Adjusting for confounding by indication in observational studies: a case study in traumatic brain injury
Received 18 October 2017
Accepted for publication 26 February 2018
Published 18 July 2018 Volume 2018:10 Pages 841—852
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Ms Justinn Cochran
Peer reviewer comments 4
Editor who approved publication: Professor Vera Ehrenstein
Maryse C Cnossen,1 Thomas A van Essen,2,3 Iris E Ceyisakar,1 Suzanne Polinder,1 Teuntje M Andriessen,4 Joukje van der Naalt,5 Iain Haitsma,6 Janneke Horn,7 Gaby Franschman,8 Pieter E Vos,9 Wilco C Peul,2,3 David K Menon,10 Andrew IR Maas,11 Ewout W Steyerberg,1,12 Hester F Lingsma1
1Center for Medical Decision Making, Department of Public Health, Erasmus Medical Center Rotterdam, Rotterdam, the Netherlands; 2Neurosurgical Cooperative Holland, Department of Neurosurgery, Leiden University Medical Center, Leiden, the Netherlands; 3Department of Neurosurgery, Haaglanden Medical Center, The Hague, the Netherlands; 4Department of Psychology, RIVAS Healthcare Group, Gorinchem, the Netherlands; 5Department of Neurology, University Medical Center Groningen, Groningen, the Netherlands; 6Department of Neurosurgery, Erasmus Medical Center Rotterdam, Rotterdam, the Netherlands; 7Department of Intensive Care Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands; 8Department of Anesthesiology, VU University Medical Center Amsterdam, Amsterdam, the Netherlands; 9Department of Neurology, Slingeland Hospital, Doetinchem, the Netherlands; 10Division of Anaesthesia, University of Cambridge/Addenbrooke’s Hospital, Cambridge, UK; 11Department of Neurosurgery, Antwerp University Hospital and University of Antwerp, Edegem, Belgium; 12Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
Introduction: Observational studies of interventions are at risk for confounding by indication. The objective of the current study was to define the circumstances for the validity of methods to adjust for confounding by indication in observational studies.
Patients and methods: We performed post hoc analyses of data prospectively collected from three European and North American traumatic brain injury studies including 1,725 patients. The effects of three interventions (intracranial pressure [ICP] monitoring, intracranial operation and primary referral) were estimated in a proportional odds regression model with the Glasgow Outcome Scale as ordinal outcome variable. Three analytical methods were compared: classical covariate adjustment, propensity score matching and instrumental variable (IV) analysis in which the percentage exposed to an intervention in each hospital was added as an independent variable, together with a random intercept for each hospital. In addition, a simulation study was performed in which the effect of a hypothetical beneficial intervention (OR 1.65) was simulated for scenarios with and without unmeasured confounders.
Results: For all three interventions, covariate adjustment and propensity score matching resulted in negative estimates of the treatment effect (OR ranging from 0.80 to 0.92), whereas the IV approach indicated that both ICP monitoring and intracranial operation might be beneficial (OR per 10% change 1.17, 95% CI 1.01–1.42 and 1.42, 95% CI 0.95–1.97). In our simulation study, we found that covariate adjustment and propensity score matching resulted in an invalid estimate of the treatment effect in case of unmeasured confounders (OR ranging from 0.90 to 1.03). The IV approach provided an estimate in the similar direction as the simulated effect (OR per 10% change 1.04–1.05) but was statistically inefficient.
Conclusion: The effect estimation of interventions in observational studies strongly depends on the analytical method used. When unobserved confounding and practice variation are expected in observational multicenter studies, IV analysis should be considered.
Keywords: confounding, observational studies, traumatic brain injury, instrumental variable analysis, comparative effectiveness research
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