ABSTRACT Importance It is important to monitor changes in biomedical literature and its funding. China has surpassed the USA in publications and, in some analyses, also in some impact indicators. Objective To evaluate changes over time in the profiles of the most highly cited biomedical papers. Design The 100 top-cited biomedical papers (based on Scopus) published in each of three time periods (2003-4, 2013-4, and 2023-4) were assessed for corresponding authors, types of publications represented, and funding sources, with emphasis on funding from the US National Institutes of Health (NIH) that has been traditionally considered the major funder of biomedical research. Setting Global. Participants not relevant Exposures not relevant Main outcome measures Provenance and funding sources. Main findings Corresponding authors from the USA decreased overtime (59/100 papers in 2003-4, 58/100 in 2013-4, 45/100 in 2023-4). China had corresponding authors in 0,1, and 4 top cited papers in the three time periods, respectively. There was a marked increase in consensus items (10/100 in 2003-4 versus 24/100 in 2023-4) and in reference statistics papers (1/100 in 2003-4, 10/100 in 2013-4, 11/100 in 2023-4). Reviews remained common among top cited papers, but almost always they were non-systematic. NIH funding was listed in 45/100, 50/100, and 23/100 papers in the three time periods, respectively. All other countries combined surpassed US public funding in 2023-4. Funding by NIH alone decreased sharply in the last decade (32/100, 28/100, and 2/100 in the three time periods, respectively). More commonly listed funding from non-profit organizations, societies, and institutions complemented the NIH funding decline. The first authors of 7/45 and the corresponding author(s) of 14/45 top cited USA-based papers of 2023-4 were listed as leaders of active NIH grants in RePORTER as of February 2025. Citation gaming became more obvious in 2023-4. Conclusions and relevance Overall, the USA remains a world leader regarding the most highly cited biomedical research and NIH funding retains a substantial presence among top cited papers. However, NIH influence has shrunk overall, and top cited papers funded exclusively by NIH have almost disappeared. Strengthening public funding is essential to secure research serves the common good.
P values linked to null hypothesis significance testing (NHST) is the most widely (mis)used method of statistical inference. Empirical data suggest that across the biomedical literature (1990–2015), when abstracts use P values 96% of them have P values of 0.05 or less. The same percentage (96%) applies for full-text articles. Among 100 articles in PubMed, 55 report P values, while only 4 present confidence intervals for all the reported effect sizes, none use Bayesian methods and none use false-discovery rate. Over 25 years (1990–2015), use of P values in abstracts has doubled for all PubMed, and tripled for meta-analyses, while for some types of designs such as randomized trials the majority of abstracts report P values. There is major selective reporting for P values. Abstracts tend to highlight most favorable P values and inferences use even further spin to reach exaggerated, unreliable conclusions. The availability of large-scale data on P values from many papers has allowed the development and applications of methods that try to detect and model selection biases, for example, p-hacking, that cause patterns of excess significance. Inferences need to be cautious as they depend on the assumptions made by these models and can be affected by the presence of other biases (e.g., confounding in observational studies). While much of the unreliability of past and present research is driven by small, underpowered studies, NHST with P values may be also particularly problematic in the era of overpowered big data. NHST and P values are optimal only in a minority of current research. Using a more stringent threshold, as in the recently proposed shift from P
Studies of routinely collected health data could give different answers from subsequent randomized controlled trials on the same clinical questions, and may substantially overestimate treatment effects. Caution is needed to prevent misguided clinical decision making.
Statistical conditions for employing asymmetry tests for publication bias are absent from most meta-analyses; yet, in medical journals these tests are performed often and interpreted erroneously.
Under diverse contributing factors in different scientific micro-environments, the number of authors who publish extreme numbers of full articles in a single year has increased. Cardiology is the subfield that has the largest share of authors with extreme publishing behavior than any other subfield in science (outside physics). Between 2000 and 2022, 137 authors in the subfield of Cardiovascular System (CVS, Science-Metrix classification) have published over 60 full articles in at least one calendar year and are also highly cited. The majority (70/137) are from Europe. All 7 countries with the highest prevalence of CVS extreme publishing authors per million population are European countries. Issues of massive authorship of papers by administrative leaders are discussed, including the arguments in favor of sustaining this practice and a refutation of these arguments. Other major contributors to the phenomenon are publications from clinical trials and epidemiological studies and massive authorship of highly cited guidelines. Micro-environments are instrumental in creating extreme publishing behavior in both developed and less developed countries. Listing of contributions does not solve the problem since contributions are also gamed; metrics that probe gaming are nevertheless available. Eventually, authorship carries both credit and accountability. The number of publications is a metric that can be heavily gamed. Emphasis should be given to what makes a major impact on science and human lives.