A systematic review of quantitative bias analysis applied to epidemiological research

Julie M. Petersen, Lynsie R. Ranker, Ruby Barnard-Mayers, Richard F. Maclehose, Matthew P. Fox

Research output: Contribution to journalReview articlepeer-review

10 Scopus citations


Background: Quantitative bias analysis (QBA) measures study errors in terms of direction, magnitude and uncertainty. This systematic review aimed to describe how QBA has been applied in epidemiological research in 2006-19. Methods: We searched PubMed for English peer-reviewed studies applying QBA to real-data applications. We also included studies citing selected sources or which were identified in a previous QBA review in pharmacoepidemiology. For each study, we extracted the rationale, methodology, bias-adjusted results and interpretation and assessed factors associated with reproducibility. Results: Of the 238 studies, the majority were embedded within papers whose main inferences were drawn from conventional approaches as secondary (sensitivity) analyses to quantity-specific biases (52%) or to assess the extent of bias required to shift the point estimate to the null (25%); 10% were standalone papers. The most common approach was probabilistic (57%). Misclassification was modelled in 57%, uncontrolled confounder(s) in 40% and selection bias in 17%. Most did not consider multiple biases or correlations between errors. When specified, bias parameters came from the literature (48%) more often than internal validation studies (29%). The majority (60%) of analyses resulted in >10% change from the conventional point estimate; however, most investigators (63%) did not alter their original interpretation. Degree of reproducibility related to inclusion of code, formulas, sensitivity analyses and supplementary materials, as well as the QBA rationale. Conclusions: QBA applications were rare though increased over time. Future investigators should reference good practices and include details to promote transparency and to serve as a reference for other researchers.

Original languageEnglish (US)
Pages (from-to)1708-1730
Number of pages23
JournalInternational journal of epidemiology
Issue number5
StatePublished - Oct 1 2021

Bibliographical note

Funding Information:
The authors wish to thank Dr. Mouna Rimani for her valuable assistance with the histopathology photographs.

Publisher Copyright:
© 2021 The Author(s) 2021; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.


  • Epidemiologic bias
  • Epidemiologic study characteristics
  • Quantitative bias analysis
  • Quantitative evaluation
  • Systematic bias
  • Uncertainty

PubMed: MeSH publication types

  • Journal Article
  • Systematic Review


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