Systematic review reveals lack of causal methodology applied to pooled longitudinal observational infectious disease studies - Hufstedler, Heather; Rahman, Sabahat; Danzer, Alexander M.; Goymann, Hannah; de Jong, Valentijn M.T.; Campbell, Harlan; Gustafson, Paul; Debray, Thomas P.A.; Jänisch, Thomas; Maxwell, Lauren; Matthay, Ellicott C.; Bärnighausen, Till (Journal of clinical epidemiology, 2022)
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.