Biostatistics: Using Restricted Mean Survival Time (RMST) in Oncology Trials to Improve Outcomes

Recent oncology trials have been approved based on RMST analysis. This proves that RMST is handling an unmet need when dealing with non-proportional hazards violations.

To analyse overall survival rates traditionally Kaplan-Meier (Logrank) and Hazard Ratio by Cox Proportional Hazards analysis are performed. However, when dealing with non-proportional hazards violations these analysis methods do not always produce meaningful results. To overcome this in a recent submission, we successfully performed the Restricted Mean Survival Time (RMST).

RMST Analysis Advantages

• Model free, robust and easily interpretable treatment effect information
• Produces radically powerful patterns of difference as has been observed in some recent Oncology clinical trials
• Accepted approach by regulatory agencies and industry leaders

Industry leaders from Pharma, Biotech and FDA are bringing this non-proportionality hazard violations analysis into the limelight as a better way of handling those violations.

This analysis has been implemented across several clinical trials. For more information on this trend you can read more at Duke University's Public Workshop on "Oncology Clinical Trials in the Presence of Non-Proportional Hazards" - https://healthpolicy.duke.edu/events/public-workshop-oncology-clinical-trials-presence-non-proportional-hazards.

You can learn even more by visiting the Harvard School of Public Health for RMST Analysis, http://bcb.dfci.harvard.edu/~huno/computer-program/rmst2_ver003.sas.

If you have questions or would just like to know more about the non-proportional hazards violation in oncology trials and how it can be analysed to lead to more meaningful results, please contact Revathy Duvedi, Biostatistics Senior Program Manager, Clinical Research Services, ICON at Revathy.Duvedi@iconplc.com.