Fitting Marginal Structural and G-Estimation Models Under Complex Treatment Patterns: Investigating the Association Between De Novo Vitamin D Supplement Use After Breast Cancer Diagnosis and All-Cause Mortality Using Linked Pharmacy Claim and Registry Data.
Am J Epidemiol
; 189(3): 224-234, 2020 03 02.
Article
en En
| MEDLINE
| ID: mdl-31673702
ABSTRACT
Studies have shown that accounting for time-varying confounding through time-dependent Cox proportional hazards models may provide biased estimates of the causal effect of treatment when the confounder is also a mediator. We explore 2 alternative approaches to addressing this problem while examining the association between vitamin D supplementation initiated after breast cancer diagnosis and all-cause mortality. Women aged 50-80 years were identified in the National Cancer Registry Ireland (n = 5,417) between 2001 and 2011. Vitamin D use was identified from linked prescription data (n = 2,570). We sought to account for the time-varying nature of vitamin D use and time-varying confounding by bisphosphonate use using 1) marginal structural models (MSMs) and 2) G-estimation of structural nested accelerated failure-time models (SNAFTMs). Using standard adjusted Cox proportional hazards models, we found a reduction in all-cause mortality in de novo vitamin D users compared with nonusers (hazard ratio (HR) = 0.84, 95% confidence interval (CI) 0.73, 0.99). Additional adjustment for vitamin D and bisphosphonate use in the previous month reduced the hazard ratio (HR = 0.45, 95% CI 0.33, 0.63). Results derived from MSMs (HR = 0.44, 95% CI 0.32, 0.61) and SNAFTMs (HR = 0.45, 95% CI 0.34, 0.52) were similar. Utilizing MSMs and SNAFTMs to account for time-varying bisphosphonate use did not alter conclusions in this example.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Vitamina D
/
Neoplasias de la Mama
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Sistema de Registros
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Modelos Estadísticos
/
Conservadores de la Densidad Ósea
Tipo de estudio:
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Aged
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Female
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Humans
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Middle aged
País como asunto:
Europa
Idioma:
En
Año:
2020
Tipo del documento:
Article