ArticlePharmacoepidemiology and drug safety2014
Using fractional polynomials to model the effect of cumulative duration of exposure on outcomes: applications to cohort and nested case-control designs.
Article in Pharmacoepidemiology and drug safety, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Optimal designs for health risk assessments using fractional polynomial models.Stochastic environmental research and risk assessment : research journal · 2022Article
- Characterizing thrombus with multiple red blood cell compositions by optical coherence tomography attenuation coefficient.Journal of biophotonics · 2021Article
- Bayesian splines versus fractional polynomials in network meta-analysis.BMC medical research methodology · 2020Article
- A review of the use of time-varying covariates in the Fine-Gray subdistribution hazard competing risk regression model.Statistics in medicine · 2020Review
- Electronic medical records can be used to emulate target trials of sustained treatment strategies.Journal of clinical epidemiology · 2018Observational
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
purposeDetermining the nature of the relationship between cumulative duration of exposure to an agent and the hazard of an adverse outcome is an important issue in environmental and occupational epidemiology, public health and clinical medicine. The Cox proportional hazards regression model can incorporate time-dependent covariates. An important class of continuous time-dependent covariates is that denoting cumulative duration of exposure.
methodsWe used fractional polynomial methods to describe the association between cumulative duration of exposure and adverse outcomes. We applied these methods in a cohort study to examine the relationship between cumulative duration of use of the antiarrhythmic drug amiodarone and the risk of thyroid dysfunction. We also used these methods with a conditional logistic regression model in a nested case-control study to examine the relationship between cumulative duration of use of bisphosphonate medication and the risk of atypical femur fracture.
resultsUsing a cohort design and a Cox proportional hazards model, we found a non-linear relationship between cumulative duration of use of the antiarrhythmic drug amiodarone and the risk of thyroid dysfunction. The risk initially increased rapidly with increasing cumulative use. However, as cumulative duration of use increased, the rate of increase in risk attenuated and eventually levelled off. Using a nested case-control design and a conditional logistic regression model, we found evidence of a linear relationship between duration of use of bisphosphonate medication and risk of atypical femur fractures.
conclusionsFractional polynomials allow one to model the relationship between cumulative duration of medication use and adverse outcomes.
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