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Published on: November 8, 2013
Addressing continuous data measured with different instruments for participants excluded from trial analysis: a guide
Shanil Ebrahim1, Bradley C Johnston2, Elie A Akl3
1Department of Clinical Epidemiology and Biostatistics, McMaster University, 1200 Main St. West, Hamilton, Ontario, Canada, L8S 4K1; Department of Anesthesia, McMaster University, 1200 Main St. West, Hamilton, Ontario, Canada, L8S 4K1; Stanford Prevention Research Center, Department of Medicine, Stanford University, 1265 Welch Road, Stanford, California, USA, 94305; Department of Anesthesia and Pain Medicine, The Hospital for Sick Children, 555 University Ave, Toronto, Ontario, Canada, M5G 1X8.
Background:
We 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.
Methods:
We 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.
Results:
Our 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.
Conclusions:
Our 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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