The multitime case-control design for time-varying exposures.
S. Suissa, S. Dell'Aniello, and C. Martinez. Epidemiology (Cambridge, Mass.), 21 (6):
876-83(November 2010)5909<m:linebreak></m:linebreak>GR: Canadian Institutes of Health Research/Canada; JID: 9009644; ppublish;<m:linebreak></m:linebreak>Dissenys híbrids.
DOI: 10.1097/EDE.0b013e3181f2f8e8
Abstract
BACKGROUND: The conventional approach to improve precision of the odds ratio in a case-control study is to increase the number of controls per case. With time-varying exposures, an alternative is to increase the number of observations per control. METHOD: We present the multitime case-control design, which uses multiple control person-moments of exposure within each control subject. The point and variance estimators of the odds ratio are corrected for within-subject correlation. We illustrate this approach using case-control data from studies of the effects of respiratory medications. RESULTS: Simulations show that, with uncorrelated exposures, it is possible to reduce the variance of the odds ratio by around 30% by increasing the number of control person-moments per subject. With correlated exposures, an accurate variance can be obtained by correcting for within-subject correlation. The corrected variance increases with increasing correlation, depending on the number of control person-moments. The first illustration shows that the rate ratio (RR) of cardiac death associated with β-agonist use, not estimable with 1 control per case (30 cases) and 1 control person-moment, was 4.2 (95% confidence interval = 0.4-49) with 12 control person-moments. The second example finds a rate ratio of acute myocardial infarction associated with antibiotics of 2.00 (1.16-3.44) with 1 control per case, which improves in precision with 10 control subjects per case (RR = 2.13 1.48-3.05) but also with 1 control per case and 10 control person-moments per control subject (1.99 1.36-2.90). CONCLUSION: When dealing with time-varying exposures, the multitime case-control design can increase the efficiency of conventional case-control studies without additional control subjects.
%0 Journal Article
%1 Suissa2010
%A Suissa, Samy
%A Dell'Aniello, Sophie
%A Martinez, Carlos
%D 2010
%J Epidemiology (Cambridge, Mass.)
%K Cardiac Case-ControlStudies Death Humans Models MyocardialInfarction MyocardialInfarction:mortality MyocardialInfarction:physiopathology OddsRatio ResearchDesign Sudden Theoretical
%N 6
%P 876-83
%R 10.1097/EDE.0b013e3181f2f8e8
%T The multitime case-control design for time-varying exposures.
%U http://www.ncbi.nlm.nih.gov/pubmed/20881601
%V 21
%X BACKGROUND: The conventional approach to improve precision of the odds ratio in a case-control study is to increase the number of controls per case. With time-varying exposures, an alternative is to increase the number of observations per control. METHOD: We present the multitime case-control design, which uses multiple control person-moments of exposure within each control subject. The point and variance estimators of the odds ratio are corrected for within-subject correlation. We illustrate this approach using case-control data from studies of the effects of respiratory medications. RESULTS: Simulations show that, with uncorrelated exposures, it is possible to reduce the variance of the odds ratio by around 30% by increasing the number of control person-moments per subject. With correlated exposures, an accurate variance can be obtained by correcting for within-subject correlation. The corrected variance increases with increasing correlation, depending on the number of control person-moments. The first illustration shows that the rate ratio (RR) of cardiac death associated with β-agonist use, not estimable with 1 control per case (30 cases) and 1 control person-moment, was 4.2 (95% confidence interval = 0.4-49) with 12 control person-moments. The second example finds a rate ratio of acute myocardial infarction associated with antibiotics of 2.00 (1.16-3.44) with 1 control per case, which improves in precision with 10 control subjects per case (RR = 2.13 1.48-3.05) but also with 1 control per case and 10 control person-moments per control subject (1.99 1.36-2.90). CONCLUSION: When dealing with time-varying exposures, the multitime case-control design can increase the efficiency of conventional case-control studies without additional control subjects.
%@ 1531-5487; 1044-3983
@article{Suissa2010,
abstract = {BACKGROUND: The conventional approach to improve precision of the odds ratio in a case-control study is to increase the number of controls per case. With time-varying exposures, an alternative is to increase the number of observations per control. METHOD: We present the multitime case-control design, which uses multiple control person-moments of exposure within each control subject. The point and variance estimators of the odds ratio are corrected for within-subject correlation. We illustrate this approach using case-control data from studies of the effects of respiratory medications. RESULTS: Simulations show that, with uncorrelated exposures, it is possible to reduce the variance of the odds ratio by around 30% by increasing the number of control person-moments per subject. With correlated exposures, an accurate variance can be obtained by correcting for within-subject correlation. The corrected variance increases with increasing correlation, depending on the number of control person-moments. The first illustration shows that the rate ratio (RR) of cardiac death associated with β-agonist use, not estimable with 1 control per case (30 cases) and 1 control person-moment, was 4.2 (95% confidence interval = 0.4-49) with 12 control person-moments. The second example finds a rate ratio of acute myocardial infarction associated with antibiotics of 2.00 (1.16-3.44) with 1 control per case, which improves in precision with 10 control subjects per case (RR = 2.13 [1.48-3.05]) but also with 1 control per case and 10 control person-moments per control subject (1.99 [1.36-2.90]). CONCLUSION: When dealing with time-varying exposures, the multitime case-control design can increase the efficiency of conventional case-control studies without additional control subjects.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Suissa, Samy and Dell'Aniello, Sophie and Martinez, Carlos},
biburl = {https://www.bibsonomy.org/bibtex/20281d113de2e49c91513fa06f6cf78ca/jepcastel},
city = {Department of Epidemiology and Biostatistics, McGill University, Montreal, Canada. samy.suissa@mcgill.ca},
doi = {10.1097/EDE.0b013e3181f2f8e8},
interhash = {6a73c8798868ef0242ef1f0c4616b794},
intrahash = {0281d113de2e49c91513fa06f6cf78ca},
isbn = {1531-5487; 1044-3983},
issn = {1531-5487},
journal = {Epidemiology (Cambridge, Mass.)},
keywords = {Cardiac Case-ControlStudies Death Humans Models MyocardialInfarction MyocardialInfarction:mortality MyocardialInfarction:physiopathology OddsRatio ResearchDesign Sudden Theoretical},
month = {11},
note = {5909<m:linebreak></m:linebreak>GR: Canadian Institutes of Health Research/Canada; JID: 9009644; ppublish;<m:linebreak></m:linebreak>Dissenys híbrids},
number = 6,
pages = {876-83},
pmid = {20881601},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {The multitime case-control design for time-varying exposures.},
url = {http://www.ncbi.nlm.nih.gov/pubmed/20881601},
volume = 21,
year = 2010
}