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04:57
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Time scale and adjusted survival curves for marginal structural cox models.
Daniel Westreich1, Stephen R Cole, Phyllis C Tien
1Department of Epidemiology, Universityof North Carolina, Chapel Hill, NorthCarolina, USA.
American Journal of Epidemiology
|February 9, 2010
Summary
Using time on treatment as a time scale in marginal structural models provides more precise estimates for highly active antiretroviral therapy
Area of Science:
- Biostatistics
- Epidemiology
- Survival Analysis
Background:
- Marginal structural models (MSMs) are used to estimate causal effects in longitudinal studies with time-varying treatments.
- Time on study is a common time scale, but may not accurately reflect treatment exposure duration.
- Accurate time scales are crucial for precise estimation of treatment effects.
Purpose of the Study:
- To evaluate time on treatment as an alternative time scale in MSMs.
- To develop a method for estimating Kaplan-Meier-type survival curves within MSMs.
- To assess the impact of time scale choice on the estimated effect of highly active antiretroviral therapy (HAART) on time to acquired immunodeficiency syndrome (AIDS) or death.
Main Methods:
- Employed marginal structural time-to-event models.
- Compared time on study versus time on treatment as the time scale.
- Estimated survival curves using a novel method for MSMs.
Main Results:
- The hazard ratio for AIDS or death comparing always vs. never HAART was 0.52 (95% CI: 0.35, 0.76) using time on study.
- The hazard ratio was 0.44 (95% CI: 0.32, 0.60) using time on treatment.
- Time on treatment yielded a hazard ratio further from the null and with greater precision.
Conclusions:
- The choice of time scale in time-to-event analyses significantly impacts association estimates and precision.
- Time on treatment is a more appropriate time scale than time on study for estimating the effects of time-varying treatments like HAART.
- The proposed methods enhance the utility of MSMs for causal inference in HIV research.
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