%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 }