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Review Article| Volume 60, ISSUE 3, P228-240, March 2007

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Imputing variance estimates do not alter the conclusions of a meta-analysis with continuous outcomes: a case study of changes in renal function after living kidney donation

  • H. Thiessen Philbrook
    Correspondence
    Corresponding author. London Kidney Clinical Research Unit, Room ELL-101, Westminster Tower, London Health Sciences Centre, 800 Commissioners Road East, London, ON N6A 4G5, Canada. Tel.: 519-685-8502; fax: 519-685-8072.
    Affiliations
    Division of Nephrology, University of Western Ontario, London, Canada
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  • N. Barrowman
    Affiliations
    Chalmers Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
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  • A.X. Garg
    Affiliations
    Division of Nephrology, University of Western Ontario, London, Canada

    Department of Epidemiology and Biostatistics, University of Western Ontario, London, Canada

    Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Canada
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      Abstract

      Objective

      To assess how different imputation methods used to account for missing variance data in primary studies influence tests of heterogeneity and pooled results from a meta-analysis with continuous outcomes.

      Study Design and Setting

      Point and variance estimates for changes in serum creatinine, glomerular filtration rate, systolic blood pressure, and diastolic blood pressure were variably reported among 48 primary longitudinal studies of living kidney donors (71%–78% of point estimates were reported, 8%–13% of variance data were reported). We compared the results of meta-analysis, which either were restricted to available data or used four methods to impute missing variance data. These methods used reported P-values, reported nonparametric summaries, results from other similar studies using multiple imputation, or results from estimated correlation coefficients.

      Results

      Significant heterogeneity was present in all four outcomes regardless of the imputation methods applied. The random effects point estimates and 95% confidence intervals varied little across imputation methods, and the differences were not clinically significant.

      Conclusions

      Different methods to impute the variance data in the primary studies did not alter the conclusions from this meta-analysis of continuous outcomes. Such reproducibility increases confidence in the results. However, as with most meta-analyses, there was no gold standard of truth, and results must be interpreted judiciously. The generalization of these findings to other meta-analyses, which differ in outcomes, missing data, or between-study heterogeneity, requires further consideration.

      Keywords

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