients with VF, suggesting that all resistance mutations associated with prior VF have not been archived in the proviral DNA or decreased to a level below the threshold of detection. In the case where no historical plasma genotypic test is available, DNA testing might be useful to rule out switching to rilpivirine/emtricitabine/tenofovir disoproxil fumarate.
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