Statistical Methods for Modeling Time-Updated Exposures in Cohort Studies of Chronic Kidney Disease

Clinical journal of the American Society of Nephrology: CJASN

Dawei Xie¹ 

[1] *Department of Biostatistics, Epidemiology and Informatics, and..*Department of Biostatistics, Epidemiology and Informatics, and..†Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania..*Department of Biostatistics, Epidemiology and Informatics, and..*Department of Biostatistics, Epidemiology and Informatics, and..*Department of Biostatistics, Epidemiology and Informatics, and..*Department of Biostatistics, Epidemiology and Informatics, and..*Department of Biostatistics, Epidemiology and Informatics, and..*Department of Biostatistics, Epidemiology and Informatics, and..

关键词: Causal inference;    marginal structural models;    survival analysis;    time-varying Cox model;    time-dependent confounding;    inverse-probability treatment weight;    inverse-probability censoring weight;    blood pressure;    Cohort Studies;    Kidney Failure;    Chronic;    Probability;    Proportional Hazards Models;    Renal Insufficiency;    Chronic;    chronic kidney disease;   

DOI  :  10.2215/CJN.00650117

学科分类：泌尿医学

来源: American Society of Nephrology

【 摘 要 】

When estimating the effect of an exposure on a time-to-event type of outcome, one can focus on the baseline exposure or the time-updated exposures. Cox regression models can be used in both situations. When time-dependent confounding exists, the Cox model with time-updated covariates may produce biased effect estimates. Marginal structural models, estimated through inverse-probability weighting, were developed to appropriately adjust for time-dependent confounding. We review the concept of time-dependent confounding and illustrate the process of inverse-probability weighting. We fit a marginal structural model to estimate the effect of time-updated systolic BP on the time to renal events such as ESRD in the Chronic Renal Insufficiency Cohort. We compare the Cox regression model and the marginal structural model on several attributes (effects estimated, result interpretation, and assumptions) and give recommendations for when to use each method.

【 授权许可】

CC BY