Journal article
Bias, precision and timeliness of historical (background) rate comparison methods for vaccine safety monitoring: an empirical multi-database analysis
- Abstract:
- Using real-world data and past vaccination data, we conducted a large-scale experiment to quantify bias, precision and timeliness of different study designs to estimate historical background (expected) compared to post-vaccination (observed) rates of safety events for several vaccines. We used negative (not causally related) and positive control outcomes. The latter were synthetically generated true safety signals with incident rate ratios ranging from 1.5 to 4. Observed vs. expected analysis using within-database historical background rates is a sensitive but unspecific method for the identification of potential vaccine safety signals. Despite good discrimination, most analyses showed a tendency to overestimate risks, with 20%-100% type 1 error, but low (0% to 20%) type 2 error in the large databases included in our study. Efforts to improve the comparability of background and post-vaccine rates, including age-sex adjustment and anchoring background rates around a visit, reduced type 1 error and improved precision but residual systematic error persisted. Additionally, empirical calibration dramatically reduced type 1 to nominal but came at the cost of increasing type 2 error.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.9MB, Terms of use)
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- Publisher copy:
- 10.3389/fphar.2021.773875
Authors
- Publisher:
- Public Library of Science
- Journal:
- Frontiers in Pharmacology More from this journal
- Volume:
- 12
- Article number:
- 773875
- Publication date:
- 2021-11-24
- Acceptance date:
- 2021-11-02
- DOI:
- EISSN:
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1663-9812
- Pmid:
-
34899334
- Language:
-
English
- Keywords:
- Pubs id:
-
1224885
- Local pid:
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pubs:1224885
- Deposit date:
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2022-05-20
- ARK identifier:
Terms of use
- Copyright holder:
- Li et al.
- Copyright date:
- 2021
- Rights statement:
- ©2021 Li, Lai, Ostropolets, Arshad, Tan, Casajust, Alshammari, Duarte-Salles, Minty, Areia, Pratt, Ryan, Hripcsak, Suchard, Schuemie and Prieto-Alhambra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
- Licence:
- CC Attribution (CC BY)
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