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Parametric g-formula implementations for causal survival analyses.

Lan Wen1, Jessica G Young2, James M Robins1,3

  • 1Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.

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Summary
This summary is machine-generated.

The g-formula estimates survival curves for sustained treatment strategies. New iterative methods are as efficient as existing noniterative ones, offering improved performance for causal inference.

Keywords:
causal inferencedeterministic dynamic regimesg-formularandom dynamic regimessurvival analysis

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Area of Science:

  • Causal inference
  • Survival analysis
  • Epidemiology

Background:

  • The g-formula is crucial for estimating survival curves under sustained treatment strategies.
  • Existing estimators include noniterative and iterative conditional expectation methods.
  • Comparative performance data for these estimators is limited.

Purpose of the Study:

  • To propose a novel iterative conditional expectation estimator for the g-formula.
  • To detail procedures for deterministic and random treatment strategies using the proposed estimator.
  • To evaluate the relative efficiency of noniterative and iterative conditional expectation estimators through simulations.

Main Methods:

  • Development of a new iterative conditional expectation estimator for the g-formula.
  • Simulation studies to compare the efficiency of proposed iterative, existing iterative, and noniterative estimators.
  • Application of estimators to "when to start" treatment questions using HIV-CAUSAL Collaboration data.

Main Results:

  • The proposed iterative conditional expectation estimator and the noniterative conditional expectation estimator demonstrate similar efficiency.
  • Both proposed and noniterative estimators are at least as efficient as the classical iterative conditional expectation estimator.
  • Performance is evaluated under conditions of no model misspecification or unmeasured confounding.

Conclusions:

  • The proposed iterative conditional expectation estimator is a viable and efficient method for g-formula estimation.
  • Noniterative and proposed iterative estimators offer comparable efficiency for survival curve estimation.
  • These methods are applicable to real-world causal inference problems, such as optimizing HIV treatment initiation.