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  • Title: Misleading meta-analyses of observational studies may generate unjustified alarms: The case of medications for nausea and vomiting in pregnancy.
    Author: Biffi A, Rea F, Locatelli A, Cetin I, Filippelli A, Corrao G.
    Journal: Pharmacol Res; 2021 Jan; 163():105229. PubMed ID: 33031909.
    Abstract:
    OBJECTIVES: Because observational studies often use imperfect measurements, results are prone to misclassification errors. We used as a motivating example the possible teratogenic risks of antiemetic agents in pregnancy since a large observational study recently showed that first-trimester exposure to doxylamine-pyridoxine was associated with significantly increased risk of congenital malformations as a whole, as well as central nervous system defects, and previous observational studies did not show such associations. A meta-analysis on this issue was carried out with the aim to illustrate how differential exposure and outcome misclassifications may lead to uncertain conclusions. METHODS: Medline, searched to October 2019 for full text papers in English. Summary Odds Ratios (ORs) with confidence intervals (CIs) were calculated using random-effect models. Probabilistic sensitivity analyses were performed for evaluating the extension of differential misclassification required to account for the exposure-outcome association. RESULTS: Summary ORs were 1.02 (95 % CI, 0.92-1.15), 0.99 (0.82-1.19) and 1.25 (1.08-1.44) for overall congenital, cardiocirculatory, and central nervous system malformations respectively. By assuming exposure and outcome bias factor respectively of 0.95 (i.e., newborns with congenital defects had exposure specificity 5% lower than healthy newborns) and 1.12 (i.e., exposed newborns had outcome sensitivity 12 % higher than unexposed newborns), summary OR of central nervous system defects became 1.13 (95 % CI, 0.99-1.29) and 1.17 (95 % CI, 0.99-1.38). CONCLUSION: Observational investigations and meta-analyses of observational studies need cautious interpretations. Their susceptibility to several, often sneaky, sources of bias should be carefully evaluated.
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