United States

**Objective** The aim of this study was to investigate the
evolution of authorship trends in MEDLINE-indexed meta-analyses over time. Although similar studies do exist,1
they all have major limitations (cross-sectional nature, small
sample sizes, etc) that do not allow for reliable conclusions to
be drawn. This may be the first work to study authorship
patterns in all MEDLINE-indexed meta-analyses published.

**Design** In PubMed, the search filters of study type and
publication date were applied, and the search was restricted
to meta-analyses published until December 31, 2019. Single
research group names included in the article’s title were
considered equivalent to 1 coauthor. Articles without author
names were excluded from the study.

**Results** A total of 116,710 meta-analyses were analyzed. The
most meta-analyses per year were published in 2019 (1.2%),
followed by 2018 (1.1%). The overall mean (SD) number of
authors was 5.4 (4). The most common number of authors
was 4, found in 16.4% of articles, followed by 5 authors
(15.4%). The mean number of authors per article increased
significantly over time, from 3 in 1990-1994 to 5.8 in 2015-
2019. Single-author articles represented 24% of all articles in
1990-1994 and only 1.2% in 2015-2019. The number of
articles authored by 15 or more authors increased from 0% in
1990-1994 to 3.2% in 2015-2019.

**Conclusions** The reported trend of authorship
proliferation1,2 was also observed in meta-analyses, with a
current mean number of 5.8 authors per article. It is doubtful
whether this increase can only be attributed to increasing
research complexity.2Scientists should adhere to the existing guidelines and include in the author list only contributors
who qualify for inclusion. Journals should adopt more strict
policies to confirm that only substantial contributions are
getting credited with authorship.

**References**

1. Gülen S, Fonnes S, Andresen K, Rosenberg J. Increasing
number of authors in Cochrane reviews. J Evid Based Med.
2020;13(1):34-41. doi:10.1111/jebm.12371
2. Papatheodorou SI, Trikalinos TA, Ioannidis JPA. Inflated
numbers of authors over time have not been just due to
increasing research complexity. J Clin Epidemiol.
2008;61(6):546-551. doi:10.1016/j.jclinepi.2007.07.017

**Conflict of Interest Disclosures** None reported.

![](https://assets.underline.io/uploads/markdown_image/1/image/d557e9a6cf699ff3e88242f75361eb0d.png)

Peer Review Congress 2022

Numbers and Trends in Authorship of Published Meta-analyses, 1990-2019

and scientometrics

informatics

ethics and ethical concerns

authorship and contributorship

bibliometrics

The UKSG Annual Conference and Exhibition 2021 will be held online for the first time. The event is a major event in the scholarly communications calendar which attracts a large number of delegates each year from around the world - librarians, publishers, content providers, consultants and intermediaries. The conference combines high-quality plenary presentations, lightning talks and breakout sessions with virtual social events and a major online trade exhibition.



UKSG Annual Conference 2021

 UKSG Annual Conference is a major event in the scholarly communications calendar which attracts a large number of delegates each year from around the world - librarians, publishers, content providers, consultants and intermediaries. 

poster

Our aim is to encourage research into the quality and credibility of peer review and scientific publication, to establish the evidence base on which scientists can improve the conduct, reporting, and dissemination of scientific research.
 
 **Welcome!**
 
 The JAMA Network, The BMJ, and METRICS welcome you to the Ninth International Congress on Peer Review and Scientific Publication. We have continued our efforts to broaden the scope of the Congress to all aspects of peer review and publication—from funding to postpublication—and to all sciences.
 
 We will have 3 days for presentations of new research into peer review and all aspects of scientific publication, bias, quality of reporting, and information access and dissemination. There are 50 plenary session research presentations and 5 plenary invited talks. Each plenary session research presentation will be followed by equal time for discussion and questions from the audience. In addition, there are 125 posters. All posters, including virtual posters, are available to view throughout the meeting. In-person posters will also be presented at designated times on September 9 and 10. If you are attending virtually, please visit the individual poster pages and ask your questions in the chat box. See the link to Posters on the left.
 
 We hope you will take an active part in the program, as we depend on your participation in the discussion sessions to make the Congress a success.

 [Peer Review Congress Organizers, Directors, and Advisory Board](https://peerreviewcongress.org/organizers-and-advisory-board/)
 
 [Health and Safety Policies](https://web.cvent.com/event/1b505794-6a0b-428c-a44c-6c46c4c50e99/websitePage:152962bb-4567-4561-9d81-21ebfa97f487)

![](https://assets.underline.io/uploads/markdown_image/1/image/7c9f0143dee383780cc4670269ade132.png)

A PDF of the schedule is available [here](https://drive.google.com/file/d/1-Jd191W-nxbWcN1prdX5o9nlSfeo9_-H/view?usp=sharing) and a flipbook version of the complete program and abstracts is included below. See also the link to the interactive schedule to the left.

<iframe width="700px" height="425px" src="https://online.fliphtml5.com/ebtyf/nlfn/#p=1" frameborder="0" allowfullscreen allowtransparency></iframe>

Registration is required to attend this event, please use the URL linked below to secure your ticket. Registration will close on Friday, September 2 at 5:00 PM CT. 

[**Register Here**]( https://web.cvent.com/event/1b505794-6a0b-428c-a44c-6c46c4c50e99/summary)

Our aim is to encourage research into the quality and credibility of peer review and scientific publication, to establish the evidence base on which scientists can improve the conduct, reporting, and dissemination of scientific research.



**Objective** Systematic reviews of prognostic accuracy studies
often use the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) tool1
to assess risk of bias and applicability
of included studies because no comparable instrument exists
for prognostic accuracy studies. The QUAPAS (Quality
Assessment of Prognostic Accuracy Studies) tool is an
adaptation of QUADAS-2 for prognostic accuracy studies.

**Design** Six experienced reviewers and methodologists in the
area of test evaluation and/or development of risk of bias
tools participated in the development of QUAPAS. They used
risk of bias tools suggested for systematic reviews by the
Cochrane Prognosis Methods Group and Diagnostic Test
Accuracy Working Group. Using QUADAS-2 as a starting
point, domains and signaling questions from QUIPS (Quality
in Prognosis Studies)2
and PROBAST (Prediction Model Risk
of Bias Assessment Tool)3
were evaluated in parallel to collate
a unique list of signaling questions for each domain.
Additional signaling questions based on relevant sources of
bias were included. The steering group of 6 experts conducted
and reviewed 3 rounds of modifications before arriving at the
final set of domains and signaling questions. The authors
further shared QUAPAS with and invited written feedback
from 10 researchers and potential end users.

**Results** QUAPAS was developed to be used as QUADAS-2:
specify the review question, tailor the tool, draw a flow
diagram, judge risk of bias, and identify applicability
concerns. Risk of bias was judged across 5 domains:
participants, index test, outcome, flow and timing, and
analysis (**Table 54**). Signaling questions assisted the final
judgment for each domain. Applicability concerns were
assessed for the first 4 domains. QUAPAS was used in parallel with QUADAS-2 and QUIPS in a systematic review evaluating
the accuracy of a noninvasive liver test in prognosis of fibrosis
and mortality. Use of QUAPAS improved the risk assessment
of the flow and timing domain by the addition of a new
signaling question and flagged studies at risk of bias in the
new analysis domain. Judgment of risk of bias in the analysis
domain was found challenging owing to sparse reporting of
statistical methods.

![](https://assets.underline.io/uploads/markdown_image/1/image/984f87e6379910b204c1b3efd3143a91.png)

**Conclusions** QUAPAS may provide future systematic
reviewers and readers with a reliable tool that can assess bias
and applicability concerns in prognostic accuracy studies. Use
of a systematically tailored tool will hopefully improve the
quality assessment process and help produce more robust
evidence base for prognostic tests.

**References**

1. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a
revised tool for the quality assessment of diagnostic accuracy
studies. Ann Intern Med. 2011;155(8):529-536.
doi:10.7326/0003-4819-155-8-201110180-00009
2. Hayden JA, van der Windt DA, Cartwright JL, Côté P,
Bombardier C. Assessing bias in studies of prognostic factors.
Ann Intern Med. 2013;158(4):280-286. doi:10.7326/0003-
4819-158-4-201302190-00009
3. Wolff RF, Moons KGM, Riley RD, et al. PROBAST: a tool to
assess the risk of bias and applicability of prediction model
studies. Ann Intern Med. 2019;170(1):51-58. doi:10.7326/
M18-1376

**Conflict of Interest Disclosures** Patrick M. Bossuyt is an
advisory board member of the Peer Review Congress but was
not involved in the review or decision of this abstract. No other
disclosures were reported.

**Funding/Support** The LITMUS project received funding from
the Innovative Medicines Initiative 2 Joint Undertaking under
grant agreement 777377. This Joint Undertaking receives support
from the European Union’s Horizon 2020 research and innovation
program and EFPIA.

**Role of the Funder/Sponsor** The funders had no role in the
study.

**Acknowledgment** The authors thank Jill Hayden, PhD (Dalhousie
Medical School), for her valuable contributions to the earlier stages
of developing QUAPAS. They also thank the volunteers for reviewing
the tool.

![](https://assets.underline.io/uploads/markdown_image/1/image/4d4b4529f7ad3c99f1c62193216e520b.png)

Development of the Quality Assessment of Prognostic Accuracy Studies (QUAPAS) Tool for Assessing Risk of Bias in Prognostic Accuracy Studies

**Objective** Preclinical human gene research articles that
describe wrongly identified nucleotide sequence reagents
provide incorrect information, and these research articles
could be manufactured by paper mills that “have been alleged
to mass-produce fraudulent manuscripts for publication.”1(p2)
Such problematic articles can be highly cited1; however, the
features and consequences of these citations are largely
unknown. The authors investigated this question by analyzing
citations of problematic human gene research articles and of
literature reviews that cite these articles.

**Design** A human gene research article cited in PubMed (ie,
PMID 25721211) with wrongly identified nucleotide sequences
was selected as an index case2
to build citation networks in
R-studio using Google Scholar citations prior to March 31,
2022. The citing articles were screened for wrongly identified
sequences1
and citation context.3
Problematic articles with
wrongly identified sequences were examined through up to 6
citation generations. Because 95 literature reviews cited
problematic articles, the authors also analyzed 13 literature
reviews that focused on human genes. All review references
were screened for wrongly identified nucleotide sequences1
to identify problematic references. Each review text was
examined to identify statements that cited problematic
references. Publications that cited each literature review were
examined to identify review citations that reflected
information from problematic references.

**Results** After analysis of the citations in PMID 25721211
through up to 6 citation generations, 87 cited problematic
articles (**Figure 23**) published in 50 journals were identified.
As previously reported,1
most problematic articles (79 of 87
[91%]) were authored by teams from hospitals in China.
Ninety-three citations of problematic articles by other
problematic articles were identified. A total of 360 statements
were identified in 338 citing articles that were supported by
problematic articles, typically in the Discussion section (183
of 360 [51%]) or Introduction section (133 of 360 [41%]). The
13 human gene literature reviews cited a total of 1887
references that included 206 problematic articles (11%).
Between 1 and 13 claims per review (82 claims in total) were
supported by problematic references. The 13 reviews have
been cited 1843 times, in which 3 citations reflected claims
from 3 problematic references. The 206 problematic
references have been cited 31,914 times, including by 5
clinical trial articles. Problematic references were also cited
by 78 patent families and 9 Wikipedia entries.

![](https://assets.underline.io/uploads/markdown_image/1/image/3983c5a0e0e2f89bd31b5c6a7a9b1d30.png)

**Conclusions** After analysis of the citation network for 1
problematic gene research article, 87 problematic articles and
93 citations of problematic articles by other problematic
articles were identified (**Figure 23**). It was further
demonstrated that 13 literature reviews of human genes
referenced 206 problematic articles that were in turn cited
31,914 times. Although infrequent, subsequent literature
review citations can reflect information from problematic
review references.

**References**

1. Park Y, West RA, Pathmendra P, et al. Identification of
human gene research articles with wrongly identified
nucleotide sequences. Life Sci Alliance. 2022;5:e202101203.
doi:10.26508/lsa.202101203
2. Kempen JH. Appropriate use and reporting of uncontrolled
case series in the medical literature. Am J Ophthalmol.
2011;151:7-10. doi:10.1016/j.ajo.2010.08.047
3. Zhang G, Ding Y, Milojević S. Citation content analysis
(CCA): a framework for syntactic and semantic analysis of
citation content. J Am Soc Inf Sci Tec. 2013;64:1490-1503.
doi:10.1002/asi.22850

**Conflict of Interest Disclosures** None reported.

**Funding/Support** Jennifer Anne Byrne acknowledges grant
funding from the National Health and Medical Research Council of
Australia, Ideas grant ID APP1184263.

**Role of the Funder/Sponsor** The funder played no role in
the study design, data collection, management, analysis, or
interpretation and will play no role in the writing of any report or
the decision to submit the report for publication.

![](https://assets.underline.io/uploads/markdown_image/1/image/a42bced5c61488a61bff554a7e14a73d.png)

Citations of Human Gene Research Articles That Describe Wrongly Identified Nucleotide Sequences

**Objective** Commercial companies often fund randomized
clinical trials, and methodological studies suggest that this
funding may influence trial results and conclusions.1
However, such methodological studies are often at risk of
confounding given that they compare trials that differ for
reasons other than funding source. The risk of confounding
can be minimized in meta-epidemiological studies that
compare similar trials within meta-analyses. The Commercial
Funding in Trials (COMFIT) study was initiated based on a
consortium of researchers who shared data sets with
information on meta-analyses and trials included in meta-
epidemiological studies (details available in the protocol2).
The primary aim of COMFIT was to investigate the impact of
commercial funding on estimated intervention effects in
randomized clinical trials.

**Design** The study approach was to identify meta-
epidemiological studies and combine and reanalyze their
meta-analysis and trial data. Studies with data on trial
funding source and results were included (eg, primarily by
investigating funding source or investigating a different trial
characteristic and adjusting for funding source). Five
bibliographic databases and other sources (eg, conference
proceedings) were searched. Meta-epidemiological study
authors were contacted and invited to join the COMFIT
consortium and share their unpublished data. Construction of
the COMFIT database involved, for example, merging data
from included studies and checking data quality.
Noninformative meta-analyses (eg, meta-analyses in which
all trials had the same funding type) and overlapping or
correlated meta-analyses and trials (eg, multiple meta-
analyses included from the same systematic review) were
removed. Bayesian hierarchical models were used to estimate
the ratio of odds ratios (RORs) and heterogeneity statistics
(to describe within- and between-study heterogeneity). A
ROR <1 indicated exaggerated intervention effects in trials
with commercial funding. Unadjusted and adjusted analyses
using bias domains (low vs high risk of bias from sequence
generation, allocation concealment, blinding, incomplete
outcome data, selective reporting, and overall risk of bias)
and trial sample size were performed. Subgroup and
sensitivity analyses (eg, using the Sterne 2-step approach3)
were performed.

**Results** The COMFIT database contained data on 554
meta-analyses, with 4936 trials from 17 meta-epidemiological
studies. Meta-analyses included a median (range) of 7 (2-68)
trials. In total, 1368 trials (28%) had noncommercial funding,
1840 trials (37%) had sole commercial or mixed commercial
and noncommercial funding, and the remaining 1728 trials
(35%) did not have funding sources reported. Using data from
the largest meta-epidemiological study (20% of meta-
analyses, 19% of trials), the ROR for the association between
commercial funding and estimated intervention effects was
0.90 (95% CI, 0.84-0.96) (preliminary findings, not the
primary analysis).

**Conclusions** The COMFIT database may enable
comprehensive analyses of the impact of commercial funding on trial results. The primary analyses will have a markedly
increased statistical power and reduced risk of confounding
and reporting bias compared with previous studies.

**References**

1. Lundh A, Lexchin J, Mintzes B, Schroll JB, Bero L. Industry
sponsorship and research outcome. Cochrane Database Syst
Rev. 2017;2:MR000033. doi:10.1002/14651858.MR000033.
pub3

2. Nejstgaard CH, Lundh A, Abdi S, et al. Combining meta-
epidemiological study datasets on commercial funding of
randomised clinical trials: database, methods, and descriptive
results of the COMFIT study. Res Synth Methods.
2022;13(2):214-228. doi:10.1002/jrsm.1527

3. Sterne JAC, Jüni P, Schulz KF, Altman DG, Bartlett C,
Egger M. Statistical methods for assessing the influence of
study characteristics on treatment effects in “meta-
epidemiological” research. Stat Med. 2002;21:1513-1524.

**Conflict of Interest Disclosures** Asbjørn Hróbjartsson and
Andreas Lundh are currently members of the TACIT steering group
to develop a tool for addressing conflicts of interest in trials. Toshi
A. Furukawa reported receiving grants and personal fees from
Mitsubishi-Tanabe and Shionogi, receiving personal fees from
Sony outside the submitted work, and having patent 2020-548587
concerning smartphone cognitive behavioral applications pending
and intellectual properties for the Kokoro application licensed
to Mitsubishi-Tanabe. Jelena Savović was paid by Core Models
to deliver an online teaching session of basic evidence synthesis
methods. John P. A. Ioannidis is co-director and Isabelle Boutron
is an advisory board member of the Peer Review Congress, but they
were not involved in the review or decision for this abstract.

![](https://assets.underline.io/uploads/markdown_image/1/image/b324cc07cafc76fee258b6908383b6e3.png)

Association Between Commercial Funding and Estimated Intervention Effects in Randomized Trials: The COMFIT Study

**Objective** Recent data suggest that authors may not be
transparent with reporting financial conflicts of interest.1,2
However, there is a paucity of data about journal editors,2
who are the ultimate decision-makers regarding publication.
This topic is particularly important among specialties with
significant academic-industry interactions.

**Design** A cross-section of the top journals in oncology (100)
and cardiology (100) were selected based on their journal
impact factors (JIFs).3The JIF and total number of citations
for each journal were collated and the primary editors (editor
in chief, executive editor, or similar designation) for each
journal were identified through journal websites; for journals
listing more than a single primary editor (14), each editor was
considered separately. Every editor (216) was queried on the
Center for Medicare and Medicaid Services Open Payments
Database (https://openpaymentsdata.cms.gov) for the most
recently reported total payments, general payments, and
research payments or associated research funding since 2014.
Exclusively international editors (33 for oncology and 45 for
cardiology) were not included in analyses. One journal was
removed from the oncology data set because of a suspected
error in JIF calculation. Payments for each specialty were
analyzed using medians and IQRs. Journal websites were
examined for editors with more than US $5000 in total
payments to assess for transparency.

**Results** Of 78 editors in oncology, 40 accepted general
payments and 24 collected research payments (18 received
both); of 60 editors for cardiology, 42 received general
payments and 18 received research payments (12 received
both). Median general payments were similar between the 2
specialties (**Table 55**), but research payments were higher
for oncology. In journals with editors receiving payments of
any type greater than $5000 (54), generic conflict of interest
policy statements appeared on 25 journal websites; 3 listed
specific dollar amounts or specific companies.

![](https://assets.underline.io/uploads/markdown_image/1/image/cf8c9eef9f847ab6f3ac3aacec1d4b70.png)

**Conclusions** Despite increased focus on potential conflicts
of interest in journal editing, a significant proportion of
editors of top-tier oncology and cardiology journals receive
payments from industry, and the nature of these relationships are not transparent to authors or the readership. Given the
role that editors play in the publication process, specific
conflicts and recusal policies should be more clearly
delineated.

**References**

1. Baraldi JH, Picozzo SA, Arnold JC, Volarich K, Giofriddo
MR, Piper BJ. A cross-sectional examination of conflict-of-
interest disclosures of physician-authors publishing in
high-impact US medical journals. medRxiv. Preprint posted
online January 1, 2022. doi:10.1101/2021.09.12.21263468

2. Dal-Ré R, Caplan AL, Marusic A. Editors’ and authors’
individual conflicts of interest disclosure and journal
transparency: a cross-sectional study of high-impact medical
specialty journals. BMJ Open. 2019;9:e029796. doi:10.1136/
bmjopen-2019-029796

3. Clarivate Analytics. 2020 Journal Impact Factor. Journal
Citation Reports. Clarivate; 2021.

**Conflict of Interest Disclosures** Paul J. Hauptman reported
receiving remuneration from Corvia Medical (DSMB), scPharma
and LivaNova (clinical events committees), and Array Biopharma
(steering committee) for work related to clinical trials as indicated.
No other disclosures were reported.

![](https://assets.underline.io/uploads/markdown_image/1/image/f5b55a06ac36bedaf48ea8b47fe9fbba.png)

Evaluation of Journal Editor Conflict of Interest Disclosures and Remuneration Transparency in Oncology and Cardiology

**Objective** To assess editors’ experience with and openness to
refining journal article abstracts by adding a results table and
a limitations header to improve abstract readability and
informational content.1-3

**Design** General medical journals were selected based on
journal impact factor rankings: all top 10 ranked journals and
5 among those ranked in the third quartile, published in
English, with multiple issues per year, and using a structured
abstract. Only one journal from the JAMA Network was
selected. Semistructured interviews were conducted with the editor recommended by the journal’s editor in chief. The
study ethics approval (exemption) was provided by
Dartmouth.

**Results** Eleven of the 15 invited journals participated (9
from the top 10 and 2 of 5 from the third quartile by impact
factor). Interviews were conducted with 4 editors in chief, 3
executive editors, and 4 other editor types by S.W. on a web
conferencing platform (1 editor responded in writing) from
February 4 to March 4, 2022, and lasted 15 to 20 minutes.
Calls were recorded and autotranscribed. All study authors
reviewed the full interview transcripts, R.J.W. summarized
key themes from transcripts, and all authors reached
consensus on abstract results tables key themes (**Table 56**).
One journal had experience publishing abstract results tables.
There was strong interest in a limitations header and few
concerns about it having any potential harms.

![](https://assets.underline.io/uploads/markdown_image/1/image/061ccdeb247a9e97036918916ab0570d.png)

**Conclusions** These findings provide preliminary support for
a trial evaluating the addition of results tables and limitations
to abstracts. Limitations of this study are that it may not be
representative of all journals and interviews did not include
abstract readers or authors.

**References**

1. Bauchner H, Henry R, Golub RM. The restructuring of
structured abstracts: adding a table in the results section.
JAMA. 2013;309(5):491-492. doi:10.1001/jama.2013.76
2. Ertl N, Gazette K. A new way of documenting scientific data
from medical publications. Karger Gaz. 1969;20(27):1-3.
3. Haynes RB, Mulrow CD, Huth EJ, Altman DG, Gardner
MJ. More informative abstracts revisited: a progress report.
Ann Intern Med. 1990;113(1):69-76. doi:10.7326/0003-4819-
113-1-69

**Conflict of Interest Disclosures** Steven Woloshin serves on the
Cochrane Collaboration and the JAMA Internal Medicine editorial
boards. Lisa Bero is Senior Research Integrity Editor, Cochrane,
and serves on the Cochrane Editorial Board; an academic editor,
Meta-Research, PLoS Biology; and a member of the Peer Review
Congress Advisory Board but was not involved in the review or
decision for this abstract. No other disclosures were reported.

**Acknowledgment** This paper is dedicated to the memory of Lisa
Schwartz, MD, MS, our remarkable partner, colleague, and friend
whose work inspired this project. The authors thank the journal
editors and staff who participated in interviews.

![](https://assets.underline.io/uploads/markdown_image/1/image/3ecec4b2b458a89d469a50971969554a.png)



Editors' Perspectives on Adding a Results Table and Limitations Section to Medical Journal Abstracts: A Qualitative Study

**Objective** To quantify the administrative demands and
timeliness of sharing individual participant data and identify
the main choke points for researchers and contracts
departments.

**Design** This mixed-methods study conducted in 2022
included 2 case studies of individual participant data meta-
analyses, Individual Participant Data on Cord Management at
Preterm Birth (iCOMP) and Transforming Obesity Prevention
for Children (TOPCHILD), for which data were requested
from international trials from 2019 until May 2022. Each
contact with trial investigators was logged in custom-built
software. From these logs, contact time points, study
characteristics (eg, year, sample size, country), email texts,
and data-sharing status were extracted. Researchers
responsible for negotiating agreements were interviewed to
identify choke points. The median, IQR, and range of time
from the first data request until data receipt were calculated,
and the number of emails required was tallied. Emails,
data-sharing agreements, reasons data could not be shared,
and interview responses were analyzed qualitatively using a
thematic analysis to identify choke points and facilitators.

**Results** For 71 of 72 included trials (50 iCOMP trials [69%],
22 TOPCHILD trials [31%]), data were directly requested and
supplied from investigators. Only 1 data set was available as a
publication supplement; none used data repositories. The
median (IQR) time from requesting to receiving data was 88
days (130 days). The longest completed request took 831 days
(ie, >2 years). A mean of 23 emails (SD, 25; range, 4-49
emails) were sent until data were received. While some data
were shared in the requested format (26 trials [36%]), other
data sets had to be recoded (46 trials [64%]), and substantial
contact with the investigators was required for this. Workload and duration to set up data sharing agreements were reduced
if institutions had executed agreements together previously.
For 3 studies, data were not shared despite investigators
being eager to do so because institutional approval could not
be obtained. For iCOMP, 7 requests remained in progress
after 854 days; for TOPCHILD, 9 requests were in progress
after 272 days. Most data sharing agreements were similar in
content but varied in detail and length (3-36 pages). The
largest choke points included differences in regulations across
jurisdictions and varying stakeholder expectations of rights
and responsibilities (eg, institutional expectations about data
storage, authorship rights). However, most emails dealt with
minor change requests and clarifications.

**Conclusions** This study’s results demonstrate major delays
in the process of data sharing from trials with requests
remaining unresolved after 2 years. The similarities identified
across agreements indicate opportunities for standardization.
Data sharing delays consume financial resources and impair
the timeliness of research, which is particularly problematic
for research endeavors linked to emergency situations (such
as the COVID-19 pandemic). Many researchers are willing, or
required by journals and funders, to share their data. To
overcome costly choke points and delays, streamlined
standards and infrastructure are needed.

**Funding/Support** Anna Lene Seidler receives research funding
support from a National Health and Medical Research Council
(NHMRC) investigator grant (GNT2009432). Kylie E. Hunter
receives research funding support via 2 scholarships administered
by the University of Sydney (Postgraduate Research Supplementary
Scholarship in Methods Development [SC3504] and Research
Training Program Stipend [SC3227]). TOPCHILD is supported by
an NHMRC ideas grant (GNT1186363); iCOMP is supported by an
NHMRC project grant (GNT1163585).

**Role of the Funder/Sponsor** The funders had no role in the
design and conduct of the study; collection, management, analysis,
and interpretation of the data; preparation, review, or approval of
the abstract; and decision to submit the abstract for presentation.

**Acknowledgment** We acknowledge all members of the iCOMP
collaboration (https://www.icompstudy.org/) and TOPCHILD
collaboration (https://www.opchildcollaboration
.org/) for their assistance with preparing and executing data
sharing agreements and sharing their data despite the barriers they
encountered.

![](https://assets.underline.io/uploads/markdown_image/1/image/46993b5bed231f8f05cc012aa43e1e8e.png)

Assessment of Time and Resources Required to Share Data for 2 Individual Participant Data Meta-analyses

**Objective** Sharing data requested by contacting the
corresponding author is a good practice in research integrity
and highly expected by authors, but it can yield erratic results
when used in systematic reviews.1Bibliometric factors are
indirect measures of scientific report and research quality.
The objective of this study was to assess whether bibliometric
factors were associated with the availability and sharing of
data requested for a previous systematic review.

**Design** This was an analysis of a cross-sectional study of
studies included in a previous systematic review performed
by the same author group in 2021, which was aimed to assess
the prevalence of childhood obesity in Brazil.2Standard
methods were followed for identifying and including studies,
which were all assessed for methodological quality.2
In cases where data were needed for the analysis, the study’s authors
were contacted and the outcome of the request was
assessed.2,3 This analysis included studies with authors who
were contacted to request needed data from April 2018 to
May 2020.3The total number of citations on Google Scholar,
the Journal Citation Reports 2020 Impact Factor (JIF), and
the language(s) that the main report was published in were
collected to September 2021. The outcome was success in
receiving the requested data, and the association with studies’
bibliometric factors was investigated. The t test was used to
assess the association of the outcome with the mean number
of citations and JIF, and Pearson χ2 or Fishers exact tests
were used to test for language. We used Stata, version 14.2
(StataCorp LLC) for all calculations.

**Results** Of the 9394 retrieved records, 163 study authors
were contacted and 51 studies’ authors sent the requested
data. The mean (SD) number of citations was higher in
studies that failed to send data (50.5 [63.0]; 112 studies) than
in studies that sent requested data (31.8 [37.0]; 51 studies),
but this difference was not statistically different (P = .05). For
97 studies published in journals with a JIF, no difference was
observed according to success (2.3 [1.1]; 31 studies) or failure
(2.2 [1.3]; 66 studies) (P = .69). Success was significantly
lower in studies published in Portuguese (28 of 109 studies
[25.7%]) than in other languages (23 of 54 studies [42.6%])
(P = .03), and no difference in success was observed for
studies published in English (33 of 94 studies [35.1%] vs 18 of
69 studies [26.1%]; P = .22) and Spanish (1 of 7 studies
[14.3%] vs 50 of 156 studies [32.1%]; P = .44) in comparison
with other languages (**Table 57**).

![](https://assets.underline.io/uploads/markdown_image/1/image/43a7110b62f66680d527963d29300dc0.png)

**Conclusions** Despite representing quality of scientific
reporting, bibliometric factors such as number of citations
and JIF were not associated with the success of obtaining
data through contacting the author. Studies published in
Portuguese were less likely to share the requested data,
possibly reflecting less involvement in research
dissemination. Availability of full data sets should be
encouraged for all scientific publications to improve value and
reduce waste on research.

**References**
1. Meursinge Reynders R, Ladu L, Di Girolamo N. Contacting
of authors modified crucial outcomes of systematic reviews but was poorly reported, not systematic, and produced
conflicting results. J Clin Epidemiol. 2019;115:64-76.

2. Ferreira CM, Reis NDD, Castro AO, et al. Prevalence of
childhood obesity in Brazil: systematic review and meta-
analysis. J Pediatr (Rio J). 2021;97(5):490-499.

3. Dutra dos Reis N, Müller Ferreira C, Silva MT, Galvão TF.
Frequency of receiving requested data for a systematic review
and associated factors: a cross-sectional study. Account Res.
2022;29(3):165-177.

**Conflict of Interest Disclosures** None reported.

**Funding/Support** This work was supported by the National
Council for Scientific and Technological Development (CNPq)
under grant 4408652017-4. Taís F. Galvão receives productivity
scholarship from CNPq (grant 3064482017-7).

![](https://assets.underline.io/uploads/markdown_image/1/image/90f51d73f7fc985708ed2268df6c2237.png)



Bibliometric and Language Factors Associated With Studies With Authors Who Share Data Requested for a Systematic Review

**Objective** Following guidance on data sharing from the
International Committee of Medical Journal Editors,1 Takeda
requires the inclusion of a data sharing statement in most
manuscripts reporting results from interventional clinical
trials. The standard version of this statement indicates that
deidentified patient data will be made available within 3
months to researchers who provide a methodologically sound
proposal. The implementation of this policy for data sharing
by request was assessed by reviewing published articles to determine whether a data sharing statement was included,
modified, or not included, and the reason(s) for not sharing
data were identified.

**Design** To identify articles for inclusion in this study, an
internal publication management system was used. Articles
published online between July 2020 and November 2021
reporting primary or secondary analyses from clinical trials
sponsored by Takeda and reviewed by an internal clinical trial
transparency (CTT) team were included in this analysis. Each
article was assigned to 1 of the following categories: inclusion
of standard data sharing statement, inclusion of modified
data sharing statement, statement indicating there is no plan
to share data, or no data sharing statement.

**Results** A total of 36 interventional clinical trial manuscripts
reviewed by the CTT team were included in the analysis. Of
these, 26 (72%) included a statement outlining data
availability: 11 (31%) used the recommended standard data
sharing statement as outlined in the internal policy, while 15
(42%) contained a modified statement on data availability,
ranging from minor editorial amendments (generally
consistent with the standard statement) to substantial
differences in wording (due to specific journal requirements)
(**Figure 24**). Only 2 articles (6%) contained a statement
indicating that there was no plan to share the data—both were
reporting results from rare disease studies involving very
small numbers of patients, and the reason was concern
regarding the risk of patient reidentification due to the
number of patients. No data sharing statement was included
in 8 articles (22%) for various reasons (**Figure 24**). Of the
journals that published articles without a data sharing
statement, 3 had policies requiring inclusion of a data sharing
statement, while the others had policies allowing and/or
encouraging inclusion of a data sharing statement.

![](https://assets.underline.io/uploads/markdown_image/1/image/54d6a20668a6320b5acb29de3cdbcb27.png)

**Conclusions** Sharing underlying data sets of published
studies is important to promote transparency and facilitate
new research. Following the adoption of a standardized
approach to data sharing by request, most interventional
clinical trial articles in this analysis contained a data sharing
statement. In a few cases (n = 2), the statement indicated that data would not be shared to protect patient privacy in
situations in which deidentification of patient-level data was
not possible.

**Reference**

1. Taichman DB, Sahni P, Pinborg A, et al. Data sharing
statements for clinical trials: a requirement of the
International Committee of Medical Journal Editors. Ann
Intern Med. 2017;167(1):63-65. doi:10.7326/M17-1028
1Takeda Pharmaceuticals International AG, Zürich, Switzerland;
2Takeda Development Center Americas, Inc, Cambridge, MA, USA,
jesse.potash@takeda.com; 

**Funding/Support** This study was sponsored by Takeda
Development Center Americas, Inc.

**Role of the Funder/Sponsor** The sponsor played a role in design
and conduct of the study; collection, management, analysis, and
interpretation of the data; preparation, review, or approval of the
abstract; and decision to submit the abstract for presentation.

![](https://assets.underline.io/uploads/markdown_image/1/image/d566022d4c53ea6c7d9d5d08386723be.png)



Data Sharing Statement Modifications in Manuscripts Reporting Interventional Clinical Trials Sponsored by a Global Biopharmaceutical Company

**Objective** Asthma disproportionately affects historically
marginalized racial and ethnic populations in the US.1
However, these populations have been reported to be
underrepresented in clinical trials,2limiting generalizability
of study conclusions. The aim of this study was to examine
enrollment and representativeness of study populations in
contemporary asthma clinical trials.

**Design** A systematic search of the PubMed database was
performed to identify randomized clinical trials enrolling 100
or more individuals aged 18 years or older with asthma living
in the US that were published between January 1, 2015, and
December 31, 2021. Exclusion criteria included trials in which
asthma was not the major disease, international trials, and
secondary analyses or meta-analyses of primary trials.
Qualifying trials were abstracted for basic trial information,
study design, and baseline epidemiological characteristics of
the participants. To evaluate representativeness of study
populations compared with Centers for Disease Control and
Prevention epidemiological data for people with asthma,
standardized mean differences using Cohen d effect size were
calculated; underrepresentation and overrepresentation were
defined as the proportions of enrolled participants that were 1or less SD and 1 or more SD of national proportions,
respectively.

**Results** Of the 1032 trials screened, 35 met inclusion criteria
(with the majority excluded due to international enrollment).
The trials included a median of 311 participants (IQR,
167-496 participants). Approximately half of the trials were
drug intervention trials, and the remainder investigated
educational or behavioral interventions. There was a mix of
funding sources, including pharmaceutical, government,
academic, and private institutions. Almost all of the trials
reported age and sex distribution of the participants. A total
of 29 trials (82.9%) reported race or ethnicity. Only 12
(34.3%) and 10 (28.6%) trials reported educational and
income levels, respectively (**Table 58**). With respect to
representativeness of the study populations, among trials
reporting participant sex, 1 of 33 (3.0%) had a proportion of
females that was overrepresentative of the US population
with asthma and no trials were underrepresentative. Among
trials reporting Black race, 5 of 25 (20.0%) enrolled a
proportion of Black participants that was overrepresentative
of the US population with asthma and no trials were
underrepresentative. Among trials reporting Hispanic
ethnicity, 1 of 16 (6.25%) was overrepresentative and no trials
were underrepresentative. Among trials reporting White race,
4 of 27 (14.8%) enrolled proportions that were underrepresentative of the US population with asthma and no
trials were overrepresentative.

![](https://assets.underline.io/uploads/markdown_image/1/image/f860b2af77a9347662e5170776e9f423.png)

**Conclusions** In contemporary clinical trials of adults with
asthma in the US, the majority of trials reported participants’
age, sex, and race and fewer reported education and income
information. The study did not find that historically
marginalized groups were systematically underrepresented in
asthma clinical trials. Collecting and reporting patients’
demographic and socioeconomic characteristics is crucial to
understanding and generalizing trial results.

**References**

1. Asthma and Allergy Foundation of America. Asthma
disparities in America. Accessed February 25, 2022. https://
www.aafa.org/asthma-disparities-burden-on-minorities.aspx
2. Downing NS, Shah ND, Neiman JH, Aminawung JA,
Krumholz HM, Ross JS. Participation of the elderly, women,
and minorities in pivotal trials supporting 2011-2013 US Food
and Drug Administration approvals. Trials. 2016;17(1):199.
doi:10.1186/s13063-016-1322-4

![](https://assets.underline.io/uploads/markdown_image/1/image/c568a17467730838458acdb81418513f.png)



Enrollment and Representativeness in Contemporary Asthma Clinical Trials

**Objective** Gender disparities have been shown to have
increased during the COVID-19 pandemic at several levels in
the research process, including in the submission and
publication of biomedical research articles.1-3 One study also
reported an increase in the rate of women declining
invitations to peer review biomedical research in the very
early pandemic period.3
However, women’s response to peer
review invitations during the longer term of the COVID-19
pandemic remains unknown. In this study, response to peer
review invitations was explored using later COVID-19 data.

**Design** This was a retrospective cohort study of research
manuscripts submitted to and sent for peer review at 21
biomedical journals from the BMJ Publishing Group from
January 1, 2018, to May 31, 2021. Data were collected on the
gender and geographic affiliation of the handling editor, the
reviewers, and the last author; the journal’s impact factor and
peer review process (open vs anonymized); and the
manuscript topic (COVID-19−related or not).1The primary outcome was response (agreed vs did not agree) to the review
invitation. Multivariable mixed-effects logistic regression was
performed with random factors on the intercept at journal
and manuscript levels.

**Results** A total of 33,342 manuscripts were included;
257,025 reviewers were invited to review and 90,467 (35.2%)
agreed. Mean (SD) number of invited and agreed reviewers by manuscript were 7.7 (5.6) and 2.7 (1.2), respectively.
Multivariable analysis showed that agreement to review was
associated significantly with time period and COVID-19 as a
topic (P < .001). Women agreed to review less frequently than
men at any time period or COVD-19−related topic: odds
ratios, 0.93 (95% CI, 0.90-0.95) in prepandemic, 0.82 (95%
CI, 0.74-0.91) in January 2020 to January 2021 for
COVID-19−related manuscripts, 0.89 (95% CI, 0.85-0.92) in
January 2020 to January 2021 for non-COVID-19−related
manuscripts, 0.81 (95% CI, 0.71-0.93) in February 2021 to
February 2022 for COVID-19−related manuscripts, and 0.91
(95% CI, 0.86-0.97) in February 2021 to February 2022 for
non−COVID-19−related manuscripts. Interaction between
reviewers’ gender, time period, or COVID-19 topic and
agreement to review was significant (P = .049). Women
agreed significantly less often than men to review COVID-19−
related manuscripts during the first year of the pandemic
compared with the prepandemic period. Agreement to review
was lower when the handling editor was a woman compared
with a man: odds ratio, 0.96 (95% CI, 0.93-0.99) (**Table 59**).

![](https://assets.underline.io/uploads/markdown_image/1/image/c7301cc4bb668751e7fca2f303ca22b6.png)

**Conclusions** For both women and men reviewers,
agreement to peer review was higher for COVID-19−related
manuscripts compared with the prepandemic period.
However, the representativeness of women researchers
among invited reviewers was below parity. Moreover, women
refused more frequently than men to participate in peer
review. More generally, women’s points of views need to be
fostered to have diverse vision in research. Editors should
ensure a fair parity in the invitation to peer review or increase
the proportion of women invited to be able to obtain parity
during peer review.

**References**
1. Gayet-Ageron A, Ben Messaoud K, Richards M, Schroter S.
Women authorship of COVID-19 research in manuscripts
submitted to 11 biomedical journals: cross sectional study.
BMJ. 2021;375:n2288.
2. Larivière V, Ni C, Gingras Y, Cronin B, Sugimoto CR.
Bibliometrics: global gender disparities in science. Nature.
2013;504(7479):211‐3.
3. Squazzoni F, Bravo G, Grimaldo F, García-Costa D, Farjam
M, Mehmani B. Gender gap in journal submissions and peer
review during the first wave of the COVID-19 pandemic: a
study on 2329 Elsevier journals. PLOS ONE.
2021;16(10):e0257919.

**Conflict of Interest Disclosures** The authors declare support
from the University Hospitals of Geneva, Geneva Medical School,
and the Swiss National Science Foundation for the submitted
work. Sara Schroter and Mark Richards are employees of the BMJ
Publishing Group. No other disclosures were reported.

**Funding/Support** This study was supported by a grant from the
Swiss National Science Foundation (No. 192374).

**Role of the Funder/Sponsor** The funder had no role in
considering the study design or in the collection, analysis, or
interpretation of data; the writing of the abstract; or the decision to
submit the abstract for presentation.

![](https://assets.underline.io/uploads/markdown_image/1/image/22fbb3282b687d4252f1e89e761d4b67.png)

Numbers and Trends in Authorship of Published Meta-analyses, 1990-2019

Next from Peer Review Congress 2022

Development of the Quality Assessment of Prognostic Accuracy Studies (QUAPAS) Tool for Assessing Risk of Bias in Prognostic Accuracy Studies

Similar lecture

Charismetrics: winning researcher hearts and minds with the Research Intelligence service at Lancaster University

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES