Standards for Cell Line Authentication and Beyond. Cell line authentication is a powerful approach to add confidence to the results of a scientific study. However, most researchers do not perform a simple, affordable test to authenticate these key resources. In this issue, Almeida et al. discuss the importance of developing standards for authentication of cell lines, with a focus on cell line identity, to address the problem of cell line misidentification. Although different genomic technologies have been used for cell line authentication, only for one method (short tandem repeat STR profiling, STR) a comprehensive and definitive standard (ASN-0002) has been developed. This ASN-0002 document will hopefully provide a fruitful example for the development of similar standards also for nonhuman cell lines.
Why Most Clinical Research Is Not Useful. In this essay, John P.A. Ioannidis argues that features relating to problem base, context placement, information gain, pragmatism, patient centeredness, value for money, feasibility, and transparency define useful clinical research. As many studies do not satisfy these criteria, he concludes that most clinical research is not useful and reform is overdue.
Importantly, he points out that clinical researchers shouldn’t be held responsible, but instead the issue of non-useful research should be seen as an opportunity to improve and to engage many other stakeholders, including funding agencies, the industry, journals and patients. ‘Joint efforts by multiple stakeholders may yield solutions that are more likely to be more widely adopted and thus successful.’
The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications. Accurate reporting of data is an essential requirement for the biomedical research process. However, publishing of inaccurate results does occur and can result from honest mistakes or intentional falsification. In this article by Bik et al., the extent of one form of data inaccuracy, inappropriate duplication, was assessed. The authors visually analyzed images from over 20,000 papers published in 40 scientific journals from 1995-2014. The study revealed that 782 (3.8%) papers contained problematic image duplications, from which at least half showed features suggestive of deliberate manipulation. Furthermore, the prevalence of image duplications seemed to raise significantly during the past decade. The authors concluded that current standards appeared inadequate in preventing inaccurate papers from being published.
Meta-analyses provide a unique way to compare initial findings with subsequent studies. In this research article, ‘Replication Validity of Initial Association Studies: A Comparison between Psychiatry, Neurology and Four Somatic Diseases’, Dumas-Mallet et al. analyzed the credibility of studies investigating the association of risk factors with diseases by testing whether these studies were in agreement with subsequent meta-analyses. Four psychiatric disorders, four neurological diseases and four different somatic diseases were investigated. The authors found that 43% of initial significant studies paired with a significant meta-analysis reported an effect size inflated by more than 100%. Interestingly, the replication rate of initial studies reporting a significant effect ranged from 6.3% for genetic studies in psychiatry to 86.4% for cognitive/behavioral studies, indicating a difference in reliability between biological psychiatry, neurology and somatic diseases. Finally, Dumas-Mallet explored several factors that might have influenced the observed discrepancies, e.g. the level of statistical significance of the corresponding meta-analyses and of the initial studies, the biomedical domain, the study type (e.g., genetic), the sample size, the journal Impact Factor and the publication year.