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Analyzing differences between restricted mean survival time curves using pseudo-values.

Federico Ambrogi1,2, Simona Iacobelli3, Per Kragh Andersen4

  • 1Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy. federico.ambrogi@unimi.it.

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Summary
This summary is machine-generated.

Restricted mean survival time (RMST) differences offer a valuable alternative to hazard ratios for quantifying treatment effects in survival analysis. This study introduces a flexible model-based approach using pseudo-values for estimating RMST curves, enabling covariate adjustment.

Keywords:
Crossing survival curvesPseudo-valuesRMST curve difference

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Area of Science:

  • Biostatistics
  • Survival Analysis
  • Clinical Trials

Background:

  • Hazard ratios are standard for treatment effect quantification in time-to-event analysis.
  • However, alternative measures like Restricted Mean Survival Time (RMST) differences provide complementary insights into absolute and relative treatment effects.
  • Recent advancements focus on model-free estimation of RMST differences across follow-up times.

Purpose of the Study:

  • To propose a novel model-based method for estimating the Restricted Mean Survival Time (RMST) difference curve.
  • To enable covariate adjustment within this model-based framework.
  • To provide a method for computing simultaneous confidence regions for the RMST difference curve.

Main Methods:

  • A model-based approach using pseudo-values is proposed for estimating the RMST difference curve.
  • This method allows for the inclusion of baseline covariates.
  • Simultaneous confidence regions for the curve are computed, and the approach is implemented using available software.

Main Results:

  • The proposed pseudo-value regression method for multiple restriction times aligns well with standard regression models using a single time point.
  • The method effectively reproduces non-parametric results when no covariates are included.
  • Simulations and examples demonstrate the utility of the approach, particularly when adjusting for baseline covariates.

Conclusions:

  • The proposed model-based pseudo-value approach offers a flexible and implementable method for estimating RMST difference curves.
  • This method facilitates covariate adjustment and provides simultaneous confidence regions, enhancing the interpretation of treatment effects in survival analysis.
  • The approach complements existing methods and is valuable for studies requiring detailed analysis of time-dependent treatment effects.