The grateful scientist: what determines the presence of acknowledgements in randomised clinical trial publications?

2018 ◽  
Author(s):  
Herm J Lamberink ◽  
Christiaan Vinkers ◽  
Willem M. Otte ◽  
Joeri K. Tijdink
Keyword(s):  
Clinical Trials ◽  
Impact Factor ◽  
Full Text ◽  
Randomised Clinical Trial ◽  
Randomised Clinical Trials ◽  
Medical Field ◽  
Research Institution ◽  
Collaborative Efforts ◽  
Journal Impact ◽  
Surgical Journals

Objective Randomised clinical trials (RCTs) are complex endeavours that demand extensive collaborative efforts from researchers, institutions, and funding partners. Undoubtedly, there is ample reason to acknowledge these efforts and to be grateful for publication of the results. However, some RCTs explicitly express gratitude in an acknowledgment section whereas other do not. We hypothesized that this would be related to author’s gender and religion, medical field, journal, and year of publication. DesignQuantitative analysis of all available full-text randomised clinical trials identified through PubMed.Methods We determined the presence of an acknowledgment section containing explicit words of gratitude in 90,163 full-text publications. The hypotheses were publicly pre-registered before study conduct. We tested the following determinants of the presence of these acknowledgment sections: gender of the first and last author, the percentage of protestant inhabitants in the country of the primary research institution, the year of publication, journal impact factor (JIF), the journal’s medical field (compared to the medical field of surgery). Explorative analyses were performed on the different determinants that were associated with received gratitude in the acknowledgement sections. Main outcome measureThe presence of an acknowledgment section with explicit words of gratitude.Results In total, 28,897 (32%) RCT publications contained an acknowledgement section with explicit words of gratitude. All hypotheses were confirmed, with a higher likelihood of an acknowledgement section with words of gratitude when the first and/or last author was female (OR 1.28 95% CI 1.24-1.31), an increased percentage of protestant inhabitants in the country of the first author’s affiliation (+ 10%; OR = 1.04 95% CI 1.04-1.05), and more recent publication (+ 1 year; OR 1.04 95% CI 1.04-1.05). The journal’s impact factor (- 1 JIF; OR = 0.99 95% CI 0.99-0.99) and RCTs published in surgical journals (OR 0.35 95% CI 0.32-0.38) were associated with a lower likelihood of RCT publications containing words of gratitude. Conclusions Acknowledgement sections with explicit words of gratefulness are more frequently present when researchers are female, from protestant countries, working in non-surgical fields, and published in lower impact factor journals, and this trend has increased over time. To foster a healthy and responsible publication culture, it is important that all individuals, institutions, and groups that have contributed to the research are acknowledged. Credit should go where credit is due, and Christmas is the most suitable period to remind us of the importance of gratitude.

scholarly journals Assessing gaps in cholesterol treatment guidelines for primary prevention of cardiovascular disease based on available randomised clinical trial evidence: The Rotterdam Study

2017 ◽  
Vol 25 (4) ◽  
pp. 420-431 ◽  
Author(s):  
Jelena Pavlović ◽  
Philip Greenland ◽  
Jaap W Deckers ◽  
Maryam Kavousi ◽  
Albert Hofman ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Primary Prevention ◽  
Randomised Clinical Trial ◽  
Lipid Lowering ◽  
Randomised Clinical Trials ◽  
Atherosclerotic Cardiovascular Disease ◽  
Intermediate Risk ◽  
Clinical Trial Evidence

Background The purpose of this study was to determine how American College of Cardiology/American Heart Association (ACC/AHA) 2013 and European Society of Cardiology 2016 guidelines for the primary prevention of atherosclerotic cardiovascular disease (CVD) compare in reflecting the totality of accrued randomised clinical trial evidence for statin treatment at population level. Methods From 1997–2008, 7279 participants aged 45–75 years, free of atherosclerotic cardiovascular disease, from the population-based Rotterdam Study were included. For each participant, we compared eligibility for each one of 11 randomised clinical trials on statin use in primary prevention of CVD, with recommendations on lipid-lowering therapy from the ACC/AHA and European Society of Cardiology (ESC) guidelines. Atherosclerotic cardiovascular disease incidence and cardiovascular disease mortality rates were calculated. Results The proportion of participants eligible for each trial ranged from 0.4% for ALLHAT-LLT to 30.8% for MEGA. The likelihood of being recommended for lipid-lowering treatment was lowest for those eligible for low-to-intermediate risk RCTs (HOPE-3, MEGA, and JUPITER), and highest for high-risk individuals with diabetes (MRC/BHF HPS, CARDS, and ASPEN) or elderly PROSPER. Eligibility for an increasing number of randomised clinical trials correlated with a greater likelihood of being recommended lipid-lowering treatment by either guideline ( p < 0.001 for both guidelines). Conclusion Compared to RCTs done in high risk populations, randomised clinical trials targeting low-to-intermediate risk populations are less well-reflected in the ACC/AHA, and even less so in the ESC guideline recommendations. Importantly, the low-to-intermediate risk population targeted by HOPE-3, the most recent randomised clinical trial in this field, is not well-captured by the current European prevention guidelines and should be specifically considered in future iterations of the guidelines.

scholarly journals Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation intervention

2020 ◽  
Author(s):  
Ravinder Claire ◽  
Christian Gluud ◽  
Ivan Berlin ◽  
Tim Coleman ◽  
Jo Leonardi-Bee
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Sample Size ◽  
Sequential Analysis ◽  
Randomised Clinical Trial ◽  
Randomised Clinical Trials ◽  
Trial Sequential Analysis ◽  
Analysis Software ◽  
Cessation Intervention ◽  
Pilot Trials

Abstract Background Assessing benefits and harms of health interventions is resource-intensive and often requires feasibility and pilot trials followed by adequately powered randomised clinical trials. Data from feasibility and pilot trials are used to inform the design and sample size of the adequately powered randomised clinical trials. When a randomised clinical trial is conducted, results from feasibility and pilot trials may be disregarded in terms of benefits and harms.MethodsWe describe using feasibility and pilot trial data in the Trial Sequential Analysis software to estimate the required sample size for one or more trials investigating a behavioural smoking cessation intervention. We show how data from a new, planned trial can be combined with data from the earlier trials using trial sequential analysis methods to assess the intervention’s effects.ResultsWe provide a worked example to illustrate how we successfully used the Trial Sequential Analysis software to arrive at a sensible sample size for a new randomised clinical trial and use it in the argumentation for research funds for the trial. ConclusionsTrial Sequential Analysis can utilise data from feasibility and pilot trials as well as other trials, to estimate a sample size for one or more, similarly designed, future randomised clinical trials. As this method uses available data, estimated sample sizes may be smaller than they would have been using conventional sample size estimation methods.

Use of docetaxel in low- and high-burden metastatic hormone-sensitive prostate cancer: A systematic review and assessment of subgroup analyses

2021 ◽  
Vol 27 (7) ◽  
pp. 1743-1750
Author(s):  
Manuel David Gil-Sierra ◽  
Emilio Jesus Alegre-del Rey ◽  
Catalina Alarcon de la Lastra-Romero ◽  
Marina Sánchez-Hidalgo
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Clinical Trials ◽  
Metastatic Disease ◽  
Subgroup Analysis ◽  
Randomised Clinical Trial ◽  
Randomised Clinical Trials ◽  
High Burden ◽  
Subgroup Analyses ◽  
Hormone Sensitive

Background Use of docetaxel in low- and high-burden metastatic hormone-sensitive prostate cancer presents considerable controversy. There is literature suggesting lack of benefit for low-volume of metastases. Objective The study aims to develop a systematic review and methodological assessment of subset analysis about use of docetaxel in metastatic hormone-sensitive prostate cancer regarding volume of metastatic disease. Methods A systematic review in the Pubmed® database was conducted up to 25 September 2020. A reference tracking was also developed. Randomised clinical trials with subgroup analysis according volume of metastatic disease for overall survival were selected. Two methodologies were used. One of them considered statistical interaction of subsets ( p(i) < 0.1), pre-specification, biological plausibility and consistency among subset results of similar randomised clinical trials. The second methodology was a two-part validated tool: preliminary questions to discard subset analysis without minimal relevance and a checklist The checklist provides recommendations for applicability of subgroup analysis in clinical practice. Results A total of 31 results were found in systematic reviews in the Pubmed® database. One result was identified in the reference tracking. Of the total of 32 results, four randomised clinical trials were included in the study. About first methodology, statistical interaction among subgroups was obtained in one randomised clinical trial. Subgroup analysis was pre-specified in two randomised clinical trials. Biological plausibility was reasonable. No external consistency among results of subgroup analyses in randomised clinical trials was observed. Preliminary questions of second methodology rejected applicability of subgroup analysis in three randomised clinical trials. A ‘null’ recommendation for applicability of subset results was obtained in the remaining randomised clinical trial. Conclusions Patients with low- and high-burden metastatic hormone-sensitive prostate cancer would benefit from docetaxel therapy. No consistent differences for overall survival were observed in subgroup analyses regarding volume of metastatic disease.

scholarly journals Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation intervention

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ravinder Claire ◽  
Christian Gluud ◽  
Ivan Berlin ◽  
Tim Coleman ◽  
Jo Leonardi-Bee
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Sample Size ◽  
Sequential Analysis ◽  
Randomised Clinical Trial ◽  
Randomised Clinical Trials ◽  
Trial Sequential Analysis ◽  
Analysis Software ◽  
Cessation Intervention ◽  
Pilot Trials

Abstract Background Assessing benefits and harms of health interventions is resource-intensive and often requires feasibility and pilot trials followed by adequately powered randomised clinical trials. Data from feasibility and pilot trials are used to inform the design and sample size of the adequately powered randomised clinical trials. When a randomised clinical trial is conducted, results from feasibility and pilot trials may be disregarded in terms of benefits and harms. Methods We describe using feasibility and pilot trial data in the Trial Sequential Analysis software to estimate the required sample size for one or more trials investigating a behavioural smoking cessation intervention. We show how data from a new, planned trial can be combined with data from the earlier trials using trial sequential analysis methods to assess the intervention’s effects. Results We provide a worked example to illustrate how we successfully used the Trial Sequential Analysis software to arrive at a sensible sample size for a new randomised clinical trial and use it in the argumentation for research funds for the trial. Conclusions Trial Sequential Analysis can utilise data from feasibility and pilot trials as well as other trials, to estimate a sample size for one or more, similarly designed, future randomised clinical trials. As this method uses available data, estimated sample sizes may be smaller than they would have been using conventional sample size estimation methods.

Is the trend to publish reviews and clinical trials related to the journal impact factor? Analysis in dentistry field

2019 ◽  
Vol 26 (7) ◽  
pp. 427-438
Author(s):  
Ángel Valderrama ◽  
Evaristo Jiménez-Contreras ◽  
Pilar Valderrama ◽  
Manuel Escabias ◽  
Pilar Baca
Keyword(s):  
Clinical Trials ◽  
Factor Analysis ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Journal Impact

scholarly journals Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation intervention

2020 ◽  
Author(s):  
Ravinder Claire ◽  
Christian Gluud ◽  
Ivan Berlin ◽  
Tim Coleman ◽  
Jo Leonardi-Bee
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Sample Size ◽  
Sequential Analysis ◽  
Randomised Clinical Trial ◽  
Randomised Clinical Trials ◽  
Trial Sequential Analysis ◽  
Analysis Software ◽  
Cessation Intervention ◽  
Pilot Trials

Abstract Background: Assessing benefits and harms of health interventions is resource-intensive and often requires feasibility and pilot trials followed by adequately powered randomised clinical trials. Data from feasibility and pilot trials are used to inform the design and sample size of the adequately powered randomised clinical trials. When a randomised clinical trial is conducted, results from feasibility and pilot trials may be disregarded in terms of benefits and harms.Methods: We describe using feasibility and pilot trial data in the Trial Sequential Analysis software to estimate the required sample size for one or more trials investigating a behavioural smoking cessation intervention. We show how data from a new, planned trial can be combined with data from the earlier trials using trial sequential analysis methods to assess the intervention's effects. Results: We provide a worked example to illustrate how we successfully used the Trial Sequential Analysis software to arrive at a sensible sample size for a new randomised clinical trial and use it in the argumentation for research funds for the trial. Conclusions: Trial Sequential Analysis can utilise data from feasibility and pilot trials as well as other trials, to estimate a sample size for one or more, similarly designed, future randomised clinical trials. As this method uses available data, estimated sample sizes may be smaller than they would have been using conventional sample size estimation methods.

scholarly journals Research transparency promotion by surgical journals publishing randomised controlled trials: a survey

2020 ◽  
Author(s):  
Nicolas Lombard ◽  
Anis Gasmi ◽  
Laurent Sulpice ◽  
Karim Boudjema ◽  
Florian Naudet ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Impact Factor ◽  
Data Sharing ◽  
Controlled Trial ◽  
International Committee ◽  
Primary Objective ◽  
Impact Factors ◽  
Specific Reference ◽  
Research Transparency ◽  
Surgical Journals

Abstract Objective: To describe surgical journals’ position statements on data-sharing policies (primary objective) and to describe key features of their research transparency promotion.Methods: Only “SURGICAL” journals with an impact factor higher than 2 (Web of Science) were eligible for the study. They were included, if there were explicit instructions for clinical trial publication in the official instructions for authors, (OIA) and or if they had published randomized controlled trial (RCT) between 1st January 2016 and 31st December 2018. The primary outcome was the existence of a data-sharing policy included in the instructions for authors. Data sharing policies were grouped into 3 categories, inclusion of data sharing policy mandatory, optional or not available. Details on research transparency promotion were also collected, namely the existence of a “prospective registration of clinical trials requirement policy”; a conflict of interests (COIs) disclosure requirement and a specific reference to reporting guidelines, such as CONSORT for RCT. Results: Among the 87 surgical journals identified, 82 were included in the study: 67 (82%) had explicit instructions for RCT and the remaining 15 (18%) had published at least one RCT. The median impact factor was 2.98 [IQR=2.48-3.77] and in 2016 and 2017, the journals published a median of 11.5 RCT [IQR=5-20.75]. The OIA of four journals (5%) stated that the inclusion of a data sharing statement was mandatory, optional in 45% (n=37), and not included in 50% (n=41).No association was found between journal characteristics and the existence of data-sharing policies (mandatory or optional). A “prospective registration of clinical trials requirement” was associated with International Committee of Medical Journal Editors (ICMJE) allusion or affiliation and higher impact factors. Journals with specific RCT instructions in their OIA and journals referenced on the ICMJE website more frequently mandated the use of CONSORT guidelines. Conclusion: Research transparency promotion is still limited in surgical journals. Standardisation of journal requirements according to ICMJE guidelines could be a first step forward for research transparency promotion in surgery.

scholarly journals Research transparency promotion by surgical journals publishing randomised controlled trials: a survey

2020 ◽  
Author(s):  
Nicolas Lombard ◽  
Anis Gasmi ◽  
Laurent Sulpice ◽  
Karim Boudjema ◽  
Florian Naudet ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Impact Factor ◽  
Data Sharing ◽  
Primary Outcome ◽  
Controlled Trial ◽  
Primary Objective ◽  
Impact Factors ◽  
Specific Reference ◽  
Research Transparency ◽  
Surgical Journals

Abstract Objective: To describe the surgical journal position statement on data-sharing policies (primary objective) and to describe the other features of their research transparency promotion. Methods: Only “SURGICAL” journals with an impact factor superior to 2 (Web of Science) were eligible for the study. They were not included if there were no explicit instructions for clinical trial publication in the official instructions for authors (OIA) and if there were no randomized controlled trial (RCT) published between 1 st January 2016 and 1 st January 2019. The primary outcome was the existence of a data-sharing policy in the instructions for authors. Data sharing policy was detailed in 3 categories, the International committee of medical journal editors (ICMJE) compliant, optional or inexistent. Details on research transparency promotion were also collected, namely the existence of a “prospective registration of clinical trials requirement” policy; a conflict of interests (COIs) disclosure requirement and a specific reference to reporting guidelines such as CONSORT for RCT. Results: Among the 87 surgical journals eligible, 82 were included in the study: 67 (82%) had explicit instructions for RCT and of the remaining, 15 (18%) had published at least one RCT. The median impact factor was 2.98 [IQR=2.48-3.77] and in 2016 and 2017, the journals published a median of 11.5 RCT [IQR=5-20.75]. Data-sharing statement instructions (primary outcome) was retrieved in 41 journals (50%); Data-sharing statement instructions were ICMJE compliant in four cases (4.9%), optional in 45% (n=37) and inexistent in 50% (n=41) of the journals. As for data-sharing statements, no association was found between journal characteristics and the existence of data-sharing policies (ICMJE-compliant or optional). A “prospective registration of clinical trials requirement” was associated with ICMJE allusion or affiliation and higher impact factors. Journals with specific RCT instructions in their OIA and journals referenced on the ICMJE website more frequently mandated the use of CONSORT guidelines. Conclusion: Research transparency promotion is still limited in surgical journals. Standardisation of journal requirements according to ICMJE guidelines could be a first step forward for research transparency promotion in surgery.

Sign in / Sign up

Export Citation Format

Share Document