Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Factors Influencing Background Incidence Rate Calculation: Systematic Empirical Evaluation Across an International Network of Observational Databases
by
Prieto-Alhambra, Daniel
, Shaoibi, Azza
, Li, Xintong
, Duarte-Salles, Talita
, Ostropolets, Anna
, Suchard, Marc A.
, Hripcsak, George
, Ryan, Patrick B.
, Rijnbeek, Peter R.
, Rao, Gowtham
, Sena, Anthony G.
, Makadia, Rupa
in
adverse events
/ Age
/ background rates
/ Biological products
/ Codes
/ Comorbidity
/ COVID-19
/ COVID-19 vaccines
/ Electronic health records
/ Genotype & phenotype
/ Immunization
/ incidence rates
/ Observational studies
/ Patients
/ Pharmacology
/ Pharmacovigilance
/ Product safety
/ SARS-CoV-2
/ vaccine
2022
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Factors Influencing Background Incidence Rate Calculation: Systematic Empirical Evaluation Across an International Network of Observational Databases
by
Prieto-Alhambra, Daniel
, Shaoibi, Azza
, Li, Xintong
, Duarte-Salles, Talita
, Ostropolets, Anna
, Suchard, Marc A.
, Hripcsak, George
, Ryan, Patrick B.
, Rijnbeek, Peter R.
, Rao, Gowtham
, Sena, Anthony G.
, Makadia, Rupa
in
adverse events
/ Age
/ background rates
/ Biological products
/ Codes
/ Comorbidity
/ COVID-19
/ COVID-19 vaccines
/ Electronic health records
/ Genotype & phenotype
/ Immunization
/ incidence rates
/ Observational studies
/ Patients
/ Pharmacology
/ Pharmacovigilance
/ Product safety
/ SARS-CoV-2
/ vaccine
2022
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Factors Influencing Background Incidence Rate Calculation: Systematic Empirical Evaluation Across an International Network of Observational Databases
by
Prieto-Alhambra, Daniel
, Shaoibi, Azza
, Li, Xintong
, Duarte-Salles, Talita
, Ostropolets, Anna
, Suchard, Marc A.
, Hripcsak, George
, Ryan, Patrick B.
, Rijnbeek, Peter R.
, Rao, Gowtham
, Sena, Anthony G.
, Makadia, Rupa
in
adverse events
/ Age
/ background rates
/ Biological products
/ Codes
/ Comorbidity
/ COVID-19
/ COVID-19 vaccines
/ Electronic health records
/ Genotype & phenotype
/ Immunization
/ incidence rates
/ Observational studies
/ Patients
/ Pharmacology
/ Pharmacovigilance
/ Product safety
/ SARS-CoV-2
/ vaccine
2022
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Factors Influencing Background Incidence Rate Calculation: Systematic Empirical Evaluation Across an International Network of Observational Databases
Journal Article
Factors Influencing Background Incidence Rate Calculation: Systematic Empirical Evaluation Across an International Network of Observational Databases
2022
Request Book From Autostore
and Choose the Collection Method
Overview
Objective: Background incidence rates are routinely used in safety studies to evaluate an association of an exposure and outcome. Systematic research on sensitivity of rates to the choice of the study parameters is lacking. Materials and Methods: We used 12 data sources to systematically examine the influence of age, race, sex, database, time-at-risk, season and year, prior observation and clean window on incidence rates using 15 adverse events of special interest for COVID-19 vaccines as an example. For binary comparisons we calculated incidence rate ratios and performed random-effect meta-analysis. Results: We observed a wide variation of background rates that goes well beyond age and database effects previously observed. While rates vary up to a factor of 1,000 across age groups, even after adjusting for age and sex, the study showed residual bias due to the other parameters. Rates were highly influenced by the choice of anchoring (e.g., health visit, vaccination, or arbitrary date) for the time-at-risk start . Anchoring on a healthcare encounter yielded higher incidence comparing to a random date, especially for short time-at-risk. Incidence rates were highly influenced by the choice of the database (varying by up to a factor of 100), clean window choice and time-at-risk duration, and less so by secular or seasonal trends. Conclusion: Comparing background to observed rates requires appropriate adjustment and careful time-at-risk start and duration choice. Results should be interpreted in the context of study parameter choices.
This website uses cookies to ensure you get the best experience on our website.