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Methods for bounding the marginal survival distribution

J J Dignam1, L A Weissfeld, S J Anderson

  • 1Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pa 15261, USA.

Statistics in Medicine
|September 30, 1995
PubMed
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Estimating marginal survival distributions is challenging with competing risks. This study presents bounding methods to estimate non-identifiable survival probabilities, showing accurate results when dependence is correctly specified.

Area of Science:

  • Biostatistics
  • Survival Analysis
  • Epidemiology

Background:

  • Competing risks present challenges in uniquely determining marginal survival distributions.
  • Accurate estimation of event-specific survival is crucial for clinical decision-making.

Purpose of the Study:

  • To discuss and compare methods for estimating bounds on non-identifiable marginal survival distributions in competing risks scenarios.
  • To evaluate the performance of these bounding methods using simulated and real-world data.

Main Methods:

  • Utilized several statistical methods to estimate functions bounding the marginal survival distribution.
  • Employed simulation studies with bivariate survival distributions to assess method performance.
  • Applied the methods to data from a large breast cancer clinical trial.

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Main Results:

  • The discussed methods provide suitable estimates of marginal survival probability.
  • Accurate estimation is contingent upon correct specification of the dependence structure.
  • Simulated data analysis demonstrated the utility of the bounding functions.

Conclusions:

  • Bounding functions offer a viable approach for estimating marginal survival in the presence of competing risks.
  • Careful consideration of the dependence structure is essential for reliable results.
  • These methods are applicable to complex survival data, including clinical trial outcomes.