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Using fractional polynomials to model the effect of cumulative duration of exposure on outcomes: applications to cohort and nested case-control designs.

Austin PC, Park-Wyllie LY, Juurlink DN - Pharmacoepidemiol Drug Saf (2014)

Bottom Line: Using 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.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.Fractional polynomials allow one to model the relationship between cumulative duration of medication use and adverse outcomes.

View Article: PubMed Central - PubMed

Affiliation: Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Institute of Health Management, Policy and Evaluation, University of Toronto, Toronto, Ontario, Canada; Schulich Heart Research Program, Sunnybrook Research Institute, Toronto, Canada.

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Deviances of all 44 fractional polynomial models
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fig02: Deviances of all 44 fractional polynomial models

Mentions: The distributions of the deviance across the 8 FP1 models and the 36 FP2 models, along with that of the model, are depicted in the left panel of Figure 2. The deviance of the best-fitting FP2 model, the best-fitting FP1 model, the linear model and the model is reported in Table 1, along with the results of the test comparing different FP models. Using the RA2 selection algorithm, the FP2 transformation with P = (1, 1) was selected as the best-fitting FP transformation. The FP model that best described the relationship between cumulative duration of use of amiodarone and the log hazard of thyroid dysfunction was of the form β1x + β2x log(x), where x denotes cumulative use of amiodarone. The point estimates and associated 95% confidence intervals for β1 and β2 were 0.0216 (0.0176, 0.0256) and −0.0027 (−0.0032, −0.0022), respectively. Four other FP2 ((0.5, 2), (0.5, 1), (0.5, 3), and (0.5, 0.5)) transformations resulted in models with deviance within four of that of the best-fitting FP2 transformation. None of the FP1 transformations resulted in models whose deviance was within four of that of the best-fitting FP2 transformation.


Using fractional polynomials to model the effect of cumulative duration of exposure on outcomes: applications to cohort and nested case-control designs.

Austin PC, Park-Wyllie LY, Juurlink DN - Pharmacoepidemiol Drug Saf (2014)

Deviances of all 44 fractional polynomial models
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230473&req=5

fig02: Deviances of all 44 fractional polynomial models
Mentions: The distributions of the deviance across the 8 FP1 models and the 36 FP2 models, along with that of the model, are depicted in the left panel of Figure 2. The deviance of the best-fitting FP2 model, the best-fitting FP1 model, the linear model and the model is reported in Table 1, along with the results of the test comparing different FP models. Using the RA2 selection algorithm, the FP2 transformation with P = (1, 1) was selected as the best-fitting FP transformation. The FP model that best described the relationship between cumulative duration of use of amiodarone and the log hazard of thyroid dysfunction was of the form β1x + β2x log(x), where x denotes cumulative use of amiodarone. The point estimates and associated 95% confidence intervals for β1 and β2 were 0.0216 (0.0176, 0.0256) and −0.0027 (−0.0032, −0.0022), respectively. Four other FP2 ((0.5, 2), (0.5, 1), (0.5, 3), and (0.5, 0.5)) transformations resulted in models with deviance within four of that of the best-fitting FP2 transformation. None of the FP1 transformations resulted in models whose deviance was within four of that of the best-fitting FP2 transformation.

Bottom Line: Using 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.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.Fractional polynomials allow one to model the relationship between cumulative duration of medication use and adverse outcomes.

View Article: PubMed Central - PubMed

Affiliation: Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Institute of Health Management, Policy and Evaluation, University of Toronto, Toronto, Ontario, Canada; Schulich Heart Research Program, Sunnybrook Research Institute, Toronto, Canada.

Show MeSH
Related in: MedlinePlus