Cytel Blog

Early stage Phase 2 clinical trials are often designed as multi-stage single arm trials, which quickly identify inefficacious molecules and interventions, without subjecting too many patients to treatments with questionable standard of care. As the primary purpose of these designs is the early stopping for futility, it is often the case that very small cohorts enroll in early stages of the design. A larger cohort is only allowed to enroll when results from earlier enrollment suggest that there is clinical benefit to the new treatment.

The rise of Bayesian methods has meant that predictive power can be used to assess efficacy during these single arm Phase 2 studies, but how do they differ from traditional designs and when should they be used?

In recent times, Single arm trials are being increasingly used to assess new treatment interventions. They establish clinical benefit by demonstrating the effects of a new therapy or treatment, without the need to use placebo or standard of care as a control. Instead, an alternative approach known as external controls or synthetic control arms (SCA) are being used that leverages real world data and historical datasets. Technical knowledge of Bayesian methods is key to being able to design and implement such trials.

Breakthrough treatments in oncology and rare diseases are now commonly approved based on a pivotal single arm trial – however this is not always optimal. Use of single arm trials in oncology or rare diseases requires appropriate comparisons to be developed to document the benefits of the new treatment. Deriving such comparisons from real world or historical trial data is not straightforward and requires data source and methods expertise.

Recent years have witnessed improving survival outcomes for those struggling with a range of common kidney cancers. Scientists at Cytel recently published findings aiming to identify those baseline factors which influence a positive response to an established therapy. Such an investigation is critical to ensure that future treatment is informed by biomarker driven strategy.

Virtual ISPOR 2020, held November 16 to 19, presented new opportunities for scientific interaction amongst HEOR community. Cytel and Ingress Health, now a Cytel company, contributed to a range of events including interactive workshops, issue panels, on demand podium presentations and virtual poster presentations.

Continue reading for discussions on tracking COVID-19 trials, reflecting on the successes, opportunities and failures of real world solutions, and bridging the gap between real world data and clinical development.

MUCE is a Bayesian solution for cohort expansion trials where multiple dose(s) and multiple indication(s) are tested in parallel. Such methods are particularly important for areas like oncology where several doses and several indications must be tested for successful completion of early phase trials, and optimal choice of dose and population to move on from early phase to a reasonable dosage for Phase 3.

Note that for these situations the number of comparator arms for a trial can increase rather rapidly. Testing three doses with three indications essentially requires 9 different trials. An efficient way to test a higher number of trials is therefore necessary for accelerated clinical development.

Cytel and Ingress Health (now a Cytel company) will be contributing to a range of events at Virtual ISPOR EUROPE 2020, on November 16th – November 19th. Our Real-World analytics teams will be collaborating to deliver a number of interactive workshops, issue panels, posters and podiums to showcase their work and share innovative insights in HEOR, evidence generation, knowledge synthesis and decision analysis.

Click below to download our full list of sessions at ISPOR EUROPE and feel free to share this brochure with any colleagues who may find our sessions insightful.

In oncology, many manufacturers go into niche indications, where there are very specific tumors, and then they opt for a single arm trial. This potentially works for regulatory purposes (EMA/FDA). However, if they go to the local HTA authorities (NICE/CADTH), they will have to answer the question on the relative effectiveness of the new product compared to the standard of care in that country, and then its cost-effectiveness. Hence, typically, a manufacturer will identify a publication on a trial or real-world evidence on standard of care, or perhaps collect individual patient level data in clinical practice. Subsequently, it will conduct comparative effectiveness analyses for HTA purposes, a naïve comparison or an unanchored MAIC/STC/PSM of the single arm trial compared with the control arm.

In this two-part blog series, we interview Bart Heeg, Vice President HEOR and Founder at Ingress Health (A Cytel company). Bart provides us insights on the trends in HEOR and explains why Bayesian methods are also important for Health Economics. Read Part 1 here.

In this interview with Thomas Wilke, Principal Scientist at Ingress-Health (a Cytel company), we talk to him about his background and experience in Health Economics, understand the important considerations of real-world evidence studies and the impact of COVID-19 pandemic on the work of the health economics outcomes researchers who work at Ingress and Cytel. We also cover important HEOR topics such as its benefits for market access studies and real-world analytics (RWA) for regulatory submission.

Cytel and Ingress-Health will be contributing to a range of events at Virtual ISPOR EU 2020, on November 16th – November 19th. Our Real-World analytics teams will be collaborating to deliver a number of interactive workshops, issue panels, posters and podiums to showcase their work and share innovative insights in HEOR, evidence generation, knowledge synthesis and decision analysis.

Click below to download our full list of sessions at ISPOR EU