Abstract P343: Comparison of Two-stage and One-stage Meta-analyses: An Example of eGFR-Cardiovascular Mortality Association (for CKD-PC collaborators)
Purpose: Individual participant data (IPD) meta-analysis provides precise statistical estimates. Two approaches to meta-analyze IPD are currently used. The 1-stage approach fits a regression model to a pooled dataset including all studies. The 2-stage approach fits models in individual studies and meta-analyzes the estimates. However, their comparability has not been well described. We compare these methods for eGFR-cardiovascular mortality association in the CKD Prognosis Consortium (CKD-PC).
Methods: For the 1-stage method, we fitted a Cox stratified model, allowing each study to have a unique baseline hazard but assuming a common hazard ratio (HR) for eGFR across studies. For the 2-stage method, we first fitted a Cox model in each study, and then meta-analyzed HRs using a fixed-effect (assuming one true HR for eGFR across studies) and a random-effects (allowing some variance of true HR) model. eGFR was fitted as linear splines in all models.
Results: In a sample of 18 of 46 cohorts joining CKD-PC (191,276 participants and 8,732 cardiovascular deaths [CHD, stroke, or heart failure]), these methods gave nearly identical estimates except for the width of the confidence intervals (Figure). The 95% CIs were wider as methods made fewer assumptions - narrowest for 1-stage method, slightly wider for the fixed-effect 2-stage and wider for the random-effects 2-stage method.
Conclusion: The two-stage and one-stage meta-analyses provided nearly identical estimates for the eGFR-cardiovascular mortality relationship. The random-effects 2-stage method will provide conservative estimates with wider 95% CIs but this is necessary in the presence of heterogeneity.
- © 2012 by American Heart Association, Inc.