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Nonparametric Estimation of the Patient-Weighted While-Alive Estimand
Alessandra Ragni1, Torben Martinussen2, Thomas Scheike2
1MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy.
Biometrical Journal. Biometrische Zeitschrift
|May 30, 2026
Summary
This study introduces a patient-weighted while-alive estimand for recurrent event trials. The proposed efficient estimator accounts for patient history, improving treatment effect assessment in clinical research.
Area of Science:
- Biostatistics
- Clinical Trial Methodology
- Survival Analysis
Background:
- Recurrent event data in clinical trials requires comprehensive patient history assessment.
- Early deaths can distort treatment effect interpretation in survival analysis.
- A while-alive strategy is crucial for accurate assessment of treatment effects.
Purpose of the Study:
- To develop efficient estimation methods for the patient-weighted while-alive estimand.
- To address complexities in recurrent event settings with a novel estimator.
- To demonstrate the practical utility and benefits of the while-alive approach.
Main Methods:
- Derivation of the efficient influence function for the while-alive estimand.
- Development of a one-step estimator for illness-death models.
- Proposal of an alternative, high-efficiency estimator for recurrent events in randomized trials.
Main Results:
- The one-step estimator is intractable for complex recurrent event models.
- A practical, efficient estimator for recurrent events is proposed.
- The proposed estimator shows practical applicability in real-world case studies.
Conclusions:
- The patient-weighted while-alive approach offers benefits over existing methods.
- The developed estimator enhances the assessment of treatment effects in recurrent event trials.
- This methodology improves the interpretation of clinical trial outcomes involving recurrent events.
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