Abstract

BackgroundWe previously developed an approach to address the impact of missing participant data in meta-analyses of continuous variables in trials that used the same measurement instrument. We extend this approach to meta-analyses including trials that use different instruments to measure the same construct. MethodsWe reviewed the available literature, conducted an iterative consultative process, and developed an approach involving a complete-case analysis complemented by sensitivity analyses that apply a series of increasingly stringent assumptions about results in patients with missing continuous outcome data. ResultsOur approach involves choosing the reference measurement instrument; converting scores from different instruments to the units of the reference instrument; developing four successively more stringent imputation strategies for addressing missing participant data; calculating a pooled mean difference for the complete-case analysis and imputation strategies; calculating the proportion of patients who experienced an important treatment effect; and judging the impact of the imputation strategies on the confidence in the estimate of effect. We applied our approach to an example systematic review of respiratory rehabilitation for chronic obstructive pulmonary disease. ConclusionsOur extended approach provides quantitative guidance for addressing missing participant data in systematic reviews of trials using different instruments to measure the same construct.

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