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Sequential Event Rate Monitoring.

Dong-Yun Kim¹, Sung-Min Han²

¹National Institutes of Health, Bethesda, Maryland, USA.

Statistics in Medicine

|January 23, 2026

Summary

Sequential Event Rate Monitoring (SERM) offers a new, practical way to continuously monitor clinical trial event rates. This method enhances statistical power and ensures study integrity for time-to-event outcomes.

Keywords:

clinical trial continuous event rate monitoring sequential probability ratio test staggered entry time‐to‐event‐data

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Area of Science:

Clinical Trials
Biostatistics
Statistical Monitoring

Background:

Effective event rate monitoring is crucial for clinical trial statistical power and integrity, especially for time-to-event outcomes.
Existing methods may not fully leverage advanced statistical theories for continuous monitoring.

Purpose of the Study:

To introduce Sequential Event Rate Monitoring (SERM), a novel approach for continuous event rate monitoring in clinical trials.
To demonstrate the practical implementation and benefits of SERM using theoretical advancements.

Main Methods:

SERM utilizes the Sequential Probability Ratio Test (SPRT) with enhanced boundaries based on the nonlinear renewal theorem.
Decision boundaries are derived from simple formulas, facilitating ease of implementation.
The method operates on blinded data, preserving study integrity across various designs.

Main Results:

SERM provides a practical and efficient method for continuous event rate monitoring.
Real-world data from a Phase III trial illustrated SERM's potential for rapid assessment.
The method maintains statistical accuracy (Type I and II errors) even with slow patient accrual.

Conclusions:

SERM is a robust tool for enhancing clinical trial monitoring and enabling timely decision-making.
Its ease of implementation, data efficiency, and broad applicability make it valuable for diverse clinical settings.
This approach represents the first practical application of advanced renewal theorem concepts in clinical trial monitoring.