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Review
. 2022 Sep 19;12(9):e063501.
doi: 10.1136/bmjopen-2022-063501.

Evidence for stratified conflicts of interest policies in research contexts: a methodological review

S Scott Graham  1 , Martha S Karnes  2 , Jared T Jensen  3 , Nandini Sharma  3 , Joshua B Barbour  3 , Zoltan P Majdik  4 , Justin F Rousseau  5
Affiliations
Review

Evidence for stratified conflicts of interest policies in research contexts: a methodological review

S Scott Graham et al. BMJ Open. .

Abstract

Objectives: The purpose of this study was to conduct a methodological review of research on the effects of conflicts of interest (COIs) in research contexts.

Design: Methodological review.

Data sources: Ovid.

Eligibility criteria: Studies published between 1986 and 2021 conducting quantitative assessments of relationships between industry funding or COI and four target outcomes: positive study results, methodological biases, reporting quality and results-conclusions concordance.

Data extraction and synthesis: We assessed key facets of study design: our primary analysis identified whether studies stratified industry funding or COI variables by magnitude (ie, number of COI or disbursement amount), type (employment, travel fees, speaking fees) or if they assessed dichotomous variables (ie, conflict present or absent). Secondary analyses focused on target outcomes and available effects measures.

Results: Of the 167 articles included in this study, a substantial majority (98.2%) evaluated the effects of industry sponsorship. None evaluated associations between funding magnitude and outcomes of interest. Seven studies (4.3%) stratified industry funding based on the mechanism of disbursement or funder relationship to product (manufacturer or competitor). A fifth of the articles (19.8%) assessed the effects of author COI on target outcomes. None evaluated COI magnitude, and three studies (9.1%) stratified COI by disbursement type and/or reporting practices. Participation of an industry-employed author showed the most consistent effect on favourability of results across studies.

Conclusions: Substantial evidence demonstrates that industry funding and COI can bias biomedical research. Evidence-based policies are essential for mitigating the risks associated with COI. Although most policies stratify guidelines for managing COI, differentiating COIs based on the type of relationship or monetary value, this review shows that the available research has generally not been designed to assess the differential risks of COI types or magnitudes. Targeted research is necessary to establish an evidence base that can effectively inform policy to manage COI.

Keywords: ethics (see medical ethics); health policy; protocols & guidelines; risk management; statistics & research methods.

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Conflict of interest statement

Competing interests: SG has received grant support from the National Institute of General Medical Sciences of the National Institutes of Health and the National Endowment for the Humanities; compute time from the National Science Foundation’s Extreme Science and Engineering Discovery Environment; and support for consulting from the Texas Health and Human Services Commission. JBB has received grant support from the National Institute of General Medical Sciences of the National Institutes of Health, The National Science Foundation and Blue Cross Blue Shield/Health Care Service Corporation. JFR has received grant support from the National Institutes of Health (National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases, the National Institute of Mental Health), the Health Care Cost Institute, the Texas Child Mental Health Care Consortium and the Michael and Susan Dell Foundation. He has received support through research service agreements with Austin Public Health and the Integrated Care Collaboration. He has also received funds from National Center for Advancing Translational Sciences via the NIH Division of Loan Repayment. ZM has received grant support from the National Institute of General Medical Sciences of the National Institutes of Health, the National Science Foundation, the Summer Institute in Computational Social Science and consulting fees from the University of Texas at Austin.

Figures

Figure 1
Figure 1
PRISMA flow diagram. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
Figure 2
Figure 2
Variable types by year number (1986–2021). Figure includes number of studies per year by dependent variable (DV) type (A), number of studies by independent variable (IV) type for studies assessing industry funding (B) and number of studies by IV type for studies evaluating COI (C). COI, conflicts of interest.
See this image and copyright information in PMC

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