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Publication in peer-reviewed journals is an essential step in the scientific process. However, publication is not simply the reporting of facts arising from a straightforward analysis thereof. Authors have broad latitude when writing their reports and may be tempted to consciously or unconsciously “spin” their study findings. Spin has been defined as a specific intentional or unintentional reporting that fails to faithfully reflect the nature and range of findings and that could affect the impression the results produce in readers. This article, based on a literature review, reports the various practices of spin from misreporting by “beautification” of methods to misreporting by misinterpreting the results. It provides data on the prevalence of some forms of spin in specific fields and the possible effects of some types of spin on readers’ interpretation and research dissemination. We also discuss why researchers would spin their reports and possible ways to avoid it.

Reproducibility, data sharing, personal data privacy concerns and patient enrolment in clinical trials are huge medical challenges for contemporary clinical research. A new technology, Blockchain, may be a key to addressing these challenges and should draw the attention of the whole clinical research community. Blockchain brings the Internet to its definitive decentralisation goal. The core principle of Blockchain is that any service relying on trusted third parties can be built in a transparent, decentralised, secure “trustless” manner at the top of the Blockchain (in fact, there is trust, but it is hardcoded in the Blockchain protocol via a complex cryptographic algorithm). Therefore, users have a high degree of control over and autonomy and trust of the data and its integrity. Blockchain allows for reaching a substantial level of historicity and inviolability of data for the whole document flow in a clinical trial. Hence, it ensures traceability, prevents a posteriori reconstruction and allows for securely automating the clinical trial through what are called Smart Contracts. At the same time, the technology ensures fine-grained control of the data, its security and its shareable parameters, for a single patient or group of patients or clinical trial stakeholders. In this commentary article, we explore the core functionalities of Blockchain applied to clinical trials and we illustrate concretely its general principle in the context of consent to a trial protocol. Trying to figure out the potential impact of Blockchain implementations in the setting of clinical trials will shed new light on how modern clinical trial methods could evolve and benefit from Blockchain technologies in order to tackle the aforementioned challenges.

About 10% of people infected by severe acute respiratory syndrome coronavirus 2 experience post COVID-19 disease. We analysed data from 968 adult patients (5350 person-months) with a confirmed infection enroled in the ComPaRe long COVID cohort, a disease prevalent prospective e-cohort of such patients in France. Day-by-day prevalence of post COVID-19 symptoms was determined from patients’ responses to the Long COVID Symptom Tool, a validated self-reported questionnaire assessing 53 symptoms. Among patients symptomatic after 2 months, 85% still reported symptoms one year after their symptom onset. Evolution of symptoms showed a decreasing prevalence over time for 27/53 symptoms (e.g., loss of taste/smell); a stable prevalence over time for 18/53 symptoms (e.g., dyspnoea), and an increasing prevalence over time for 8/53 symptoms (e.g., paraesthesia). The disease impact on patients’ lives began increasing 6 months after onset. Our results are of importance to understand the natural history of post COVID-19 disease. Long-term complications and persistent symptoms occur following COVID-19, but the nature and duration of the long-term symptoms are not fully characterised. Here the authors report the evolution of post COVID-19 symptoms using a validated self-reported questionnaire assessing 53 symptoms over time in the ComPaRe long COVID prospective e-cohort.

The growth in scientific production may threaten the capacity for the scientific community to handle the ever-increasing demand for peer review of scientific publications. There is little evidence regarding the sustainability of the peer-review system and how the scientific community copes with the burden it poses. We used mathematical modeling to estimate the overall quantitative annual demand for peer review and the supply in biomedical research. The modeling was informed by empirical data from various sources in the biomedical domain, including all articles indexed at MEDLINE. We found that for 2015, across a range of scenarios, the supply exceeded by 15% to 249% the demand for reviewers and reviews. However, 20% of the researchers performed 69% to 94% of the reviews. Among researchers actually contributing to peer review, 70% dedicated 1% or less of their research work-time to peer review while 5% dedicated 13% or more of it. An estimated 63.4 million hours were devoted to peer review in 2015, among which 18.9 million hours were provided by the top 5% contributing reviewers. Our results support that the system is sustainable in terms of volume but emphasizes a considerable imbalance in the distribution of the peer-review effort across the scientific community. Finally, various individual interactions between authors, editors and reviewers may reduce to some extent the number of reviewers who are available to editors at any point.

The biomedical research complex has been estimated to consume almost a quarter of a trillion US dollars every year. Unfortunately, evidence suggests that a high proportion of this sum is avoidably wasted. In 2014, The Lancet published a series of five reviews showing how dividends from the investment in research might be increased from the relevance and priorities of the questions being asked, to how the research is designed, conducted, and reported. 17 recommendations were addressed to five main stakeholders—funders, regulators, journals, academic institutions, and researchers. This Review provides some initial observations on the possible effects of the Series, which seems to have provoked several important discussions and is on the agendas of several key players. Some examples of individual initiatives show ways to reduce waste and increase value in biomedical research. This momentum will probably move strongly across stakeholder groups, if collaborative relationships evolve between key players; further important work is needed to increase research value. A forthcoming meeting in Edinburgh, UK, will provide an initial forum within which to foster the collaboration needed.

In this randomized trial, patients with vasculitides who were in complete remission after initial induction therapy received either rituximab at intervals or daily azathioprine. More patients had sustained remission with rituximab than with azathioprine. Granulomatosis with polyangiitis (formerly called Wegener’s granulomatosis), microscopic polyangiitis, and renal-limited antineutrophil cytoplasm antibody (ANCA)–associated vasculitides are the main ANCA-associated vasculitis variants. 1 Although these entities differ in their pathogenesis, genetics, and serotypes, severe forms of ANCA-associated vasculitis share several clinical features and currently have similar treatments. 2 – 6 A staged therapeutic strategy that combines glucocorticoids and cyclophosphamide to induce remission has dramatically improved survival over the past few decades, but with frequent early and late side effects. The results of two trials (RAVE and RITUXVAS) showed that rituximab was not inferior to daily oral or pulse intravenous cyclophosphamide for the induction . . .

Despite the burden of rheumatic and musculoskeletal diseases (RMDs), these conditions probably deserve more attention from public health authorities in several countries including developed ones. We assessed their contribution to disability. Data on disabilities associated with RMDs were extracted from the national 2008-2009 Disability-Health Survey of 29,931 subjects representative of the population in France. We used the core set of disability categories for RMDs of the World Health Organization's International Classification of Functioning, Disability and Health for analysis. Diagnosis and disabilities were self-reported. We assessed the risk of disability associated with RMDs using odds ratios (ORs) and the societal impact of RMDs using the average attributable fraction (AAF). Overall 27.7% (about 17.3 million people) (95% CI 26.9-28.4%) of the population reported having RMDs. The most prevalent RMDs were low back pain (12.5%, 12.1-13.1) and osteoarthritis (12.3%, 11.8-12.7). People reporting osteoarthritis were more disabled in walking (adjusted OR 1.9, 1.7-2.2) than those without. People reporting inflammatory arthritis were more limited in activities of daily living (from 1.4, 1.2-1.8 for walking to 2.1, 1.5-2.9 for moving around). From a societal perspective, osteoarthritis was the main contributor to activity limitations (AAF 22% for walking difficulties). Changing jobs was mainly attributed to neck pain (AAF 13%) and low back pain (11.5%). RMDs are highly prevalent and significantly affect activity limitations and participation restrictions. More effort is needed to improve care and research in this field.

To avoid a surge of demand on the healthcare system due to the COVID-19 pandemic, we must reduce transmission to individuals with chronic conditions who are at risk of severe illness with COVID-19. We aimed at understanding the perceptions, context and attitudes of individuals with chronic conditions during the COVID-19 pandemic to clarify their potential risk of infection. A cross-sectional survey was nested in ComPaRe, an e-cohort of adults with chronic conditions, in France. It assessed participants' perception of their risk of severe illness with COVID-19; their context (i.e., work, household, contacts with external people); and their attitudes in situations involving frequent or occasional contacts with symptomatic or asymptomatic people. Data were collected from March 23 to April 2, 2020, during the lockdown in France. Analyses were weighted to represent the demographic characteristics of French patients with chronic conditions. The subgroup of participants at high risk according to the recommendations of the French High Council for Public Health was examined. Among the 7169 recruited participants, 63% patients felt at risk because of severe illness. About one quarter (23.7%) were at risk of infection because they worked outside home, had a household member working outside home or had regular visits from external contacts. Less than 20% participants refused contact with symptomatic people and <20% used masks when in contact with asymptomatic people. Among patients considered at high risk according to the recommendations of the French High Council for Public Health, 20% did not feel at risk, which led to incautious attitudes. Individuals with chronic conditions have distorted perceptions of their risk of severe illness with COVID-19. In addition, they are exposed to COVID-19 due to their context or attitudes.

Wearable biometric monitoring devices (BMDs) and artificial intelligence (AI) enable the remote measurement and analysis of patient data in real time. These technologies have generated a lot of “hype,” but their real-world effectiveness will depend on patients’ uptake. Our objective was to describe patients’ perceptions of the use of BMDs and AI in healthcare. We recruited adult patients with chronic conditions in France from the “Community of Patients for Research” (ComPaRe). Participants (1) answered quantitative and open-ended questions about the potential benefits and dangers of using of these new technologies and (2) participated in a case-vignette experiment to assess their readiness for using BMDs and AI in healthcare. Vignettes covered the use of AI to screen for skin cancer, remote monitoring of chronic conditions to predict exacerbations, smart clothes to guide physical therapy, and AI chatbots to answer emergency calls. A total of 1183 patients (51% response rate) were enrolled between May and June 2018. Overall, 20% considered that the benefits of technology (e.g., improving the reactivity in care and reducing the burden of treatment) greatly outweighed the dangers. Only 3% of participants felt that negative aspects (inadequate replacement of human intelligence, risks of hacking and misuse of private patient data) greatly outweighed potential benefits. We found that 35% of patients would refuse to integrate at least one existing or soon-to-be available intervention using BMDs and AI-based tools in their care. Accounting for patients’ perspectives will help make the most of technology without impairing the human aspects of care, generating a burden or intruding on patients’ lives.

The US Food and Drug Administration Amendments Act requires results from clinical trials of Food and Drug Administration-approved drugs to be posted at ClinicalTrials.gov within 1 y after trial completion. We compared the timing and completeness of results of drug trials posted at ClinicalTrials.gov and published in journals. We searched ClinicalTrials.gov on March 27, 2012, for randomized controlled trials of drugs with posted results. For a random sample of these trials, we searched PubMed for corresponding publications. Data were extracted independently from ClinicalTrials.gov and from the published articles for trials with results both posted and published. We assessed the time to first public posting or publishing of results and compared the completeness of results posted at ClinicalTrials.gov versus published in journal articles. Completeness was defined as the reporting of all key elements, according to three experts, for the flow of participants, efficacy results, adverse events, and serious adverse events (e.g., for adverse events, reporting of the number of adverse events per arm, without restriction to statistically significant differences between arms for all randomized patients or for those who received at least one treatment dose). From the 600 trials with results posted at ClinicalTrials.gov, we randomly sampled 50% (n = 297) had no corresponding published article. For trials with both posted and published results (n = 202), the median time between primary completion date and first results publicly posted was 19 mo (first quartile = 14, third quartile = 30 mo), and the median time between primary completion date and journal publication was 21 mo (first quartile = 14, third quartile = 28 mo). Reporting was significantly more complete at ClinicalTrials.gov than in the published article for the flow of participants (64% versus 48% of trials, p<0.001), efficacy results (79% versus 69%, p = 0.02), adverse events (73% versus 45%, p<0.001), and serious adverse events (99% versus 63%, p<0.001). The main study limitation was that we considered only the publication describing the results for the primary outcomes. Our results highlight the need to search ClinicalTrials.gov for both unpublished and published trials. Trial results, especially serious adverse events, are more completely reported at ClinicalTrials.gov than in the published article.