Comparing two counterfactual-outcome approaches in causal mediation analysis of a multicategorical exposure: An application for the estimation of the effect of maternal intake of inhaled corticosteroids doses on birthweight

2020 ◽  
Vol 29 (10) ◽  
pp. 2767-2782
Author(s):  
Mariia Samoilenko ◽  
Nadia Arrouf ◽  
Lucie Blais ◽  
Geneviève Lefebvre

Although medical research frequently involves an exposure variable with three or more discrete levels, detailed presentations of mediation techniques for dealing with multicategorical (multilevel) exposures are sparse. In this paper, we study two causal mediation approaches applicable to such a type of exposure for continuous mediator and outcome: the closed-form regression-based approach of Valeri and VanderWeele, and the marginal structural model-based approach of Lange, Vansteelandt, and Bekaert. While the consideration of multicategorical exposures is found explicitly addressed in the literature for the latter approach, this is, to our knowledge, not yet the case for the former. We first illustrate the application of the two aforementioned approaches to assess the dose–response relationship between maternal intake of inhaled corticosteroids and birthweight, where this relationship is potentially mediated by gestational age. More specifically, we provide a precise roadmap for the application of the regression-based approach and of the marginal structural model-based approach on our cohort of pregnancies. Expressions for the natural direct and indirect effects associated with our categorical exposure are provided and, for the regression-based approach, analytic formulas for standard error calculation using the delta method are presented for these effects. Second, a simulation study which mimics our data is presented to add to current knowledge on these causal mediation techniques. Results from this study highlight the relevance to assess robustness of mediation results obtained from multicategorical exposures, most notably for the least prevalent of exposure categories.

Author(s):  
Marco Doretti ◽  
Martina Raggi ◽  
Elena Stanghellini

AbstractWith reference to causal mediation analysis, a parametric expression for natural direct and indirect effects is derived for the setting of a binary outcome with a binary mediator, both modelled via a logistic regression. The proposed effect decomposition operates on the odds ratio scale and does not require the outcome to be rare. It generalizes the existing ones, allowing for interactions between both the exposure and the mediator and the confounding covariates. The derived parametric formulae are flexible, in that they readily adapt to the two different natural effect decompositions defined in the mediation literature. In parallel with results derived under the rare outcome assumption, they also outline the relationship between the causal effects and the correspondent pathway-specific logistic regression parameters, isolating the controlled direct effect in the natural direct effect expressions. Formulae for standard errors, obtained via the delta method, are also given. An empirical application to data coming from a microfinance experiment performed in Bosnia and Herzegovina is illustrated.


2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Asma Bahamyirou ◽  
Mireille E. Schnitzer ◽  
Edward H. Kennedy ◽  
Lucie Blais ◽  
Yi Yang

Abstract Effect modification occurs when the effect of a treatment on an outcome differsaccording to the level of some pre-treatment variable (the effect modifier). Assessing an effect modifier is not a straight-forward task even for a subject matter expert. In this paper, we propose a two-stageprocedure to automatically selecteffect modifying variables in a Marginal Structural Model (MSM) with a single time point exposure based on the two nuisance quantities (the conditionaloutcome expectation and propensity score). We highlight the performance of our proposal in a simulation study. Finally, to illustrate tractability of our proposed methods, we apply them to analyze a set of pregnancy data. We estimate the conditional expected difference in the counterfactual birth weight if all women were exposed to inhaled corticosteroids during pregnancy versus the counterfactual birthweight if all women were not, using data from asthma medications during pregnancy.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eun-San Kim ◽  
Chang-yup Kim

AbstractContinuity of care is a core dimension of high-quality care in the management of disease. The purpose of this study was to investigate the association between continuity of care and lumbar surgery in patients with moderate disc herniation. The Korean National Sample Cohort was used. The target population consisted of patients who have had disc herniation more than 6 months and didn’t get surgery and red flag signs within 6 months from onset. The population was enrolled from 2004 to 2013. The Bice-Boxerman Continuity of Care was used in measuring continuity of care. The marginal structural model with time dependent survival analysis was used. In total, 29,061 patients were enrolled in the cohort. High level of continuity of care was associated with a lower risk of lumbar surgery (HR, 0.27; 95% CI, 0.20–0.27). When the index was calculated only with outpatient visits to primary care with related specialty, the HR was 0.49 (95% CI: 0.43–0.57). In exploratory analysis, patients with lumbar stenosis and spondylolisthesis had higher risk of having a low level of continuity of care. These results indicate that continuity of care is associated with lower rates of lumbar surgery in patients with moderate disc herniation.


Sign in / Sign up

Export Citation Format

Share Document