The Inflation Reduction Act (IRA), passed in August 2022, marks a significant shift in the US healthcare landscape, particularly for Medicare. The IRA introduces reforms to Medicare’s prescription drug program (Part D), inflationary caps in Medicare (Part B), and Medicare price negotiation. To effectively navigate these changes, pharmaceutical companies must develop robust evidence-generation programs that support evolving value requirements throughout a drug’s life cycle. Read more »
Navigating the Clinical Development Landscape: Insights for Success in 2024
After explosive and frenetic activity in the clinical trial industry during the COVID era, the past two years have seen challenging market dynamics and a drop-off in activity. Every one of us working in clinical development has felt this slowdown, but as we begin 2024, there is reason for optimism. The future looks promising. Here are some things to consider as you go forward.
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Estimator Choice in Synthetic Controls Analyses
Synthetic control arm (SCA) methods are statistical methods that are seeing rapidly increasing use in comparative effectiveness research. SCA analyses often involve comparing single-arm trials against external control arms constructed from real-world data (RWD) where conducting randomized clinical trials is difficult or infeasible. These benefits are especially evident in rare disease trials where sample sizes are typically substantially smaller, and it is difficult to determine standard-of-care treatments. Rare disease trials conducted with very few patients translates to insufficient statistical power or are performed as single-arm trials that make it difficult to compare against other therapeutic options without SCA methods. Advanced statistical methods are applied to RWD to build the SCA in a way that allows for the appropriate comparison with data gathered during the execution of the single arm trial.
However, each synthetic control project has its own unique challenges with regards to generalizability of results, interpretation and associated statistical methodology. In rare disease indications, the severely limited sample sizes in both single-arm trial and RWD, can present design challenges for SCAs. At ISPOR US 2022, Eric Mackay and Aaron Springford, Research Principal at Cytel, contributed a podium presentation on ‘Power Implications of Estimator Choice in Synthetic Control Arm Analyses’.
FDA Guidance on the Design and Conduct of Externally Controlled Trials — What to Watch
The U.S. FDA has recently provided specific guidance[i] on the design and conduct of trials incorporating an external control group, sometimes known as a synthetic control arm. Their guidance represents the culmination of several other topics related to these trial designs and research themes, such as existing guidance on the use real-world data and real-world evidence,[ii] the use of electronic health records and medical claims to support regulatory decision-making,[iii] and guidance on demonstrating substantial evidence of effectiveness for drugs and biological products.[iv]
Early Planning Strategies for External Control Arms in HTA and Regulatory Submissions
To establish treatment efficacy and safety, regulatory and reimbursement decision-makers have traditionally preferred evidence from randomized clinical trials, which, by design, have a low risk of bias. However, single-arm trials (SAT) using an external control arm (ECA) are commonly performed for ethical reasons, due to the difficulties in identifying a suitable comparator arm(s) for head-to-head trials in a rapidly evolving therapeutic landscape and in recruiting patients in the case of rare diseases.
Epidemiological Methods to Tackle Real-World Evidence Challenges
Regulatory requirements regarding documentation for new medicines are constantly evolving. Previously, randomized controlled trials alone qualified as high-level evidence in pharmaceutical development — today, approval is often followed by requirements for additional post-approval studies or for so-called real-world evidence (RWE) studies. Here, I’ll explain these concepts and share epidemiological and statistical methods to tackle RWE challenges.
Data Challenges (and Solutions) for Externally Controlled Trials
Real-world data and evidence are increasingly being used in health care decisions and publications. However, there are challenges in identifying suitable data for external control arms, and researchers need to consider solutions to address issues like data quality, bias, and selection bias when using real-world evidence for comparative efficacy analyses.1 Read more »