Rho experts recently attended the FDA-AACR-ASA Workshop on the use of overall survival as an endpoint in oncology trials.  In a series of five blogposts, they will discuss key topics to consider when designing such a study as presented at the workshop. These topics will include study design, endpoint construction, subgroup considerations, and analysis interpretation. This is the fourth blog in the series.

Longer life spans for patients with cancer is the ultimate goal in oncology clinical trials. This leads to the idea that overall survival (OS) should always be a specified endpoint in the study protocol. However, OS outcomes take time to accumulate data necessary to power for the endpoint, and in today’s fast paced world, people do not want to wait 20 years for a potential lifesaving drug to come to market. At the same time, we as researchers and fellow humans bear the responsibility for potential harm and toxicities that may arise from new experimental therapies. How do we get both information to rule out harm and assess the overall survival benefit, while still being realistic in our conduct of oncology clinical trials? The answer to that question, depends on a variety of factors, such as the type and aggressiveness of the cancer. As you are designing your next clinical trial assessing OS, here are some items to keep in mind:

Design aspects

OS has been less and less pre-specified as a primary efficacy endpoint in recent years, due to intermediate endpoints such as progression-free survival (PFS) and overall response rate (ORR) allowing earlier approval due these alternative endpoints requiring shorter follow-up time. When OS is not an efficacy endpoint at all, the FDA has encouraged oncology trials to specify OS as a safety endpoint, and if possible, include thresholds for harm that may be used to inform decision-making, based on a variety of considerations such as disease setting, feasibility of obtaining long-term OS data, rate of mortality, physician/patient input, and known toxicity.

One way to measure harm via OS is to specify thresholds for harm as shown in the illustration below:

A lower boundary could be “no difference between treatments,” while an upper boundary could be a certain risk of death higher for the experimental treatment.

Analysis aspects

Whether or not OS is included as an efficacy or safety endpoint, multiple specified sensitivity and supplementary analyses in the statistical analysis plan can help to interpret OS as it pertains to understanding the impact of intercurrent events (for example, starting a new line of anti-cancer therapy) or when deviations from analysis model assumptions occur.

With these considerations in mind, a rigorous plan for assessment of OS is necessary to provide regulators additional information when deciding on approval. Partnering with an experienced CRO can help guide the process to ensure a plan that best fits the study objectives is chosen. Ultimately, it is critical to specify in the protocol and/or statistical analysis plan how OS will be assessed and to include guidelines for ruling out OS harm from an experimental treatment in oncology trials. That way, both patient safety and research integrity are maintained, regulatory approval can be reached, and treatments can reach the patients in need.

Abram Graham, MS, Senior Biostatistician, has 9 years of experience providing statistical support for Phase I-III clinical trials, acting as both a supporting and lead statistician. His experience includes writing detailed statistical analysis plans including estimands, preparing CDISC-compliant specifications for SDTM and ADaM datasets, and preparing statistical displays and reports for a variety of therapeutic areas. Mr. Graham’s academic background includes a Bachelor’s degree in Biostatistics from The University of North Carolina at Chapel Hill, and a Master’s degree in Biometry from The University of Reading (England, United Kingdom). 

Regina Tayag, MA, Senior Biostatistician, has 8 years of experience as a biostatistician in the CRO industry. By leading statistical efforts in clinical studies from study start up activities through CSR completion, CDISC submission package creation, and additional analyses for publications, Ms. Tayag has provided steady and reliable support as a lead biostatistician. She has worked on a variety of therapeutic areas, including rare diseases and oncology, for phase I-IV clinical trials.