Dataset Information

Does type of funding affect reporting in network meta-analysis? A scoping review of network meta-analyses.

ABSTRACT:

Background

Evidence has shown that private industry-sponsored randomized controlled trials (RCTs) and meta-analyses are more likely to report intervention-favourable results compared with other sources of funding. However, this has not been assessed in network meta-analyses (NMAs).

Objectives

To (a) explore the recommendation rate of industry-sponsored NMAs on their company's intervention, and (b) assess reporting in NMAs of pharmacologic interventions according to their funding type.

Methods

Design: Scoping review of published NMAs with RCTs.

Information sources

We used a pre-existing NMA database including 1,144 articles from MEDLINE, EMBASE and Cochrane Database of Systematic Reviews, published between January 2013 and July 2018.

Study selection

NMAs with transparent funding information and comparing pharmacologic interventions with/without placebo.

Synthesis

We captured whether NMAs recommended their own or another company's intervention, classified NMAs according to their primary outcome findings (i.e., statistical significance and direction of effect), and according to the overall reported conclusion. We assessed reporting using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension to NMA (PRISMA-NMA) 32-item checklist. We matched and compared industry with non-industry NMAs having the same research question, disease, primary outcome, and pharmacologic intervention against placebo/control.

Results

We retrieved 658 NMAs, which reported a median of 23 items in the PRISMA-NMA checklist (interquartile range [IQR]: 21-26). NMAs were categorized as 314 publicly-sponsored (PRISMA-NMA median 24.5, IQR 22-27), 208 non-sponsored (PRISMA-NMA median 23, IQR 20-25), and 136 industry/mixed-sponsored NMAs (PRISMA-NMA median 21, IQR 19-24). Most industry-sponsored NMAs recommended their own manufactured drug (92%), suggested a statistically significant positive treatment-effect for their drug (82%), and reported an overall positive conclusion (92%). Our matched NMAs (25 industry vs 25 non-industry) indicated that industry-sponsored NMAs had favourable conclusions more often (100% vs 80%) and were associated with larger (but not statistically significantly different) efficacy effect sizes (in 61% of NMAs) compared with non-industry-sponsored NMAs.

Conclusions

Differences in completeness of reporting and author characteristics were apparent among NMAs with different types of funding. Publicly-sponsored NMAs had the best reporting and published their findings in higher impact-factor journals. Knowledge users should be mindful of this potential funding bias in NMAs.

SUBMITTER: Veroniki AA

PROVIDER: S-EPMC10163730 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Does type of funding affect reporting in network meta-analysis? A scoping review of network meta-analyses.

Veroniki Areti Angeliki AA Wong Eric Kai Chung EKC Lunny Carole C Martinez Molina Juan Camilo JC Florez Ivan D ID Tricco Andrea C AC Straus Sharon E SE

Systematic reviews 20230506 1

<h4>Background</h4>Evidence has shown that private industry-sponsored randomized controlled trials (RCTs) and meta-analyses are more likely to report intervention-favourable results compared with other sources of funding. However, this has not been assessed in network meta-analyses (NMAs).<h4>Objectives</h4>To (a) explore the recommendation rate of industry-sponsored NMAs on their company's intervention, and (b) assess reporting in NMAs of pharmacologic interventions according to their funding t ...[more]

PMID: 37149700

Similar Datasets

Project description:BACKGROUND:Network meta-analysis (NMA) has rapidly grown in use during the past decade for the comparison of healthcare interventions. While its general use in the comparison of conventional medicines has been studied previously, to our awareness, its use to assess complementary and alternative medicines (CAM) has not been studied. A scoping review of the literature was performed to identify systematic reviews incorporating NMAs involving one or more CAM interventions. METHODS:An information specialist executed a multi-database search (e.g., MEDLINE, Embase, Cochrane), and two reviewers performed study selection and data collection. Information on publication characteristics, diseases studied, interventions compared, reporting transparency, outcomes assessed, and other parameters were extracted from each review. RESULTS:A total of 89 SR/NMAs were included. The largest number of NMAs was conducted in China (39.3%), followed by the United Kingdom (12.4%) and the United States (9.0%). Reviews were published between 2010 and 2018, with the majority published between 2015 and 2018. More than 90 different CAM therapies appeared at least once, and the median number per NMA was 2 (IQR 1-4); 20.2% of reviews consisted of only CAM therapies. Dietary supplements (51.1%) and vitamins and minerals (42.2%) were the most commonly studied therapies, followed by electrical stimulation (31.1%), herbal medicines (24.4%), and acupuncture and related treatments (22.2%). A diverse set of conditions was identified, the most common being various forms of cancer (11.1%), osteoarthritis of the hip/knee (7.8%), and depression (5.9%). Most reviews adequately addressed a majority of the PRISMA NMA extension items; however, there were limitations in indication of an existing review protocol, exploration of network geometry, and exploration of risk of bias across studies, such as publication bias. CONCLUSION:The use of NMA to assess the effectiveness of CAM interventions is growing rapidly. Efforts to identify priority topics for future CAM-related NMAs and to enhance methods for CAM comparisons with conventional medicine are needed. SYSTEMATIC REVIEW REGISTRATION: https://ruor.uottawa.ca/handle/10393/35658.

Project description:Immunization through vaccines among children has contributed to improved childhood survival and health outcomes globally. However, vaccine coverage among children is unevenly distributed across settings and populations. The measurement of inequalities is essential for understanding gaps in vaccine coverage affecting certain sub-populations and monitoring progress towards achieving equity. Our study aimed to characterize the methods of reporting inequalities in childhood vaccine coverage, inclusive of the settings, data source types, analytical methods, and reporting modalities used to quantify and communicate inequality. We conducted a scoping review of publications in academic journals which included analyses of inequalities in vaccination among children. Literature searches were conducted in PubMed and Web of Science and included relevant articles published between 8 December 2013 and 7 December 2023. Overall, 242 publications were identified, including 204 assessing inequalities in a single country and 38 assessing inequalities across more than one country. We observed that analyses on inequalities in childhood vaccine coverage rely heavily on Demographic Health Survey (DHS) or Multiple Indicator Cluster Surveys (MICS) data (39.3%), and papers leveraging these data had increased in the last decade. Additionally, about half of the single-country studies were conducted in low- and middle-income countries. We found that few studies analyzed and reported inequalities using summary measures of health inequality and largely used the odds ratio resulting from logistic regression models for analyses. The most analyzed dimensions of inequality were economic status and maternal education, and the most common vaccine outcome indicator was full vaccination with the recommended vaccine schedule. However, the definition and construction of both dimensions of inequality and vaccine coverage measures varied across studies, and a variety of approaches were used to study inequalities in vaccine coverage across contexts. Overall, harmonizing methods for selecting and categorizing dimensions of inequalities as well as methods for analyzing and reporting inequalities can improve our ability to assess the magnitude and patterns of inequality in vaccine coverage and compare those inequalities across settings and time.

Dataset Information

Does type of funding affect reporting in network meta-analysis? A scoping review of network meta-analyses.

Background

Objectives

Methods

Information sources

Study selection

Synthesis

Results

Conclusions

Publications

Does type of funding affect reporting in network meta-analysis? A scoping review of network meta-analyses.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets