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Use of signal detection methods to identify associations between prenatal medication exposure and subsequent
Hannah Johnson1,2, Sarah Hjorth2, Joan Morris1
1Population Health Research Institute, St George's University of London, London, UK.
Background:
Childhood cancer is an important contributor to childhood mortality in high-income countries. Information on associations between childhood cancer and in-utero exposure is absent or limited for most medications. Signal detection methods identify medications where research should be focused but have not been applied to datasets containing prenatal medication exposures and childhood cancers.
Research Design And Methods:
The aim of this study was to apply and evaluate four signal detection methods - odds ratios (OR), the information component (IC), sequential probability ratio testing (SPRT), and Bayesian hierarchical models (BHM) - for identification of associations between medications dispensed during pregnancy and subsequent, incident diagnosis of childhood cancer <10 years, using linked Nordic registry data. Signal detection results were compared to propensity score adjusted odds ratios from generalized linear models.
Results:
Analysis was performed for 117 medication-cancer pairs with 5 or more observations. The OR had the greatest sensitivity (0.75). The IC had a greater specificity (0.98) than the OR (0.95).
Conclusions:
The IC may be the most appropriate method for identifying signals within this type of data. Reported signals should not be considered sufficient evidence of causal association and must be followed-up by tailored investigations that consider confounding by indication.
Insights
This study evaluated four methods for detecting associations between prenatal medication exposure and childhood cancer. The Information Component (IC) showed the highest specificity, suggesting it is most suitable for this research area.
Area of Science:
- Pharmacoepidemiology
- Pediatric Oncology
- Biostatistics
Background:
- Childhood cancer is a significant cause of mortality in high-income nations.
- Limited data exists on the link between in-utero medication exposure and childhood cancer.
- Signal detection methods can pinpoint medications needing further research but haven't been applied to prenatal exposure and cancer data.
Purpose of the Study:
- To apply and assess four signal detection methods: odds ratios (OR), Information Component (IC), Sequential Probability Ratio Testing (SPRT), and Bayesian Hierarchical Models (BHM).
- To identify potential associations between medications used during pregnancy and childhood cancer diagnoses within 10 years.
- To compare signal detection results with propensity score-adjusted odds ratios from generalized linear models.
Main Methods:
- Utilized linked Nordic registry data for analysis.
- Evaluated 117 medication-cancer pairs with at least 5 observations.
- Employed four distinct signal detection methodologies.
Main Results:
- The Odds Ratio (OR) demonstrated the highest sensitivity at 0.75.
- The Information Component (IC) exhibited superior specificity (0.98) compared to the OR (0.95).
Conclusions:
- The Information Component (IC) appears to be the most appropriate method for signal detection in this context.
- Identified signals require further investigation to confirm causal associations, considering potential confounding factors like indication.
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