An evaluation of exact matching and propensity score methods as applied in a comparative effectiveness study of inhaled corticosteroids in asthma

A. Burden; N. Roche; C. Miglio; E. V. Hillyer; D. S. Postma; R. M. Herings; J. A. Overbeek; J. M. Khalid; D. van Eickels; D. B. Price

doi:https://doi.org/10.2147/POR.S122563

An evaluation of exact matching and propensity score methods as applied in a comparative effectiveness study of inhaled corticosteroids in asthma

A. Burden, N. Roche, C. Miglio, E. V. Hillyer, D. S. Postma, R. M. Herings, J. A. Overbeek, J. M. Khalid, D. van Eickels, D. B. Price

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

BACKGROUND: Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre-post historical database study to investigate asthma-related outcomes by treatment. METHODS: We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of 10% for four variables in the exact-matched dataset and

Original language	English
Pages (from-to)	15-30
Number of pages	16
Journal	Pragmat Obs Res
Volume	8
DOIs	https://doi.org/10.2147/POR.S122563
Publication status	Published - 2017

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https://doi.org/10.2147/POR.S122563

https://www.ncbi.nlm.nih.gov/pubmed/28356782

Cite this

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title = "An evaluation of exact matching and propensity score methods as applied in a comparative effectiveness study of inhaled corticosteroids in asthma",

abstract = "BACKGROUND: Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre-post historical database study to investigate asthma-related outcomes by treatment. METHODS: We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of 10% for four variables in the exact-matched dataset and",

author = "A. Burden and N. Roche and C. Miglio and Hillyer, {E. V.} and Postma, {D. S.} and Herings, {R. M.} and Overbeek, {J. A.} and Khalid, {J. M.} and {van Eickels}, D. and Price, {D. B.}",

note = "Burden, Anne Roche, Nicolas Miglio, Cristiana Hillyer, Elizabeth V Postma, Dirkje S Herings, Ron Mc Overbeek, Jetty A Khalid, Javaria Mona van Eickels, Daniela Price, David B eng New Zealand Pragmat Obs Res. 2017 Mar 22;8:15-30. doi: 10.2147/POR.S122563. eCollection 2017.",

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T1 - An evaluation of exact matching and propensity score methods as applied in a comparative effectiveness study of inhaled corticosteroids in asthma

AU - Burden, A.

AU - Roche, N.

AU - Miglio, C.

AU - Hillyer, E. V.

AU - Postma, D. S.

AU - Herings, R. M.

AU - Overbeek, J. A.

AU - Khalid, J. M.

AU - van Eickels, D.

AU - Price, D. B.

N1 - Burden, Anne Roche, Nicolas Miglio, Cristiana Hillyer, Elizabeth V Postma, Dirkje S Herings, Ron Mc Overbeek, Jetty A Khalid, Javaria Mona van Eickels, Daniela Price, David B eng New Zealand Pragmat Obs Res. 2017 Mar 22;8:15-30. doi: 10.2147/POR.S122563. eCollection 2017.

PY - 2017

Y1 - 2017

N2 - BACKGROUND: Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre-post historical database study to investigate asthma-related outcomes by treatment. METHODS: We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of 10% for four variables in the exact-matched dataset and

AB - BACKGROUND: Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre-post historical database study to investigate asthma-related outcomes by treatment. METHODS: We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of 10% for four variables in the exact-matched dataset and

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