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Are Randomized Trials Better? Comparison of Baseline Covariate Balance of a Propensity Score-Balanced Lumbar Spine
Greg Maislin1, Brendan T Keenan1, Todd F Alamin2
1Biomedical Statistical Consulting LLC®, Philadelphia, PA, USA.
None:
Study DesignProspective Observational Propensity Score.ObjectivesRandomization may lead to bias when the treatment is unblinded and there is a strong patient preference for treatment arms (such as in spinal device trials). This report describes the rationale and methods utilized to develop a propensity score (PS) model for an investigational device exemption (IDE) trial (NCT03115983) to evaluate decompression and stabilization with an investigational dynamic sagittal tether (DST) vs decompression and Transforaminal Lumbar Interbody Fusion (TLIF) for patients with symptomatic grade I lumbar degenerative spondylolisthesis with spinal stenosis.MethodsTwenty-five baseline covariates were selected for their expected relationship to patient outcomes or enrollment bias. Subclassification by PS quintiles was used to design a sample of investigational DST patients and TLIF controls with excellent covariate balance in which to estimate causal treatment effects. Additionally, balance in PS covariates was compared to available matching covariates from seven randomized spine IDE trials.ResultsThe PS subclassification design resulted in excellent balance across baseline covariates, as evidenced by small standardized mean differences and no significant between group differences after accounting for the PS design (all P ≥ 0.768). Differences in SMDs among covariates of randomized spine IDE trials were not significant (P = 0.396).ConclusionThe PS subclassification design achieved excellent covariate balance between DST investigational and TLIF control participants. This PS designed sample shows covariate balance similar to that observed in published studies in which patients were randomized to investigational or control arms.Clinical trial registered with https://www.clinicaltrials.gov (NCT03115983).
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