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Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome

BACKGROUND: There has been little research on design of studies based on routinely collected data when the clinical endpoint of interest is not recorded, but can be inferred from a prescription. This often happens when exploring the effect of a drug on chronic diseases. Using the LifeLink claims dat...

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Autores principales: Lodi, Sara, Carpenter, James, Egger, Peter, Evans, Stephen
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3079701/
https://www.ncbi.nlm.nih.gov/pubmed/21457565
http://dx.doi.org/10.1186/1471-2288-11-36
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author Lodi, Sara
Carpenter, James
Egger, Peter
Evans, Stephen
author_facet Lodi, Sara
Carpenter, James
Egger, Peter
Evans, Stephen
author_sort Lodi, Sara
collection PubMed
description BACKGROUND: There has been little research on design of studies based on routinely collected data when the clinical endpoint of interest is not recorded, but can be inferred from a prescription. This often happens when exploring the effect of a drug on chronic diseases. Using the LifeLink claims database in studying the possible anti-inflammatory effects of statins in rheumatoid arthritis (RA), oral steroids (OS) were treated as surrogate of inflammatory flare-ups. We compared two cohort study designs, the first using time to event outcomes and the second using quantitative amount of the surrogate. METHODS: RA patients were extracted from the LifeLink database. In the first study, patients were split into two sub-cohorts based on whether they were using OS within a specified time window of the RA index date (first record of RA). Using Cox models we evaluated the association between time-varying exposure to statins and (i) initiation of OS therapy in the non-users of OS at RA index date and (ii) cessation of OS therapy in the users of OS at RA index date. In the second study, we matched new statin users to non users on age and sex. Zero inflated negative binomial models were used to contrast the number of days' prescriptions of OS in the year following date of statin initiation for the two exposure groups. RESULTS: In the unmatched study, the statin exposure hazard ratio (HR) of initiating OS in the 31451 non-users of OS at RA index date was 0.96(95% CI 0.9,1.1) and the statin exposure HR of cessation of OS therapy in the 6026 users of OS therapy at RA index date was 0.95 (0.87,1.05). In the matched cohort of 6288 RA patients the statin exposure rate ratio for duration on OS therapy was 0.88(0.76,1.02). There was digit preference for outcomes in multiples of 7 and 30 days. CONCLUSIONS: The 'time to event' study design was preferable because it better exploits information on all available patients and provides a degree of robustness toward confounding. We found no convincing evidence that statins reduce inflammation in RA patients.
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spelling pubmed-30797012011-04-20 Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome Lodi, Sara Carpenter, James Egger, Peter Evans, Stephen BMC Med Res Methodol Research Article BACKGROUND: There has been little research on design of studies based on routinely collected data when the clinical endpoint of interest is not recorded, but can be inferred from a prescription. This often happens when exploring the effect of a drug on chronic diseases. Using the LifeLink claims database in studying the possible anti-inflammatory effects of statins in rheumatoid arthritis (RA), oral steroids (OS) were treated as surrogate of inflammatory flare-ups. We compared two cohort study designs, the first using time to event outcomes and the second using quantitative amount of the surrogate. METHODS: RA patients were extracted from the LifeLink database. In the first study, patients were split into two sub-cohorts based on whether they were using OS within a specified time window of the RA index date (first record of RA). Using Cox models we evaluated the association between time-varying exposure to statins and (i) initiation of OS therapy in the non-users of OS at RA index date and (ii) cessation of OS therapy in the users of OS at RA index date. In the second study, we matched new statin users to non users on age and sex. Zero inflated negative binomial models were used to contrast the number of days' prescriptions of OS in the year following date of statin initiation for the two exposure groups. RESULTS: In the unmatched study, the statin exposure hazard ratio (HR) of initiating OS in the 31451 non-users of OS at RA index date was 0.96(95% CI 0.9,1.1) and the statin exposure HR of cessation of OS therapy in the 6026 users of OS therapy at RA index date was 0.95 (0.87,1.05). In the matched cohort of 6288 RA patients the statin exposure rate ratio for duration on OS therapy was 0.88(0.76,1.02). There was digit preference for outcomes in multiples of 7 and 30 days. CONCLUSIONS: The 'time to event' study design was preferable because it better exploits information on all available patients and provides a degree of robustness toward confounding. We found no convincing evidence that statins reduce inflammation in RA patients. BioMed Central 2011-04-01 /pmc/articles/PMC3079701/ /pubmed/21457565 http://dx.doi.org/10.1186/1471-2288-11-36 Text en Copyright ©2011 Lodi et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lodi, Sara
Carpenter, James
Egger, Peter
Evans, Stephen
Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome
title Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome
title_full Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome
title_fullStr Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome
title_full_unstemmed Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome
title_short Design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome
title_sort design of cohort studies in chronic diseases using routinely collected databases when a prescription is used as surrogate outcome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3079701/
https://www.ncbi.nlm.nih.gov/pubmed/21457565
http://dx.doi.org/10.1186/1471-2288-11-36
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