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Adjustment of publication bias using a cumulative meta-analytic framework

Part of: Special Collection - Methods

Published online by Cambridge University Press:  28 June 2022

W. J. Canestaro Open the ORCID record for W. J. Canestaro [Opens in a new window] ,
E. B. Devine ,
A. Bansal ,
S. D. Sullivan  and
J. J. Carlson
W. J. Canestaro*
Affiliation:
School of Pharmacy, University of Washington, Seattle, WA, USA Washington Research Foundation, Seattle, WA, USA
E. B. Devine
Affiliation:
School of Pharmacy, University of Washington, Seattle, WA, USA
A. Bansal
Affiliation:
School of Pharmacy, University of Washington, Seattle, WA, USA
S. D. Sullivan
Affiliation:
School of Pharmacy, University of Washington, Seattle, WA, USA
J. J. Carlson
Affiliation:
School of Pharmacy, University of Washington, Seattle, WA, USA
*
* Author for correspondence: W. J. Canestaro, E-mail: [email protected]
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Abstract

Objectives

Publication bias has the potential to adversely impact clinical decision making and patient health if alternative decisions would have been made had there been complete publication of evidence.

Methods

The objective of our analysis was to determine if earlier publication of the complete evidence on rosiglitazone’s risk of myocardial infarction (MI) would have changed clinical decision making at an earlier point in time. We tested several methods for adjustment of publication bias to assess the impact of potential time delays to identifying the MI effect. We then performed a cumulative meta-analysis (CMA) for both published studies (published-only data set) and all studies performed (comprehensive data set). We then created an adjusted data set using existing methods of adjustment for publication bias (Harbord regression, Peter’s regression, and the nonparametric trim and fill method) applied to the limited data set. Finally, we compared the time to the decision threshold for each data set using CMA.

Results

Although published-only and comprehensive data sets did not provide notably different final summary estimates [OR = 1.4 (95 percent confidence interval [CI]: .95–2.05) and 1.42 (95 percent CI: 1.03–1.97)], the comprehensive data set reached the decision threshold 36 months earlier than the published-only data set. All three adjustment methods tested did not show a differential time to decision threshold versus the published-only data set.

Conclusions

Complete access to studies capturing MI risk for rosiglitazone would have led to the evidence reaching a clinically meaningful decision threshold 3 years earlier.

Keywords

Publication biasCumulative meta-analysisStatistical adjustment
Type
Method
Information
International Journal of Technology Assessment in Health Care , Volume 38 , Issue 1 , 2022 , e61
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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