Étiquette : biomedical research

Publié le

COVID‐19 and the generation of novel scientific knowledge: Evidence‐based decisions and data sharing

Authors : Lucie Perillat, Brian S. Baigrie

Rationale, aims and objectives

The COVID‐19 pandemic has impacted every facet of society, including medical research. This paper is the second part of a series of articles that explore the intricate relationship between the different challenges that have hindered biomedical research and the generation of novel scientific knowledge during the COVID‐19 pandemic.

In the first part of this series, we demonstrated that, in the context of COVID‐19, the scientific community has been faced with numerous challenges with respect to (1) finding and prioritizing relevant research questions and (2) choosing study designs that are appropriate for a time of emergency.

Methods

During the early stages of the pandemic, research conducted on hydroxychloroquine (HCQ) sparked several heated debates with respect to the scientific methods used and the quality of knowledge generated.

Research on HCQ is used as a case study in both papers. The authors explored biomedical databases, peer‐reviewed journals, pre‐print servers and media articles to identify relevant literature on HCQ and COVID‐19, and examined philosophical perspectives on medical research in the context of this pandemic and previous global health challenges.

Results

This second paper demonstrates that a lack of research prioritization and methodological rigour resulted in the generation of fleeting and inconsistent evidence that complicated the development of public health guidelines.

The reporting of scientific findings to the scientific community and general public highlighted the difficulty of finding a balance between accuracy and speed.

Conclusions

The COVID‐19 pandemic presented challenges in terms of (3) evaluating evidence for the purpose of making evidence‐based decisions and (4) sharing scientific findings with the rest of the scientific community.

This second paper demonstrates that the four challenges outlined in the first and second papers have often compounded each other and have contributed to slowing down the creation of novel scientific knowledge during the COVID‐19 pandemic.

DOI : https://doi.org/10.1111/jep.13548

Publié le

‘Nepotistic journals’: a survey of biomedical journals

Authors : Alexandre Scanff, Florian Naudet, Ioana Cristea, David Moher, Dorothy V M Bishop, Clara Locher

Context

Convergent analyses in different disciplines support the use of the Percentage of Papers by the Most Prolific author (PPMP) as a red flag to identify journals that can be suspected of questionable editorial practices. We examined whether this index, complemented by the Gini index, could be useful for identifying cases of potential editorial bias, using a large sample of biomedical journals.

Methods

We extracted metadata for all biomedical journals referenced in the National Library of Medicine, with any attributed Broad Subject Terms, and at least 50 authored (i.e. by at least one author) articles between 2015 and 2019, identifying the most prolific author (i.e. the person who signed the most papers in each particular journal).

We calculated the PPMP and the 2015-2019 Gini index for the distribution of articles across authors. When the relevant information was reported, we also computed the median publication lag (time between submission and acceptance) for articles authored by any of the most prolific authors and that for articles not authored by prolific authors.

For outlier journals, defined as a PPMP or Gini index above the 95th percentile of their respective distributions, a random sample of 100 journals was selected and described in relation to status on the editorial board for the most prolific author.

Results

5 468 journals that published 4 986 335 papers between 2015 and 2019 were analysed. The PPMP 95th percentile was 10.6% (median 2.9%). The Gini index 95th percentile was 0.355 (median 0.183). Correlation between the two indices was 0.35 (95CI 0.33 to 0.37). Information on publication lag was available for 2 743 journals.

We found that 277 journals (10.2%) had a median time lag to publication for articles by the most prolific author(s) that was shorter than 3 weeks, versus 51 (1.9%) journals with articles not authored by prolific author(s).

Among the random sample of outlier journals, 98 provided information about their editorial board. Among these 98, the most prolific author was part of the editorial board in 60 cases (61%), among whom 25 (26% of the 98) were editors-in-chief.

Discussion

In most journals publications are distributed across a large number of authors. Our results reveal a subset of journals where a few authors, often members of the editorial board, were responsible for a disproportionate number of publications.

The papers by these authors were more likely to be accepted for publication within 3 weeks of their submission. To enhance trust in their practices, journals need to be transparent about their editorial and peer review practices.

URL : ‘Nepotistic journals’: a survey of biomedical journals

DOI : https://doi.org/10.1101/2021.02.03.429520

Publié le

Influence and management of conflicts of interest in randomised clinical trials: qualitative interview study

Authors : Lasse Østengaard, Andreas Lundh, Tine Tjørnhøj-Thomsen, Suhayb Abdi, Mustafe H A Gelle, Lesley A Stewart, Isabelle Boutron, Asbjørn Hróbjartsson

Objective

To characterise and analyse the experiences of trial researchers of if and how conflicts of interest had unduly influenced clinical trials they had worked on, what management strategies they had used to minimise any potential influence, and their experiences and views on conflicts of interest more generally.

Design

Qualitative interview study.

Participants

Trial researchers who had participated in at least 10 clinical trials with methodological or statistical expertise. Researchers differed by geographical location, educational background, and experience with different types of funders. Interviewees were identified by searches on Web of Science and snowball sampling. 52 trial researchers were approached by email; 20 agreed to be interviewed.

Setting

Interviews conducted by telephone, recorded, transcribed verbatim, imported to NVivo 12, and analysed by systematic text condensation. Semistructured interviews focused on financial and non-financial conflicts of interest.

Results

The interviewees had participated in a median of 37.5 trials and were mainly male physicians who had experience with commercial and non-commercial trial funders. Two predefined themes (influence of conflicts of interest and management strategies) and two additional themes (definition and reporting of conflicts of interest) emerged.

Examples of perceived influence of conflicts of interest were: choice of inferior comparator, manipulation of the randomisation process, prematurely stopping the trials, fabrication of data, blocking access to data, and spin (eg, overly favourable interpretation of the results).

Examples of strategies to manage conflicts of interest were: disclosure procedures, exclusion of the funder from design and analysis, independent committees, contracts ensuring complete access to the data, and no restriction by the funder on analysis and reporting.

Interviewees used different definitions or thresholds for what they considered to be conflicts of interest, and they described different criteria for when to report them. Some interviewees considered non-commercial financial conflicts of interest (eg, funding of trials by governmental health agencies with a political agenda) to be equally or more important than commercial financial conflicts of interest (eg, funding by drug and device companies), but more challenging to report and manage.

Conclusion

This study described how trial researchers perceive conflicts of interest unduly influencing clinical trials they had worked on, and the management strategies they used to prevent these influences.

The results indicated considerable variability in researchers’ understanding of what conflicts of interest are and when they should be reported.

URL : Influence and management of conflicts of interest in randomised clinical trials: qualitative interview study

DOI : https://doi.org/10.1136/bmj.m3764

Publié le

The Rigor and Transparency Index Quality Metric for Assessing Biological and Medical Science Methods

Authors : Joe Menke, Martijn Roelandse, Burak Ozyurt, Maryann Martone, Anita Bandrowski

The reproducibility crisis is a multifaceted problem involving ingrained practices within the scientific community. Fortunately, some causes are addressed by the author’s adherence to rigor and reproducibility criteria, implemented via checklists at various journals.

We developed an automated tool (SciScore) that evaluates research articles based on their adherence to key rigor criteria, including NIH criteria and RRIDs, at an unprecedented scale. We show that despite steady improvements, less than half of the scoring criteria, such as blinding or power analysis, are routinely addressed by authors; digging deeper, we examined the influence of specific checklists on average scores.

The average score for a journal in a given year was named the Rigor and Transparency Index (RTI), a new journal quality metric. We compared the RTI with the Journal Impact Factor and found there was no correlation. The RTI can potentially serve as a proxy for methodological quality.

URL : The Rigor and Transparency Index Quality Metric for Assessing Biological and Medical Science Methods

DOI : https://doi.org/10.1016/j.isci.2020.101698

Publié le

Deep Learning in Mining Biological Data

Authors : Mufti Mahmud, M. Shamim Kaiser, T. Martin McGinnity, Amir Hussain

Recent technological advancements in data acquisition tools allowed life scientists to acquire multimodal data from different biological application domains. Categorized in three broad types (i.e. images, signals, and sequences), these data are huge in amount and complex in nature.

Mining such enormous amount of data for pattern recognition is a big challenge and requires sophisticated data-intensive machine learning techniques. Artificial neural network-based learning systems are well known for their pattern recognition capabilities, and lately their deep architectures—known as deep learning (DL)—have been successfully applied to solve many complex pattern recognition problems.

To investigate how DL—especially its different architectures—has contributed and been utilized in the mining of biological data pertaining to those three types, a meta-analysis has been performed and the resulting resources have been critically analysed. Focusing on the use of DL to analyse patterns in data from diverse biological domains, this work investigates different DL architectures’ applications to these data.

This is followed by an exploration of available open access data sources pertaining to the three data types along with popular open-source DL tools applicable to these data. Also, comparative investigations of these tools from qualitative, quantitative, and benchmarking perspectives are provided.

Finally, some open research challenges in using DL to mine biological data are outlined and a number of possible future perspectives are put forward.

URL : Deep Learning in Mining Biological Data

DOI : https://doi.org/10.1007/s12559-020-09773-x

Publié le

The move to open: medical library leadership in scholarly communication

Author : Chris Shaffer

Over the years, health sciences librarians have been change agents, leading the charge on issues of importance to the profession and the communities we serve. From its founding in 1898 with the Exchange, the Medical Library Association (MLA) has been dedicated to improving access to health information.

In 2003, the Board of Directors published a statement supporting open access to information generated from federally funded scientific and medical research and maintained that having access to timely, relevant, and accurate information is vital to the health of the nation and its education and research programs.

At some financial risk, the association made the Journal of the Medical Library Association (JMLA) open access and published the entire archive of JMLA and its predecessor, the Bulletin of the Medical Library Association, in PubMed Central. Nearly two decades later, the promise of open access and open science finally seems to be coming to fruition.

In the 2020 Janet Doe Lecture, Chris Shaffer, AHIP, described the ways that MLA has led the profession, standing behind a shared vision and “walking the walk.” In challenging listeners to embrace open science, he affirmed that, as leaders in improving access to health sciences information since 1898, medical librarians must work in the open science arena to realize our vision “that quality information is essential for improved health.”

URL : The move to open: medical library leadership in scholarly communication

DOI : https://doi.org/10.5195/jmla.2021.1127

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Biomedical Data Sharing Among Researchers: A Study from Jordan

Authors : Lina Al-Ebbini, Omar F Khabour, Karem H Alzoubi, Almuthanna K Alkaraki

Background

Data sharing is an encouraged practice to support research in all fields. For that purpose, it is important to examine perceptions and concerns of researchers about biomedical data sharing, which was investigated in the current study.

Methods

This is a cross-sectional survey study that was distributed among biomedical researchers in Jordan, as an example of developing countries. The study survey consisted of questions about demographics and about respondent’s attitudes toward sharing of biomedical data.

Results

Among study participants, 46.9% (n=82) were positive regarding making their research data available to the public, whereas 53.1% refused the idea. The reasons for refusing to publicly share their data included “lack of regulations” (33.5%), “access to research data should be limited to the research team” (29.5%), “no place to deposit the data” (6.5%), and “lack of funding for data deposition” (6.0%).

Agreement with the idea of making data available was associated with academic rank (P=0.003). Moreover, gender (P-value=0.043) and number of publications (P-value=0.005) were associated with a time frame for data sharing (ie, agreeing to share data before vs after publication).

Conclusion

About half of the respondents reported a positive attitude toward biomedical data sharing. Proper regulations and facilitation data deposition can enhance data sharing in Jordan.

URL : Biomedical Data Sharing Among Researchers: A Study from Jordan

DOI : https://doi.org/10.2147/JMDH.S284294