Surrogate endpoints create potential, require statistical validation

By Maggie Lynch contact

- Last updated on GMT

(Image: Getty/ gan chaonan)
(Image: Getty/ gan chaonan)
Transforming statistical data into a surrogate endpoint can enable comprehension of trial results sooner than usual, but few make the cut after formal validation, says drug development expert and DIA panelist.

Marc Buyse, CSO of the International Drug Development Institute, will sit on a panel during the DIA Annual Meeting next week, discussing statistical considerations and surrogate endpoints in clinical trials with other drug development experts.

The panel will focus on the use of statistics to accelerate drug candidate development.

Chronic and slowly progressing diseases can often pose difficulty when researchers look to define a clinical outcome, which is required for regulatory approval and clinical research. Using statistics and additional knowledge, researchers can create surrogate endpoints to be used as a means of measuring clinical outcomes in such diseases, while still maintaining a timely manner of drug development.

Buyse described a surrogate endpoint as a substitute for a clinical endpoint in a trial that enables researchers to measure short-term outcomes like tumor shrinkage or changes in a biomarker, rather than long-term impacts of treatment like survival or improved quality of life.

Read more:​ CROs debate: Can surrogate endpoints speed oncology drugs to market?

Surrogate endpoints can be critical in chronic and long-term conditions where clinical endpoints such as overall survival can take years to measure, said Buyse. These types of statistics can play an important role in life-threatening diseases, like cancer, and can provide access to new treatments.

“Surrogate endpoints can be measured earlier than clinical endpoints, allowing for the results of a clinical trial to be understood sooner than would usually be possible,”​ Buyse told us.

According to Buyse, technology advances in recent years have enabled researchers to use imaging and identification processes as surrogate endpoints.

However, the discussion of how to determine which points of data can be used as surrogate endpoints is ongoing: “Potential surrogates will usually require formal statistical validation to be acceptable from a regulatory point of view. In fact, there is such a high bar for acceptance that very few surrogate endpoint candidates have met the grade,” ​Buyse explained.

The DIA panel will examine not only how surrogate endpoints can be determined, but the ways in which they can be used for clinical trial protocols targeting both rare and common diseases.

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