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  • 1.  Short Course - Beyond Hazard Ratios: RMST in Clinical Trial Design

    Posted 20 days ago

    Final Announcement | This Friday

    Is RMST the future of survival analysis? If you're still relying on hazard ratios, it may be time to rethink.

    For decades, the hazard ratio (HR) has been the default tool in survival analysis.

    But:

    • What happens when proportional hazards doesn't hold?
    • How do we interpret HR clinically?
    • Are we missing a more interpretable and robust alternative?

    Join us for a WTASA short course with Prof. Lu Tian (Stanford University):

    πŸ”₯ Beyond Hazard Ratios: RMST in Clinical Trial Design

    πŸ“… April 17, 2026
    ⏰ 2–5 PM (Central Time)
    πŸ’» Online

    This course introduces Restricted Mean Survival Time (RMST) - an increasingly important framework for:

    βœ” Clinically interpretable treatment effect
    βœ” Robust analysis under non-proportional hazards
    βœ” Modern clinical trial design

    πŸ“š Topics include:

    • Limitations of HR
    • RMST fundamentals
    • Trial design with RMST
    • Non-inferiority
    • Competing risks
    • Duration of response

    πŸ’΅ Registration: $20
    πŸ‘‰ https://lnkd.in/gbFzYbcE

    We anticipate a highly engaged audience across biostatistics, oncology, and clinical research.

    Final call - we look forward to seeing you there.

    πŸ‘‰ Can't make it live? No problem - a recording and slides will be available to all registered participants.

    #Statistics #Biostatistics #ClinicalTrials #SurvivalAnalysis #RMST #Oncology #DataScience #ASA



    ------------------------------
    Haitao Pan
    Associate Professor
    St. Jude Children's Research Hospital
    ------------------------------


  • 2.  RE: Short Course - Beyond Hazard Ratios: RMST in Clinical Trial Design

    Posted 19 days ago

    This is a great topic in survival analysis. The hazard ratio and log-rank test have been used for over 50 years to analyze survival data, yet the proportional hazards assumption is often difficult to justify clinically. Moreover, interpreting a hazard ratio of 0.80 in practice is not straightforward, as it lacks a direct connection to the underlying baseline hazard (e.g., from the control arm), making it unclear what a 20% reduction truly represents.


    Recent FDA guidance on survival analysis strongly suggests the need for a backup analysis plan beyond relying solely on the hazard ratio as a summary of the treatment effect.


    Professor Tian is an excellent lecturer-I am sure you will enjoy the talk.



    ------------------------------
    Lee-Jen Wei
    Professor
    Harvard University
    ------------------------------

    Original Message


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