| アブストラクト | BACKGROUND: The use of decongestants during the second or third trimesters of pregnancy has been associated with a decreased risk of preterm delivery in two observational studies. This effect may have been subject to immortal time bias, a bias arising from the improper classification of exposure during follow-up. We illustrate this bias by repeating the studies using a different data source. METHODS: The United Kingdom Hospital Episodes Statistics and the Clinical Practice Research Datalink databases were linked to identify all live singleton pregnancies among women aged 15 to 45 years between 1997 and 2012. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals of preterm delivery (before 37 weeks of gestation) by considering the use of decongestants during the third trimester as a time-fixed (biased analysis which misclassifies unexposed person-time as exposed person-time) and time-varying exposure (unbiased analysis with proper classification of unexposed person-time). All models were adjusted for maternal age, smoking status, maternal diabetes, maternal hypertension, preeclampsia, and parity. RESULTS: Of the 195,582 singleton deliveries, 10,248 (5.2%) were born preterm. In the time-fixed analysis, the HR of preterm delivery for the use of decongestants was below the null and suggestive of a 46% decreased risk (adjusted HR = 0.54; 95% confidence interval, 0.24-1.20). In contrast, the HR was closer to null (adjusted HR = 0.93 95% confidence interval, 0.42-2.06) when the use of decongestants was treated as a time-varying variable. CONCLUSION: Studies of drug safety in pregnancy should use the appropriate statistical techniques to avoid immortal time bias, particularly when the exposure occurs at later stages of pregnancy. |
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| ジャーナル名 | Birth defects research. Part A, Clinical and molecular teratology |
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| 投稿日 | 2014/07/06 |
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| 投稿者 | Matok, Ilan; Azoulay, Laurent; Yin, Hui; Suissa, Samy |
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| 組織名 | Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital,;Montreal; Department of Epidemiology, Biostatistics and Occupational Health;McGill University, Montreal. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/24985740/ |
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