TY - JOUR
T1 - Systematic Review Reveals Lack of Causal Methodology Applied to Pooled Longitudinal Observational Infectious Disease Studies
AU - Hufstedler, Heather
AU - Rahman, Sabahat
AU - Danzer, Alexander M.
AU - Goymann, Hannah
AU - de Jong, Valentijn M.T.
AU - Campbell, Harlan
AU - Gustafson, Paul
AU - Debray, Thomas P.A.
AU - Jaenisch, Thomas
AU - Maxwell, Lauren
AU - Matthay, Ellicott C.
AU - Bärnighausen, Till
N1 - Funding Information:
This work is supported by the ReCoDID study, which has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 825746 and the Canadian Institutes of Health Research, Institute of Genetics (CIHR-IG) under Grant Agreement N. 01886-000 .
Publisher Copyright:
© 2022 The Authors
PY - 2022/5
Y1 - 2022/5
N2 - OBJECTIVES: Among ID studies seeking to make causal inferences and pooling individual-level longitudinal data from multiple infectious disease cohorts, we sought to assess what methods are being used, how those methods are being reported, and whether these factors have changed over time.STUDY DESIGN AND SETTING: Systematic review of longitudinal observational infectious disease studies pooling individual-level patient data from 2+ studies published in English in 2009. 2014, or 2019. This systematic review protocol is registered with PROSPERO (CRD42020204104).RESULTS: Our search yielded 1,462 unique articles. Of these, 16 were included in the final review. Our analysis showed a lack of causal inference methods and of clear reporting on methods and the required assumptions.CONCLUSION: There are many approaches to causal inference which may help facilitate accurate inference in the presence of unmeasured and time-varying confounding. In observational ID studies leveraging pooled, longitudinal IPD, the absence of these causal inference methods and gaps in the reporting of key methodological considerations suggests there is ample opportunity to enhance the rigor and reporting of research in this field. Interdisciplinary collaborations between substantive and methodological experts would strengthen future work.
AB - OBJECTIVES: Among ID studies seeking to make causal inferences and pooling individual-level longitudinal data from multiple infectious disease cohorts, we sought to assess what methods are being used, how those methods are being reported, and whether these factors have changed over time.STUDY DESIGN AND SETTING: Systematic review of longitudinal observational infectious disease studies pooling individual-level patient data from 2+ studies published in English in 2009. 2014, or 2019. This systematic review protocol is registered with PROSPERO (CRD42020204104).RESULTS: Our search yielded 1,462 unique articles. Of these, 16 were included in the final review. Our analysis showed a lack of causal inference methods and of clear reporting on methods and the required assumptions.CONCLUSION: There are many approaches to causal inference which may help facilitate accurate inference in the presence of unmeasured and time-varying confounding. In observational ID studies leveraging pooled, longitudinal IPD, the absence of these causal inference methods and gaps in the reporting of key methodological considerations suggests there is ample opportunity to enhance the rigor and reporting of research in this field. Interdisciplinary collaborations between substantive and methodological experts would strengthen future work.
KW - Causal inference
KW - Individual participant data meta-analysis
KW - Infectious disease
KW - Methodological systematic review
KW - Pooled data
KW - Reporting
UR - http://www.scopus.com/inward/record.url?scp=85124211291&partnerID=8YFLogxK
U2 - 10.1016/j.jclinepi.2022.01.008
DO - 10.1016/j.jclinepi.2022.01.008
M3 - Review article
C2 - 35045316
SN - 0895-4356
VL - 145
SP - 29
EP - 38
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
ER -