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Ghosn L, Assi R, Evrenoglou T, Buckley BS, Henschke N, Probyn K, Riveros C, Davidson M, Graña C, Bonnet H, Jarde A, Ávila C, Nejstgaard CH, Menon S, Ferrand G, Kapp P, Breuer C, Schmucker C, Sguassero Y, Nguyen TV, Devane D, Meerpohl JJ, Rada G, Hróbjartsson A, Grasselli G, Tovey D, Ravaud P, Chaimani A, Boutron I. Interleukin-6 blocking agents for treating COVID-19: a living systematic review. Cochrane Database Syst Rev 2023; 6:CD013881. [PMID: 37260086 PMCID: PMC10237088 DOI: 10.1002/14651858.cd013881.pub2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
BACKGROUND It has been reported that people with COVID-19 and pre-existing autoantibodies against type I interferons are likely to develop an inflammatory cytokine storm responsible for severe respiratory symptoms. Since interleukin 6 (IL-6) is one of the cytokines released during this inflammatory process, IL-6 blocking agents have been used for treating people with severe COVID-19. OBJECTIVES To update the evidence on the effectiveness and safety of IL-6 blocking agents compared to standard care alone or to a placebo for people with COVID-19. SEARCH METHODS We searched the World Health Organization (WHO) International Clinical Trials Registry Platform, the Living OVerview of Evidence (L·OVE) platform, and the Cochrane COVID-19 Study Register to identify studies on 7 June 2022. SELECTION CRITERIA We included randomized controlled trials (RCTs) evaluating IL-6 blocking agents compared to standard care alone or to placebo for people with COVID-19, regardless of disease severity. DATA COLLECTION AND ANALYSIS Pairs of researchers independently conducted study selection, extracted data and assessed risk of bias. We assessed the certainty of evidence using the GRADE approach for all critical and important outcomes. In this update we amended our protocol to update the methods used for grading evidence by establishing minimal important differences for the critical outcomes. MAIN RESULTS This update includes 22 additional trials, for a total of 32 trials including 12,160 randomized participants all hospitalized for COVID-19 disease. We identified a further 17 registered RCTs evaluating IL-6 blocking agents without results available as of 7 June 2022. The mean age range varied from 56 to 75 years; 66.2% (8051/12,160) of enrolled participants were men. One-third (11/32) of included trials were placebo-controlled. Twenty-two were published in peer-reviewed journals, three were reported as preprints, two trials had results posted only on registries, and results from five trials were retrieved from another meta-analysis. Eight were funded by pharmaceutical companies. Twenty-six included studies were multicenter trials; four were multinational and 22 took place in single countries. Recruitment of participants occurred between February 2020 and June 2021, with a mean enrollment duration of 21 weeks (range 1 to 54 weeks). Nineteen trials (60%) had a follow-up of 60 days or more. Disease severity ranged from mild to critical disease. The proportion of participants who were intubated at study inclusion also varied from 5% to 95%. Only six trials reported vaccination status; there were no vaccinated participants included in these trials, and 17 trials were conducted before vaccination was rolled out. We assessed a total of six treatments, each compared to placebo or standard care. Twenty trials assessed tocilizumab, nine assessed sarilumab, and two assessed clazakizumab. Only one trial was included for each of the other IL-6 blocking agents (siltuximab, olokizumab, and levilimab). Two trials assessed more than one treatment. Efficacy and safety of tocilizumab and sarilumab compared to standard care or placebo for treating COVID-19 At day (D) 28, tocilizumab and sarilumab probably result in little or no increase in clinical improvement (tocilizumab: risk ratio (RR) 1.05, 95% confidence interval (CI) 1.00 to 1.11; 15 RCTs, 6116 participants; moderate-certainty evidence; sarilumab: RR 0.99, 95% CI 0.94 to 1.05; 7 RCTs, 2425 participants; moderate-certainty evidence). For clinical improvement at ≥ D60, the certainty of evidence is very low for both tocilizumab (RR 1.10, 95% CI 0.81 to 1.48; 1 RCT, 97 participants; very low-certainty evidence) and sarilumab (RR 1.22, 95% CI 0.91 to 1.63; 2 RCTs, 239 participants; very low-certainty evidence). The effect of tocilizumab on the proportion of participants with a WHO Clinical Progression Score (WHO-CPS) of level 7 or above remains uncertain at D28 (RR 0.90, 95% CI 0.72 to 1.12; 13 RCTs, 2117 participants; low-certainty evidence) and that for sarilumab very uncertain (RR 1.10, 95% CI 0.90 to 1.33; 5 RCTs, 886 participants; very low-certainty evidence). Tocilizumab reduces all cause-mortality at D28 compared to standard care/placebo (RR 0.88, 95% CI 0.81 to 0.94; 18 RCTs, 7428 participants; high-certainty evidence). The evidence about the effect of sarilumab on this outcome is very uncertain (RR 1.06, 95% CI 0.86 to 1.30; 9 RCTs, 3305 participants; very low-certainty evidence). The evidence is uncertain for all cause-mortality at ≥ D60 for tocilizumab (RR 0.91, 95% CI 0.80 to 1.04; 9 RCTs, 2775 participants; low-certainty evidence) and very uncertain for sarilumab (RR 0.95, 95% CI 0.84 to 1.07; 6 RCTs, 3379 participants; very low-certainty evidence). Tocilizumab probably results in little to no difference in the risk of adverse events (RR 1.03, 95% CI 0.95 to 1.12; 9 RCTs, 1811 participants; moderate-certainty evidence). The evidence about adverse events for sarilumab is uncertain (RR 1.12, 95% CI 0.97 to 1.28; 4 RCT, 860 participants; low-certainty evidence). The evidence about serious adverse events is very uncertain for tocilizumab (RR 0.93, 95% CI 0.81 to 1.07; 16 RCTs; 2974 participants; very low-certainty evidence) and uncertain for sarilumab (RR 1.09, 95% CI 0.97 to 1.21; 6 RCTs; 2936 participants; low-certainty evidence). Efficacy and safety of clazakizumab, olokizumab, siltuximab and levilimab compared to standard care or placebo for treating COVID-19 The evidence about the effects of clazakizumab, olokizumab, siltuximab, and levilimab comes from only one or two studies for each blocking agent, and is uncertain or very uncertain. AUTHORS' CONCLUSIONS In hospitalized people with COVID-19, results show a beneficial effect of tocilizumab on all-cause mortality in the short term and probably little or no difference in the risk of adverse events compared to standard care alone or placebo. Nevertheless, both tocilizumab and sarilumab probably result in little or no increase in clinical improvement at D28. Evidence for an effect of sarilumab and the other IL-6 blocking agents on critical outcomes is uncertain or very uncertain. Most of the trials included in our review were done before the waves of different variants of concern and before vaccination was rolled out on a large scale. An additional 17 RCTs of IL-6 blocking agents are currently registered with no results yet reported. The number of pending studies and the number of participants planned is low. Consequently, we will not publish further updates of this review.
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Affiliation(s)
- Lina Ghosn
- Cochrane France, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004, Paris, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Rouba Assi
- Cochrane France, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004, Paris, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Theodoros Evrenoglou
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | | | | | | | - Carolina Riveros
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004, Paris, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Mauricia Davidson
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Carolina Graña
- Cochrane France, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004, Paris, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Hillary Bonnet
- Cochrane France, Paris, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Alexander Jarde
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | | | - Camilla Hansen Nejstgaard
- Centre for Evidence-Based Medicine Odense (CEBMO) and Cochrane Denmark, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Open Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | | | | | - Philipp Kapp
- Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Claudia Breuer
- Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany
| | - Christine Schmucker
- Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany
| | | | | | - Declan Devane
- Evidence Synthesis Ireland, Galway, Ireland
- Cochrane Ireland and HRB-Trials Methodology Research Network, Galway, Ireland
- University of Galway, Galway, Ireland
| | - Joerg J Meerpohl
- Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany
| | - Gabriel Rada
- Epistemonikos Foundation, Santiago, Chile
- UC Evidence Center, Cochrane Chile Associated Center, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Asbjørn Hróbjartsson
- Centre for Evidence-Based Medicine Odense (CEBMO) and Cochrane Denmark, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Open Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Giacomo Grasselli
- Department of Anesthesia, Intensive Care and Emergency Department of Anesthesia, Intensive Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | | | - Philippe Ravaud
- Cochrane France, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004, Paris, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Anna Chaimani
- Cochrane France, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004, Paris, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Isabelle Boutron
- Cochrane France, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004, Paris, France
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
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Evrenoglou T, Boutron I, Seitidis G, Ghosn L, Chaimani A. metaCOVID: A web-application for living meta-analyses of COVID-19 trials. Res Synth Methods 2023; 14:479-488. [PMID: 36772980 DOI: 10.1101/2021.09.07.21263207] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 01/07/2023] [Accepted: 02/07/2023] [Indexed: 05/27/2023]
Abstract
Outputs from living evidence syntheses projects have been used widely during the pandemic by guideline developers to form evidence-based recommendations. However, the needs of different stakeholders cannot be accommodated by solely providing pre-defined non amendable numerical summaries. Stakeholders also need to understand the data and perform their own exploratory analyses. This requires resources, time, statistical expertise, software knowledge as well as relevant clinical expertise to avoid spurious conclusions. To assist them, we created the metaCOVID application which, based on automation processes, facilitates the fast exploration of the data and the conduct of sub-analyses tailored to end-users needs. metaCOVID has been created in R and is freely available as an R-Shiny application. Based on the COVID-NMA platform (https://covid-nma.com/) the application conducts living meta-analyses of randomized controlled trials related to COVID-19 treatments and vaccines for several outcomes. Several options are available for subgroup and sensitivity analyses. The results are presented in downloadable forest plots. We illustrate metaCOVID through three examples involving well-known treatments and vaccines for COVID-19. The application is freely available from https://covid-nma.com/metacovid/.
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Affiliation(s)
- Theodoros Evrenoglou
- Centre of Research in Epidemiology and Statistics (CRESS-U1153), Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Paris, France
| | - Isabelle Boutron
- Centre of Research in Epidemiology and Statistics (CRESS-U1153), Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, Paris, France
| | - Georgios Seitidis
- Department of Primary Education, School of Education, University of Ioannina, Ioannina, Greece
| | - Lina Ghosn
- Centre of Research in Epidemiology and Statistics (CRESS-U1153), Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, Paris, France
| | - Anna Chaimani
- Centre of Research in Epidemiology and Statistics (CRESS-U1153), Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Paris, France
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Evrenoglou T, Boutron I, Seitidis G, Ghosn L, Chaimani A. metaCOVID: A web-application for living meta-analyses of COVID-19 trials. Res Synth Methods 2023; 14:479-488. [PMID: 36772980 DOI: 10.1002/jrsm.1627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 01/07/2023] [Accepted: 02/07/2023] [Indexed: 02/12/2023]
Abstract
Outputs from living evidence syntheses projects have been used widely during the pandemic by guideline developers to form evidence-based recommendations. However, the needs of different stakeholders cannot be accommodated by solely providing pre-defined non amendable numerical summaries. Stakeholders also need to understand the data and perform their own exploratory analyses. This requires resources, time, statistical expertise, software knowledge as well as relevant clinical expertise to avoid spurious conclusions. To assist them, we created the metaCOVID application which, based on automation processes, facilitates the fast exploration of the data and the conduct of sub-analyses tailored to end-users needs. metaCOVID has been created in R and is freely available as an R-Shiny application. Based on the COVID-NMA platform (https://covid-nma.com/) the application conducts living meta-analyses of randomized controlled trials related to COVID-19 treatments and vaccines for several outcomes. Several options are available for subgroup and sensitivity analyses. The results are presented in downloadable forest plots. We illustrate metaCOVID through three examples involving well-known treatments and vaccines for COVID-19. The application is freely available from https://covid-nma.com/metacovid/.
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Affiliation(s)
- Theodoros Evrenoglou
- Centre of Research in Epidemiology and Statistics (CRESS-U1153), Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Paris, France
| | - Isabelle Boutron
- Centre of Research in Epidemiology and Statistics (CRESS-U1153), Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, Paris, France
| | - Georgios Seitidis
- Department of Primary Education, School of Education, University of Ioannina, Ioannina, Greece
| | - Lina Ghosn
- Centre of Research in Epidemiology and Statistics (CRESS-U1153), Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, Paris, France
| | - Anna Chaimani
- Centre of Research in Epidemiology and Statistics (CRESS-U1153), Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Paris, France
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Graña C, Ghosn L, Evrenoglou T, Jarde A, Minozzi S, Bergman H, Buckley BS, Probyn K, Villanueva G, Henschke N, Bonnet H, Assi R, Menon S, Marti M, Devane D, Mallon P, Lelievre JD, Askie LM, Kredo T, Ferrand G, Davidson M, Riveros C, Tovey D, Meerpohl JJ, Grasselli G, Rada G, Hróbjartsson A, Ravaud P, Chaimani A, Boutron I. Efficacy and safety of COVID-19 vaccines. Cochrane Database Syst Rev 2022; 12:CD015477. [PMID: 36473651 PMCID: PMC9726273 DOI: 10.1002/14651858.cd015477] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Different forms of vaccines have been developed to prevent the SARS-CoV-2 virus and subsequent COVID-19 disease. Several are in widespread use globally. OBJECTIVES: To assess the efficacy and safety of COVID-19 vaccines (as a full primary vaccination series or a booster dose) against SARS-CoV-2. SEARCH METHODS We searched the Cochrane COVID-19 Study Register and the COVID-19 L·OVE platform (last search date 5 November 2021). We also searched the WHO International Clinical Trials Registry Platform, regulatory agency websites, and Retraction Watch. SELECTION CRITERIA We included randomized controlled trials (RCTs) comparing COVID-19 vaccines to placebo, no vaccine, other active vaccines, or other vaccine schedules. DATA COLLECTION AND ANALYSIS We used standard Cochrane methods. We used GRADE to assess the certainty of evidence for all except immunogenicity outcomes. We synthesized data for each vaccine separately and presented summary effect estimates with 95% confidence intervals (CIs). MAIN RESULTS: We included and analyzed 41 RCTs assessing 12 different vaccines, including homologous and heterologous vaccine schedules and the effect of booster doses. Thirty-two RCTs were multicentre and five were multinational. The sample sizes of RCTs were 60 to 44,325 participants. Participants were aged: 18 years or older in 36 RCTs; 12 years or older in one RCT; 12 to 17 years in two RCTs; and three to 17 years in two RCTs. Twenty-nine RCTs provided results for individuals aged over 60 years, and three RCTs included immunocompromized patients. No trials included pregnant women. Sixteen RCTs had two-month follow-up or less, 20 RCTs had two to six months, and five RCTs had greater than six to 12 months or less. Eighteen reports were based on preplanned interim analyses. Overall risk of bias was low for all outcomes in eight RCTs, while 33 had concerns for at least one outcome. We identified 343 registered RCTs with results not yet available. This abstract reports results for the critical outcomes of confirmed symptomatic COVID-19, severe and critical COVID-19, and serious adverse events only for the 10 WHO-approved vaccines. For remaining outcomes and vaccines, see main text. The evidence for mortality was generally sparse and of low or very low certainty for all WHO-approved vaccines, except AD26.COV2.S (Janssen), which probably reduces the risk of all-cause mortality (risk ratio (RR) 0.25, 95% CI 0.09 to 0.67; 1 RCT, 43,783 participants; high-certainty evidence). Confirmed symptomatic COVID-19 High-certainty evidence found that BNT162b2 (BioNtech/Fosun Pharma/Pfizer), mRNA-1273 (ModernaTx), ChAdOx1 (Oxford/AstraZeneca), Ad26.COV2.S, BBIBP-CorV (Sinopharm-Beijing), and BBV152 (Bharat Biotect) reduce the incidence of symptomatic COVID-19 compared to placebo (vaccine efficacy (VE): BNT162b2: 97.84%, 95% CI 44.25% to 99.92%; 2 RCTs, 44,077 participants; mRNA-1273: 93.20%, 95% CI 91.06% to 94.83%; 2 RCTs, 31,632 participants; ChAdOx1: 70.23%, 95% CI 62.10% to 76.62%; 2 RCTs, 43,390 participants; Ad26.COV2.S: 66.90%, 95% CI 59.10% to 73.40%; 1 RCT, 39,058 participants; BBIBP-CorV: 78.10%, 95% CI 64.80% to 86.30%; 1 RCT, 25,463 participants; BBV152: 77.80%, 95% CI 65.20% to 86.40%; 1 RCT, 16,973 participants). Moderate-certainty evidence found that NVX-CoV2373 (Novavax) probably reduces the incidence of symptomatic COVID-19 compared to placebo (VE 82.91%, 95% CI 50.49% to 94.10%; 3 RCTs, 42,175 participants). There is low-certainty evidence for CoronaVac (Sinovac) for this outcome (VE 69.81%, 95% CI 12.27% to 89.61%; 2 RCTs, 19,852 participants). Severe or critical COVID-19 High-certainty evidence found that BNT162b2, mRNA-1273, Ad26.COV2.S, and BBV152 result in a large reduction in incidence of severe or critical disease due to COVID-19 compared to placebo (VE: BNT162b2: 95.70%, 95% CI 73.90% to 99.90%; 1 RCT, 46,077 participants; mRNA-1273: 98.20%, 95% CI 92.80% to 99.60%; 1 RCT, 28,451 participants; AD26.COV2.S: 76.30%, 95% CI 57.90% to 87.50%; 1 RCT, 39,058 participants; BBV152: 93.40%, 95% CI 57.10% to 99.80%; 1 RCT, 16,976 participants). Moderate-certainty evidence found that NVX-CoV2373 probably reduces the incidence of severe or critical COVID-19 (VE 100.00%, 95% CI 86.99% to 100.00%; 1 RCT, 25,452 participants). Two trials reported high efficacy of CoronaVac for severe or critical disease with wide CIs, but these results could not be pooled. Serious adverse events (SAEs) mRNA-1273, ChAdOx1 (Oxford-AstraZeneca)/SII-ChAdOx1 (Serum Institute of India), Ad26.COV2.S, and BBV152 probably result in little or no difference in SAEs compared to placebo (RR: mRNA-1273: 0.92, 95% CI 0.78 to 1.08; 2 RCTs, 34,072 participants; ChAdOx1/SII-ChAdOx1: 0.88, 95% CI 0.72 to 1.07; 7 RCTs, 58,182 participants; Ad26.COV2.S: 0.92, 95% CI 0.69 to 1.22; 1 RCT, 43,783 participants); BBV152: 0.65, 95% CI 0.43 to 0.97; 1 RCT, 25,928 participants). In each of these, the likely absolute difference in effects was fewer than 5/1000 participants. Evidence for SAEs is uncertain for BNT162b2, CoronaVac, BBIBP-CorV, and NVX-CoV2373 compared to placebo (RR: BNT162b2: 1.30, 95% CI 0.55 to 3.07; 2 RCTs, 46,107 participants; CoronaVac: 0.97, 95% CI 0.62 to 1.51; 4 RCTs, 23,139 participants; BBIBP-CorV: 0.76, 95% CI 0.54 to 1.06; 1 RCT, 26,924 participants; NVX-CoV2373: 0.92, 95% CI 0.74 to 1.14; 4 RCTs, 38,802 participants). For the evaluation of heterologous schedules, booster doses, and efficacy against variants of concern, see main text of review. AUTHORS' CONCLUSIONS Compared to placebo, most vaccines reduce, or likely reduce, the proportion of participants with confirmed symptomatic COVID-19, and for some, there is high-certainty evidence that they reduce severe or critical disease. There is probably little or no difference between most vaccines and placebo for serious adverse events. Over 300 registered RCTs are evaluating the efficacy of COVID-19 vaccines, and this review is updated regularly on the COVID-NMA platform (covid-nma.com). Implications for practice Due to the trial exclusions, these results cannot be generalized to pregnant women, individuals with a history of SARS-CoV-2 infection, or immunocompromized people. Most trials had a short follow-up and were conducted before the emergence of variants of concern. Implications for research Future research should evaluate the long-term effect of vaccines, compare different vaccines and vaccine schedules, assess vaccine efficacy and safety in specific populations, and include outcomes such as preventing long COVID-19. Ongoing evaluation of vaccine efficacy and effectiveness against emerging variants of concern is also vital.
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Affiliation(s)
- Carolina Graña
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | - Lina Ghosn
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | - Theodoros Evrenoglou
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | - Alexander Jarde
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | | | | | | | | | | | | | - Hillary Bonnet
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | - Rouba Assi
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | | | - Melanie Marti
- Department of Immunization, Vaccines and Biologicals, World Health Organization, Geneva, Switzerland
| | - Declan Devane
- Evidence Synthesis Ireland, Cochrane Ireland and HRB-Trials Methodology Research Network, National University of Ireland, Galway, Ireland
| | - Patrick Mallon
- UCD Centre for Experimental Pathogen Host Research and UCD School of Medicine, University College Dublin, Dublin, Ireland
| | - Jean-Daniel Lelievre
- Department of Clinical Immunology and Infectious Diseases, Henri Mondor Hospital, Vaccine Research Institute, Université Paris Est Créteil, Paris, France
| | - Lisa M Askie
- Quality Assurance Norms and Standards Department, World Health Organization, Geneva, Switzerland
| | - Tamara Kredo
- Cochrane South Africa, South African Medical Research Council, Cape Town, South Africa
| | | | - Mauricia Davidson
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | - Carolina Riveros
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | | | - Joerg J Meerpohl
- Institute for Evidence in Medicine, Medical Center & Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany
| | - Giacomo Grasselli
- Department of Anesthesia, Intensive Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Gabriel Rada
- Epistemonikos Foundation, Santiago, Chile
- UC Evidence Center, Cochrane Chile Associated Center, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Asbjørn Hróbjartsson
- Centre for Evidence Based Medicine Odense (CEBMO) and Cochrane Denmark, University of Southern Denmark, Odense, Denmark
- Open Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Philippe Ravaud
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | - Anna Chaimani
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
| | - Isabelle Boutron
- Cochrane France, Paris, France
- Centre of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Université de Paris, Paris, France
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Abstract
BACKGROUND In the context of the COVID-19 pandemic, randomized controlled trials (RCTs) are essential to support clinical decision-making. We aimed (1) to assess and compare the reporting characteristics of RCTs between preprints and peer-reviewed publications and (2) to assess whether reporting improves after the peer review process for all preprints subsequently published in peer-reviewed journals. METHODS We searched the Cochrane COVID-19 Study Register and L·OVE COVID-19 platform to identify all reports of RCTs assessing pharmacological treatments of COVID-19, up to May 2021. We extracted indicators of transparency (e.g., trial registration, data sharing intentions) and assessed the completeness of reporting (i.e., some important CONSORT items, conflict of interest, ethical approval) using a standardized data extraction form. We also identified paired reports published in preprint and peer-reviewed publications. RESULTS We identified 251 trial reports: 121 (48%) were first published in peer-reviewed journals, and 130 (52%) were first published as preprints. Transparency was poor. About half of trials were prospectively registered (n = 140, 56%); 38% (n = 95) made their full protocols available, and 29% (n = 72) provided access to their statistical analysis plan report. A data sharing statement was reported in 68% (n = 170) of the reports of which 91% stated their willingness to share. Completeness of reporting was low: only 32% (n = 81) of trials completely defined the pre-specified primary outcome measures; 57% (n = 143) reported the process of allocation concealment. Overall, 51% (n = 127) adequately reported the results for the primary outcomes while only 14% (n = 36) of trials adequately described harms. Primary outcome(s) reported in trial registries and published reports were inconsistent in 49% (n = 104) of trials; of them, only 15% (n = 16) disclosed outcome switching in the report. There were no major differences between preprints and peer-reviewed publications. Of the 130 RCTs published as preprints, 78 were subsequently published in a peer-reviewed journal. There was no major improvement after the journal peer review process for most items. CONCLUSIONS Transparency, completeness, and consistency of reporting of COVID-19 clinical trials were insufficient both in preprints and peer-reviewed publications. A comparison of paired reports published in preprint and peer-reviewed publication did not indicate major improvement.
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Affiliation(s)
- Philipp Kapp
- Université Paris Cité, Inserm, INRAE, Centre of Research in Epidemiology and Statistics (CRESS), F-75004, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, F-75004, Paris, France.,Cochrane France, F-75004, Paris, France.,Institute for Evidence in Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, D-79110, Freiburg, Germany
| | - Laura Esmail
- Université Paris Cité, Inserm, INRAE, Centre of Research in Epidemiology and Statistics (CRESS), F-75004, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, F-75004, Paris, France.,Cochrane France, F-75004, Paris, France
| | - Lina Ghosn
- Université Paris Cité, Inserm, INRAE, Centre of Research in Epidemiology and Statistics (CRESS), F-75004, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, F-75004, Paris, France.,Cochrane France, F-75004, Paris, France
| | - Philippe Ravaud
- Université Paris Cité, Inserm, INRAE, Centre of Research in Epidemiology and Statistics (CRESS), F-75004, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, F-75004, Paris, France.,Cochrane France, F-75004, Paris, France
| | - Isabelle Boutron
- Université Paris Cité, Inserm, INRAE, Centre of Research in Epidemiology and Statistics (CRESS), F-75004, Paris, France. .,Centre d'Épidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, F-75004, Paris, France. .,Cochrane France, F-75004, Paris, France.
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6
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Davidson M, Menon S, Chaimani A, Evrenoglou T, Ghosn L, Graña C, Henschke N, Cogo E, Villanueva G, Ferrand G, Riveros C, Bonnet H, Kapp P, Moran C, Devane D, Meerpohl JJ, Rada G, Hróbjartsson A, Grasselli G, Tovey D, Ravaud P, Boutron I. Interleukin-1 blocking agents for treating COVID-19. Cochrane Database Syst Rev 2022; 1:CD015308. [PMID: 35080773 PMCID: PMC8791232 DOI: 10.1002/14651858.cd015308] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
BACKGROUND Interleukin-1 (IL-1) blocking agents have been used for treating severe coronavirus disease 2019 (COVID-19), on the premise that their immunomodulatory effect might be beneficial in people with COVID-19. OBJECTIVES To assess the effects of IL-1 blocking agents compared with standard care alone or with placebo on effectiveness and safety outcomes in people with COVID-19. We will update this assessment regularly. SEARCH METHODS We searched the Cochrane COVID-19 Study Register and the COVID-19 L-OVE Platform (search date 5 November 2021). These sources are maintained through regular searches of MEDLINE, Embase, CENTRAL, trial registers and other sources. We also checked the World Health Organization International Clinical Trials Registry Platform, regulatory agency websites, Retraction Watch (search date 3 November 2021). SELECTION CRITERIA We included randomised controlled trials (RCTs) evaluating IL-1 blocking agents compared with standard care alone or with placebo for people with COVID-19, regardless of disease severity. DATA COLLECTION AND ANALYSIS We followed Cochrane methodology. The protocol was amended to reduce the number of outcomes considered. Two researchers independently screened and extracted data and assessed the risk of bias with the Cochrane Risk of Bias 2 tool. We rated the certainty of evidence using the GRADE approach for the critical outcomes of clinical improvement (Day 28; ≥ D60); WHO Clinical Progression Score of level 7 or above (i.e. the proportion of participants with mechanical ventilation +/- additional organ support OR death) (D28; ≥ D60); all-cause mortality (D28; ≥ D60); incidence of any adverse events; and incidence of serious adverse events. MAIN RESULTS We identified four RCTs of anakinra (three published in peer-reviewed journals, one reported as a preprint) and two RCTs of canakinumab (published in peer-reviewed journals). All trials were multicentre (2 to 133 centres). Two trials stopped early (one due to futility and one as the trigger for inferiority was met). The median/mean age range varied from 58 to 68 years; the proportion of men varied from 58% to 77%. All participants were hospitalised; 67% to 100% were on oxygen at baseline but not intubated; between 0% and 33% were intubated at baseline. We identified a further 16 registered trials with no results available, of which 15 assessed anakinra (four completed, four terminated, five ongoing, three not recruiting) and one (completed) trial assessed canakinumab. Effectiveness of anakinra for people with COVID-19 Anakinra probably results in little or no increase in clinical improvement at D28 (risk ratio (RR) 1.08, 95% confidence interval (CI) 0.97 to 1.20; 3 RCTs, 837 participants; absolute effect: 59 more per 1000 (from 22 fewer to 147 more); moderate-certainty evidence. The evidence is uncertain about an effect of anakinra on 1) the proportion of participants with a WHO Clinical Progression Score of level 7 or above at D28 (RR 0.67, 95% CI 0.36 to 1.22; 2 RCTs, 722 participants; absolute effect: 55 fewer per 1000 (from 107 fewer to 37 more); low-certainty evidence) and ≥ D60 (RR 0.54, 95% CI 0.30 to 0.96; 1 RCT, 606 participants; absolute effect: 47 fewer per 1000 (from 72 fewer to 4 fewer) low-certainty evidence); and 2) all-cause mortality at D28 (RR 0.69, 95% CI 0.34 to 1.39; 2 RCTs, 722 participants; absolute effect: 32 fewer per 1000 (from 68 fewer to 40 more); low-certainty evidence). The evidence is very uncertain about an effect of anakinra on 1) the proportion of participants with clinical improvement at ≥ D60 (RR 0.93, 95% CI 0.78 to 1.12; 1 RCT, 115 participants; absolute effect: 59 fewer per 1000 (from 186 fewer to 102 more); very low-certainty evidence); and 2) all-cause mortality at ≥ D60 (RR 1.03, 95% CI 0.68 to 1.56; 4 RCTs, 1633 participants; absolute effect: 8 more per 1000 (from 84 fewer to 147 more); very low-certainty evidence). Safety of anakinra for people with COVID-19 Anakinra probably results in little or no increase in adverse events (RR 1.02, 95% CI 0.94 to 1.11; 2 RCTs, 722 participants; absolute effect: 14 more per 1000 (from 43 fewer to 78 more); moderate-certainty evidence). The evidence is uncertain regarding an effect of anakinra on serious adverse events (RR 0.95, 95% CI 0.58 to 1.56; 2 RCTs, 722 participants; absolute effect: 12 fewer per 1000 (from 104 fewer to 138 more); low-certainty evidence). Effectiveness of canakinumab for people with COVID-19 Canakinumab probably results in little or no increase in clinical improvement at D28 (RR 1.05, 95% CI 0.96 to 1.14; 2 RCTs, 499 participants; absolute effect: 42 more per 1000 (from 33 fewer to 116 more); moderate-certainty evidence). The evidence of an effect of canakinumab is uncertain on 1) the proportion of participants with a WHO Clinical Progression Score of level 7 or above at D28 (RR 0.72, 95% CI 0.44 to 1.20; 2 RCTs, 499 participants; absolute effect: 35 fewer per 1000 (from 69 fewer to 25 more); low-certainty evidence); and 2) all-cause mortality at D28 (RR:0.75; 95% CI 0.39 to 1.42); 2 RCTs, 499 participants; absolute effect: 20 fewer per 1000 (from 48 fewer to 33 more); low-certainty evidence). The evidence is very uncertain about an effect of canakinumab on all-cause mortality at ≥ D60 (RR 0.55, 95% CI 0.16 to 1.91; 1 RCT, 45 participants; absolute effect: 112 fewer per 1000 (from 210 fewer to 227 more); very low-certainty evidence). Safety of canakinumab for people with COVID-19 Canakinumab probably results in little or no increase in adverse events (RR 1.02; 95% CI 0.86 to 1.21; 1 RCT, 454 participants; absolute effect: 11 more per 1000 (from 74 fewer to 111 more); moderate-certainty evidence). The evidence of an effect of canakinumab on serious adverse events is uncertain (RR 0.80, 95% CI 0.57 to 1.13; 2 RCTs, 499 participants; absolute effect: 44 fewer per 1000 (from 94 fewer to 28 more); low-certainty evidence). AUTHORS' CONCLUSIONS Overall, we did not find evidence for an important beneficial effect of IL-1 blocking agents. The evidence is uncertain or very uncertain for several outcomes. Sixteen trials of anakinra and canakinumab with no results are currently registered, of which four are completed, and four terminated. The findings of this review are updated on the COVID-NMA platform (covid-nma.com).
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Affiliation(s)
- Mauricia Davidson
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
| | | | - Anna Chaimani
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
| | - Theodoros Evrenoglou
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
| | - Lina Ghosn
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
| | - Carolina Graña
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
| | | | - Elise Cogo
- Cochrane Response, Cochrane, Toronto, Canada
| | | | - Gabriel Ferrand
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
| | - Carolina Riveros
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
| | - Hillary Bonnet
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
| | - Philipp Kapp
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
| | - Conor Moran
- Infectious Diseases and General Medicine, Mater Misercordiae University Hospital, Dublin, Ireland
| | - Declan Devane
- Evidence Synthesis Ireland, Cochrane Ireland and HRB-Trials Methodology Research Network, National University of Ireland, Galway, Ireland
| | - Joerg J Meerpohl
- Institute for Evidence in Medicine, Medical Center & Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany
| | - Gabriel Rada
- Epistemonikos Foundation, Santiago, Chile
- UC Evidence Center, Cochrane Chile Associated Center, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Asbjørn Hróbjartsson
- Centre for Evidence-Based Medicine Odense (CEBMO) and Cochrane Denmark, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Open Patient data Exploratory Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Giacomo Grasselli
- Department of Anesthesia, Intensive Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - David Tovey
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
| | - Philippe Ravaud
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
| | - Isabelle Boutron
- Cochrane France, Paris, France
- Université de Paris, INSERM, INRAE, CNAM, CRESS, Paris, France
- Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, Paris, France
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7
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Ghosn L, Chaimani A, Evrenoglou T, Davidson M, Graña C, Schmucker C, Bollig C, Henschke N, Sguassero Y, Nejstgaard CH, Menon S, Nguyen TV, Ferrand G, Kapp P, Riveros C, Ávila C, Devane D, Meerpohl JJ, Rada G, Hróbjartsson A, Grasselli G, Tovey D, Ravaud P, Boutron I. Interleukin-6 blocking agents for treating COVID-19: a living systematic review. Cochrane Database Syst Rev 2021; 3:CD013881. [PMID: 33734435 PMCID: PMC8406988 DOI: 10.1002/14651858.cd013881] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Interleukin 6 (IL-6) blocking agents have been used for treating severe coronavirus disease 2019 (COVID-19). Their immunosuppressive effect might be valuable in patients with COVID-19 characterised by substantial immune system dysfunction by controlling inflammation and promoting disease tolerance. OBJECTIVES To assess the effect of IL-6 blocking agents compared to standard care alone or with placebo on efficacy and safety outcomes in COVID-19. We will update this assessment regularly. SEARCH METHODS We searched the World Health Organization (WHO) International Clinical Trials Registry Platform (up to 11 February 2021) and the L-OVE platform, and Cochrane COVID-19 Study Register to identify trials up to 26 February 2021. SELECTION CRITERIA We included randomised controlled trials (RCTs) evaluating IL-6 blocking agents compared with standard care alone or with placebo for people with COVID-19, regardless of disease severity. DATA COLLECTION AND ANALYSIS We followed standard Cochrane methodology. The protocol was amended to reduce the number of outcomes considered. Two review authors independently collected data and assessed the risk of bias with the Cochrane Risk of Bias 2 tool. We rated the certainty of evidence with the GRADE approach for the critical outcomes such as clinical improvement (defined as hospital discharge or improvement on the scale used by trialists to evaluate clinical progression or recovery) (day (D) 28 / ≥ D60); WHO Clinical Progression Score of level 7 or above (i.e. the proportion of participants with mechanical ventilation +/- additional organ support OR death) (D28 / ≥ D60); all-cause mortality (D28 / ≥ D60); incidence of any adverse events; and incidence of serious adverse events. MAIN RESULTS We identified 10 RCTs with available data including one platform trial comparing tocilizumab and sarilumab with standard of care. These trials evaluated tocilizumab (nine RCTs including two platform trials; seven were reported as peer-reviewed articles, two as preprints; 6428 randomised participants); and two sarilumab (one platform trial reported as peer reviewed article, one reported as preprint, 880 randomised participants). All trials included were multicentre trials. They were conducted in Brazil, China, France, Italy, UK, USA, and four were multi-country trials. The mean age range of participants ranged from 56 to 65 years; 4572 (66.3%) of trial participants were male. Disease severity ranged from mild to critical disease. The reported proportion of participants on oxygen at baseline but not intubated varied from 56% to 100% where reported. Five trials reported the inclusion of intubated patients at baseline. We identified a further 20 registered RCTs of tocilizumab compared to placebo/standard care (five completed without available results, five terminated without available results, eight ongoing, two not recruiting); 11 RCTs of sarilumab (two completed without results, three terminated without available results, six ongoing); six RCTs of clazakisumab (five ongoing, one not recruiting); two RCTs of olokizumab (one completed, one not recruiting); one of siltuximab (ongoing) and one RCT of levilimab (completed without available results). Of note, three were cancelled (2 tocilizumab, 1 clazakisumab). One multiple-arm RCT evaluated both tocilizumab and sarilumab compared to standard of care, one three-arm RCT evaluated tocilizumab and siltuximab compared to standard of care and consequently they appear in each respective comparison. Tocilizumab versus standard care alone or with placebo a. Effectiveness of tocilizumab for patients with COVID-19 Tocilizumab probably results in little or no increase in the outcome of clinical improvement at D28 (RR 1.06, 95% CI 1.00 to 1.13; I2 = 40.9%; 7 RCTs, 5585 participants; absolute effect: 31 more with clinical improvement per 1000 (from 0 fewer to 67 more); moderate-certainty evidence). However, we cannot exclude that some subgroups of patients could benefit from the treatment. We did not obtain data for longer-term follow-up (≥ D60). The effect of tocilizumab on the proportion of participants with a WHO Clinical Progression Score of level of 7 or above is uncertain at D28 (RR 0.99, 95% CI 0.56 to 1.74; I2 = 64.4%; 3 RCTs, 712 participants; low-certainty evidence). We did not obtain data for longer-term follow-up (≥ D60). Tocilizumab reduces all-cause mortality at D28 compared to standard care alone or placebo (RR 0.89, 95% CI 0.82 to 0.97; I2 = 0.0%; 8 RCTs, 6363 participants; absolute effect: 32 fewer deaths per 1000 (from 52 fewer to 9 fewer); high-certainty evidence). The evidence suggests uncertainty around the effect on mortality at ≥ D60 (RR 0.86, 95% CI 0.53 to 1.40; I2 = 0.0%; 2 RCTs, 519 participants; low-certainty evidence). b. Safety of tocilizumab for patients with COVID-19 The evidence is very uncertain about the effect of tocilizumab on adverse events (RR 1.23, 95% CI 0.87 to 1.72; I2 = 86.4%; 7 RCTs, 1534 participants; very low-certainty evidence). Nevertheless, tocilizumab probably results in slightly fewer serious adverse events than standard care alone or placebo (RR 0.89, 95% CI 0.75 to 1.06; I2 = 0.0%; 8 RCTs, 2312 participants; moderate-certainty evidence). Sarilumab versus standard care alone or with placebo The evidence is uncertain about the effect of sarilumab on all-cause mortality at D28 (RR 0.77, 95% CI 0.43 to 1.36; 2 RCTs, 880 participants; low certainty), on all-cause mortality at ≥ D60 (RR 1.00, 95% CI 0.50 to 2.0; 1 RCT, 420 participants; low certainty), and serious adverse events (RR 1.17, 95% CI 0.77 to 1.77; 2 RCTs, 880 participants; low certainty). It is unlikely that sarilumab results in an important increase of adverse events (RR 1.05, 95% CI 0.88 to 1.25; 1 RCT, 420 participants; moderate certainty). However, an increase cannot be excluded No data were available for other critical outcomes. AUTHORS' CONCLUSIONS On average, tocilizumab reduces all-cause mortality at D28 compared to standard care alone or placebo and probably results in slightly fewer serious adverse events than standard care alone or placebo. Nevertheless, tocilizumab probably results in little or no increase in the outcome clinical improvement (defined as hospital discharge or improvement measured by trialist-defined scales) at D28. The impact of tocilizumab on other outcomes is uncertain or very uncertain. With the data available, we were not able to explore heterogeneity. Individual patient data meta-analyses are needed to be able to identify which patients are more likely to benefit from this treatment. Evidence for an effect of sarilumab is uncertain and evidence for other anti-IL6 agents is unavailable. Thirty-nine RCTs of IL-6 blocking agents with no results are currently registered, of which nine are completed and seven trials were terminated with no results available. The findings of this review will be updated as new data are made available on the COVID-NMA platform (covid-nma.com).
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Affiliation(s)
- Lina Ghosn
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Anna Chaimani
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Theodoros Evrenoglou
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Mauricia Davidson
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Carolina Graña
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Christine Schmucker
- Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany
- Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Claudia Bollig
- Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany
- Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | | | | | - Camilla Hansen Nejstgaard
- Centre for Evidence-Based Medicine Odense (CEBMO) and Cochrane Denmark, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Open Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Sonia Menon
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Thu Van Nguyen
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Gabriel Ferrand
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Philipp Kapp
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Carolina Riveros
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | | | - Declan Devane
- HRB-Trials Methodology Research Network, National University of Ireland Galway, Galway, Ireland
- Evidence Synthesis Ireland and Cochrane Ireland, Galway, Ireland
| | - Joerg J Meerpohl
- Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany
- Institute for Evidence in Medicine (for Cochrane Germany Foundation), Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Gabriel Rada
- Epistemonikos Foundation, Santiago, Chile
- UC Evidence Center, Cochrane Chile Associated Center, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Asbjørn Hróbjartsson
- Centre for Evidence-Based Medicine Odense (CEBMO) and Cochrane Denmark, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Open Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Giacomo Grasselli
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
- Department of Anesthesia, Intensive Care and Emergency, Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
- Department of Pathophysiology and Transplantation, Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | | | - Philippe Ravaud
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
| | - Isabelle Boutron
- Cochrane France, Paris, France
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
- Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), INSERM, F-75004, Paris, France
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8
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Malmartel A, Ravaud P, Ghosn L, Tran VT. A classification of methods used to personalize participative interventions revealed inadequate reporting in trial protocols. J Clin Epidemiol 2021; 133:80-93. [PMID: 33476767 DOI: 10.1016/j.jclinepi.2021.01.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 12/21/2020] [Accepted: 01/12/2021] [Indexed: 01/14/2023]
Abstract
OBJECTIVES The objective of the study was to develop a classification of methods used to personalize participative interventions in randomized controlled trials (RCTs). STUDY DESIGN AND SETTING We conducted a systematic review including protocols of RCTs assessing participative interventions in PubMed and ClinicalTrials.gov between June 2018 and May 2019. Data extraction was performed by two independent reviewers. We developed a precise classification of methods used to personalize interventions. Then, protocols were reviewed to determine whether personalization was sufficiently described to enable replication. RESULTS We included 109 protocols. The classification used four components and 13 subcomponents accounting for decision points (when interventions were personalized), tailoring variables (on what interventions were personalized), decision rules (how and by whom interventions were personalized), and nature of the subsequent tailoring (what was personalized in the interventions). In 95% of protocols, at least one component or subcomponent of our classification was not adequately reported to enable the replication of the intervention. Components the least well described were tailoring variables (72% of protocols insufficiently described) and the nature of the subsequent tailoring (46% of protocols). CONCLUSION This study provides the first detailed classification of methods used to personalize interventions. This is required to transparently implement personalization and improve reporting in RCTs.
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Affiliation(s)
- Alexandre Malmartel
- Université de Paris, METHODS Team, CRESS, INSERM, INRA, F-75004 Paris, France; Département de médecine générale, Université de Paris, F-75014 Paris, France.
| | - Philippe Ravaud
- Université de Paris, METHODS Team, CRESS, INSERM, INRA, F-75004 Paris, France; Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, Paris, France
| | - Lina Ghosn
- Université de Paris, METHODS Team, CRESS, INSERM, INRA, F-75004 Paris, France
| | - Viet-Thi Tran
- Université de Paris, METHODS Team, CRESS, INSERM, INRA, F-75004 Paris, France; Centre d'Epidémiologie Clinique, AP-HP, Hôpital Hôtel-Dieu, Paris, France
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Graña Possamai C, Ravaud P, Ghosn L, Tran VT. Use of wearable biometric monitoring devices to measure outcomes in randomized clinical trials: a methodological systematic review. BMC Med 2020; 18:310. [PMID: 33153462 PMCID: PMC7646072 DOI: 10.1186/s12916-020-01773-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 09/01/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Wearable biometric monitoring devices (BMDs) have the potential to transform the conduct of randomized controlled trials (RCTs) by shifting the collection of outcome data from single measurements at predefined time points to dense continuous measurements. METHODS Methodological systematic review to understand how recent RCTs used BMDs to measure outcomes and to describe the reporting of these RCTs. Electronic search was performed in the Cochrane Central Register of Controlled Trials, PubMed, and EMBASE and completed a page-by-page hand search in five leading medical journals between January 1, 2018, and December 31, 2018. Three reviewers independently extracted all primary and secondary outcomes collected using BMDs, and assessed (1) the definitions used to summarize BMD outcome data; (2) whether the validity, reliability, and responsiveness of sensors was reported; (3) the discrepancy with outcomes prespecified in public clinical trial registries; and (4) the methods used to manage missing and incomplete BMD outcome data. RESULTS Of the 4562 records screened, 75 RCTs were eligible. Among them, 24% tested a pharmacological intervention and 57% used an inertial measurement sensor to measure physical activity. Included trials involved 464 outcomes (average of 6 [SD = 8] outcomes per trial). In total, 35 trials used a BMD to measure a primary outcome. Several issues affected the value and transparency of trials using BMDs to measure outcomes. First, the definition of outcomes used in the trials was highly heterogeneous (e.g., 21 diabetes trials had 266 outcomes and 153 had different unique definitions to measure diabetes control), which limited the combination and comparison of results. Second, information on the validity, reliability, and responsiveness of sensors used was lacking in 74% of trials. Third, half (53%) of the outcomes measured with BMDs had not been prespecified, with a high risk of outcome reporting bias. Finally, reporting on the management of incomplete outcome data (e.g., due to suboptimal compliance with the BMD) was absent in 68% of RCTs. CONCLUSIONS Use of BMDs to measure outcomes is becoming the norm rather than the exception in many fields. Yet, trialists need to account for several methodological issues when specifying and conducting RCTs using these novel tools.
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Affiliation(s)
- Carolina Graña Possamai
- METHODS Team, Center for Research in Epidemiology and Statistics (CRESS), Université de Paris/INSERM (UMR 1153), 1 Place du Parvis Notre Dame, 75004, Paris, France
| | - Philippe Ravaud
- METHODS Team, Center for Research in Epidemiology and Statistics (CRESS), Université de Paris/INSERM (UMR 1153), 1 Place du Parvis Notre Dame, 75004, Paris, France.,Centre d'Epidémiologie Clinique, Hôpital Hôtel-Dieu (AP-HP), 1 Place du Parvis Notre Dame, 75004, Paris, France.,Department of Epidemiology, Columbia University Mailman School of Public Health, 22 W 168th St, New York, NY, USA
| | - Lina Ghosn
- METHODS Team, Center for Research in Epidemiology and Statistics (CRESS), Université de Paris/INSERM (UMR 1153), 1 Place du Parvis Notre Dame, 75004, Paris, France.,Centre d'Epidémiologie Clinique, Hôpital Hôtel-Dieu (AP-HP), 1 Place du Parvis Notre Dame, 75004, Paris, France
| | - Viet-Thi Tran
- METHODS Team, Center for Research in Epidemiology and Statistics (CRESS), Université de Paris/INSERM (UMR 1153), 1 Place du Parvis Notre Dame, 75004, Paris, France. .,Centre d'Epidémiologie Clinique, Hôpital Hôtel-Dieu (AP-HP), 1 Place du Parvis Notre Dame, 75004, Paris, France.
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Nguyen VT, Benchoufi M, Young B, Ghosn L, Ravaud P, Boutron I. A scoping review provided a framework for new ways of doing research through mobilizing collective intelligence. J Clin Epidemiol 2019; 110:1-11. [PMID: 30772456 DOI: 10.1016/j.jclinepi.2019.02.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 01/14/2019] [Accepted: 02/04/2019] [Indexed: 11/16/2022]
Abstract
OBJECTIVES New forms of research involving collective intelligence (CI) of diverse individuals mobilized through crowdsourcing is successfully emerging in various fields. This scoping review aimed to describe these methods across different fields and propose a framework for implementation. STUDY DESIGN AND SETTING We searched seven electronic databases for reports describing projects that had mobilized CI with crowdsourcing. We used content analysis to develop themes and categories of the methods. RESULTS We identified 145 reports. CI was mobilized to generate ideas, conduct evaluations, solve problems, and create intellectual outputs. Most projects (n = 110, 76%) were open to the public without restrictions on participants' expertise. Participants contributed to projects by independent contribution (i.e., no interaction with other participants) (n = 50, 34%), collaboration (n = 41, 28%), competitions (n = 33, 23%), and playing games (n = 16, 11%). In total, 61% of articles (n = 89) reported methods to evaluate participants' contribution and decision-making process: 43% used an independent panel of experts and 18% involved end users. We identified challenges in implementation and sustainability of CI and proposed solutions. CONCLUSION New research methods based on CI through crowdsourcing could transform clinical research. This framework facilitates the implementation of these methods.
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Affiliation(s)
- Van Thu Nguyen
- INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris, F-75014 France; Paris Descartes University, Sorbonne Paris Cité, France; Department of Health Services Research, Institute of Population Health Sciences, University of Liverpool, Liverpool L69 3GB, UK.
| | - Mehdi Benchoufi
- INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris, F-75014 France; Paris Descartes University, Sorbonne Paris Cité, France; Centre d'Epidémiologie Clinique, Hôpital Hôtel Dieu, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Bridget Young
- Department of Health Services Research, Institute of Population Health Sciences, University of Liverpool, Liverpool L69 3GB, UK
| | - Lina Ghosn
- INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris, F-75014 France; Paris Descartes University, Sorbonne Paris Cité, France; Centre d'Epidémiologie Clinique, Hôpital Hôtel Dieu, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Philippe Ravaud
- INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris, F-75014 France; Paris Descartes University, Sorbonne Paris Cité, France; Centre d'Epidémiologie Clinique, Hôpital Hôtel Dieu, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Isabelle Boutron
- INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of Therapeutic Evaluation of Chronic Diseases Team (METHODS), Paris, F-75014 France; Paris Descartes University, Sorbonne Paris Cité, France; Centre d'Epidémiologie Clinique, Hôpital Hôtel Dieu, Assistance Publique des Hôpitaux de Paris, Paris, France
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Haneef R, Ravaud P, Baron G, Ghosn L, Boutron I. Factors associated with online media attention to research: a cohort study of articles evaluating cancer treatments. Res Integr Peer Rev 2017; 2:9. [PMID: 29451556 PMCID: PMC5803628 DOI: 10.1186/s41073-017-0033-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Accepted: 05/05/2017] [Indexed: 11/22/2022] Open
Abstract
Background New metrics have been developed to assess the impact of research and provide an indication of online media attention and data dissemination. We aimed to describe online media attention of articles evaluating cancer treatments and identify the factors associated with high online media attention. Methods We systematically searched MEDLINE via PubMed on March 1, 2015 for articles published during the first 6 months of 2014 in oncology and medical journals with a diverse range of impact factors, from 3.9 to 54.4, and selected a sample of articles evaluating a cancer treatment regardless of study design. Altmetric Explorer was used to identify online media attention of selected articles. The primary outcome was media attention an article received online as measured by Altmetric score (i.e., number of mentions in online news outlets, science blogs and social media). Regression analysis was performed to investigate the factors associated with high media attention, and regression coefficients represent the logarithm of ratio of mean (RoM) values of Altmetric score per unit change in the covariate. Results Among 792 articles, 218 (27.5%) received no online media attention (Altmetric score = 0). The median [Q1–Q3] Altmetric score was 2.0 [0.0–8.0], range 0.0–428.0. On multivariate analysis, factors associated with high Altmetric score were presence of a press release (RoM = 10.14, 95%CI [4.91–20.96]), open access to the article (RoM = 1.48, 95%CI [1.02–2.16]), and journal impact factor (RoM = 1.10, 95%CI [1.07–1.12]. As compared with observational studies, systematic reviews were not associated with high Altmetric score (RoM = 1.46, 95%CI [0.74–2.86]; P = 0.27), nor were RCTs (RoM = 0.65, 95%CI [0.41–1.02]; P = 0.059) and phase I/II non-RCTs (RoM = 0.58, 95%CI [0.33–1.05]; P = 0.07). The articles with abstract conclusions favouring study treatments were not associated with high Altmetric score (RoM = 0.97, 95%CI [0.60–1.58]; P = 0.91). Conclusions Most important factors associated with high online media attention were the presence of a press release and the journal impact factor. There was no evidence that study design with high level of evidence and type of abstract conclusion were associated with high online media attention. Electronic supplementary material The online version of this article (doi:10.1186/s41073-017-0033-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Romana Haneef
- INSERM, UMR 1153 Epidemiology and Biostatistics Sorbonne Paris Cité Center (CRESS), METHODS team, University of Paris Descartes, Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France.,2Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
| | - Philippe Ravaud
- INSERM, UMR 1153 Epidemiology and Biostatistics Sorbonne Paris Cité Center (CRESS), METHODS team, University of Paris Descartes, Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France.,2Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France.,French Cochrane Center, Paris, France.,5Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY USA
| | - Gabriel Baron
- Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
| | - Lina Ghosn
- 2Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine, Paris, France
| | - Isabelle Boutron
- INSERM, UMR 1153 Epidemiology and Biostatistics Sorbonne Paris Cité Center (CRESS), METHODS team, University of Paris Descartes, Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France.,2Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine, Paris, France.,Centre d'Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France.,French Cochrane Center, Paris, France
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