ArticlePaediatric and perinatal epidemiology2026
Assessing the Impact of Exposure Misclassification in Case-Control Studies of Self-Reported Medication Use.
Article in Paediatric and perinatal epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Recall bias in population-based case-control studies of ovarian cancer and genital talcum powder use: potential impact and quantitative bias analysis.BMC medical research methodology · 2026Article
- Exposome influences: a multi-omics perspective on the combined toxic effects of pharmaceuticals and personal care products in Alzheimer's disease.Frontiers in toxicology · 2026Review
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Authors and funding
7 authors.
Funding
Abstract
backgroundEmpirically evaluating the potential impact of recall bias on observed associations of prenatal medication exposure is crucial.
objectiveWe sought to assess the effects of exposure misclassification on previous studies of the use of nonsteroidal anti-inflammatory drugs (NSAIDs) in early pregnancy and increased risk of amniotic band syndrome (ABS).
methodsUsing data from the National Birth Defects Prevention Study (NBDPS) on births from 1997 to 2011, we included 189 mothers of infants with ABS and 11,829 mothers of infants without congenital anomalies. We identified external studies of medication use during pregnancy to obtain validity parameters for a probabilistic bias analysis to adjust for exposure misclassification. Due to uncertainty about the transportability of these parameters, we conducted multidimensional bias analyses to explore combinations of values on the results.
resultsWhen we assumed higher specificity in cases or higher sensitivity in controls, misclassification-adjusted estimates suggested confounding-adjusted estimates were attenuated. However, in a few instances, when we assumed greater sensitivity in the cases than the controls (and Sp ≥ 0.9), the misclassification-adjusted estimates suggested upward bias in the confounding-adjusted estimates.
conclusionsResults from our bias analysis highlighted that the magnitude of bias depended on the mechanism and the extent of misclassification. However, the parameters available from the validation studies were not directly applicable to our study. In the absence of reliable validation studies, considering mechanisms of bias and simulation studies to outline combinations of plausible scenarios to better inform conclusions on the effects of these medications on pregnancy outcomes remains important.
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