INTRODUCTION The tobacco control community has raised some concerns about whether studies on electronic cigarettes (e-cigarettes) published in scientific journals hide conflicts of interest (COI) and whether such reports are biased. This study assessed potential COI in the e-cigarette scientific literature. METHODS Cross-sectional study was conducted on e-cigarette publications indexed in PubMed up to August 2014. We extracted information about the authors (affiliations, location, etc.), publication characteristics (type, topic, subject, etc.), results and conclusions, presence of a COI statement, and funding by and/or financial ties to pharmaceutical, tobacco, and/or e-cigarette companies. An algorithm to determine the COI disclosure status was created based on the information in the publication. Prevalence ratios (PRs) and confidence intervals (CIs) were calculated to identify associations with COI disclosure, controlling for several independent variables. RESULTS Of the 404 publications included in the analysis, 37.1% (n=150) had no COI disclosure statement, 38.6% declared no COI, 13.4% declared potential COI with pharmaceutical companies, 3.0% with tobacco companies, and 10.6% with e-cigarette companies. The conclusions in publications with COI, which were mainly tied to pharmaceutical companies, were more likely to be favourable to e-cigarette use (PR=2.23; 95% CI: 1.43-3.46). Publications that supported the use of e-cigarettes for both harm reduction (PR= 1.81; 95% CI: 1.14-2.89) and smoking cessation (PR= 2.02; 95% CI: 1.26-3.23) were more likely to have conclusions that were favourable to e-cigarettes. CONCLUSIONS One-third of the publications reporting studies on e-cigarettes did not have a COI disclosure statement, and this proportion was even higher in news articles, editorials and other types of publications. Papers with conclusions that were favourable to e-cigarette use were more likely to have COI. Journal editors and reviewers should consider evaluating publications, including funding sources, to determine whether the results and conclusions may be biased.