The relationship between osteoporotic fracture risk and a surrogate: Apparent discrepancies between analyses based on individual patient data and summary statistics

Authors

  • Ian Barton

    Corresponding author
    1. Department of Biometrics & Statistical Sciences, The Procter & Gamble Company, Egham, Surrey, UK
    • Department of Biometrics & Statistical Sciences, The Procter & Gamble Company, Rusham Park, Whitehall Lane, Egham, Surrey TW20 9NW, UK
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Abstract

There is debate within the osteoporosis research community about the relationship between the risk of osteoporotic fracture and the surrogate measures of fracture risk. Meta-regression analyses based on summary data have shown a linear relationship between fracture risk and surrogate measures, whereas analyses based on individual patient data (IPD) have shown a nonlinear relationship. We investigated the association between changes in a surrogate measure of fracture incidence, in this case a bone turnover marker for resorption assessed in the three risedronate phase III clinical programmes, and incident osteoporosis-related fracture risk using regression models based on patient-level and trial-level information. The relationship between osteoporosis-related fracture risk and changes in bone resorption was different when analysed on the basis of IPD than when analysed on the basis of a meta-analytic approach (i.e., meta-regression) using summary data (e.g., treatment effect based on treatment group estimates). This inconsistency in our findings was consistent with those in the published literature. Meta-regression based on summary statistics at the trial level is not expected to reflect causal relationships between a clinical outcome and surrogate measures. Analyses based on IPD make possible a more comprehensive analysis since all relevant data on a patient level are available. Copyright © 2004 John Wiley & Sons Ltd.

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