Nucleotide sequence reagents underpin molecular techniques that have been applied across hundreds of thousands of publications. We have previously reported wrongly identified nucleotide sequence reagents in human research publications and described a semi-automated screening tool Seek & Blastn to fact-check their claimed status. We applied Seek & Blastn to screen >11,700 publications across five literature corpora, including all original publications in Gene from 2007 to 2018 and all original open-access publications in Oncology Reports from 2014 to 2018. After manually checking Seek & Blastn outputs for >3,400 human research articles, we identified 712 articles across 78 journals that described at least one wrongly identified nucleotide sequence. Verifying the claimed identities of >13,700 sequences highlighted 1,535 wrongly identified sequences, most of which were claimed targeting reagents for the analysis of 365 human protein-coding genes and 120 non-coding RNAs. The 712 problematic articles have received >17,000 citations, including citations by human clinical trials. Given our estimate that approximately one-quarter of problematic articles may misinform the future development of human therapies, urgent measures are required to address unreliable gene research articles.

Background The increasing use of preprints to disseminate evidence on the effect of interventions for the coronavirus disease 2019 (COVID-19) can lead to multiple evidence sources for a single study, which may differ in the reported evidence. We aim to describe the proportion of evidence on the effect of interventions for COVID-19 from preprints and journal articles and map changes in evidence between and within different sources reporting on the same study. Methods Meta-research study. We screened the Cochrane living systematic review and network meta-analysis (COVID-NMA) database to identify all preprints and journal articles on all studies assessing interventions for COVID-19 published up to 15 August 2020. We compared all evidence sources (i.e., preprint and associated journal article) and the first and latest versions of preprints for each study to identify changes in two evidence components: study results (e.g., numeric change in hazard ratio, odds ratio, event rate, or change in p value > or < 0.05 in any outcome) and abstract conclusions (classified as positive, negative or neutral regarding the intervention effect, and as reporting uncertainty in the findings or not). Changes in study results were further classified as important changes if they (1) represented a change in any effect estimate by ≥ 10% and/or (2) led to a change in the p value crossing the threshold of 0.05. Results We identified 556 studies. In total, 338 (61%) had been reported in a preprint: 66 (20%) of these had an associated journal article (median time to publication 76 days [interquartile range (IQR) 55–106]) and 91 (27%) had > 1 preprint version. A total of 139 studies (25% of the overall sample) were reported in multiple evidence sources or versions of the same source: for 63 (45%), there was a change in at least one evidence component between or within sources (42 [30%] had a change in study results, and in 29 [21%] the change was classified as important; 33 [24%] had a change in the abstract conclusion). For studies with both a preprint and an article, a median of 29% (IQR 14–50) of total citations were attributed to the preprint instead of the article. Conclusions Results on the effect of interventions for COVID-19 are often reported in multiple evidence sources or source versions for a single study. Evidence is not stable between and within evidence sources. Real-time linkage of all sources per study could help to keep systematic reviews up-to-date.