June 5, 2024Statistical Methods in Medical Research

Group sequential methods based on supremum logrank statistics under proportional and nonproportional hazards

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Authors

JBJean‐Marie BoherAix-Marseille Université TFThomas FilleronInserm PSPatrick SfumatoAix-Marseille Université

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Implication

Methodological study demonstrates robust group sequential supremum logrank tests under nonproportional hazards, suggesting improved power and early stopping in oncology trials.

Key Points

Supremum logrank statistics provide a robust testing framework for clinical trials that violate the proportional hazards assumption, maintaining statistical power.
Methodological evaluation uses a Monte Carlo algorithm to determine crossing boundaries for interim analyses within group sequential trial designs—allowing early stopping.
Numerical studies demonstrate favorable frequency properties under nonproportional hazards, supporting improved efficacy evaluation in immunotherapy oncology trials.

Cite This Study

Boher et al. (2024) studied this question.

synapsesocial.com/papers/68e660d7b6db6435875ef20e https://doi.org/10.1177/09622802241254211

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Implication

Methodological study demonstrates robust group sequential supremum logrank tests under nonproportional hazards, suggesting improved power and early stopping in oncology trials.

Group sequential methods based on supremum logrank statistics under proportional and nonproportional hazards

Discussion

Member takes

Implication

Key Points

Cite This Study

Group sequential methods based on supremum logrank statistics under proportional and nonproportional hazards

Discussion

Member takes

Implication

Key Points

Cite This Study

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