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Published in: BMC Medicine 1/2021

01-12-2021 | COVID-19 | Research article

Following the science? Comparison of methodological and reporting quality of covid-19 and other research from the first wave of the pandemic

Authors: Terence J. Quinn, Jennifer K. Burton, Ben Carter, Nicola Cooper, Kerry Dwan, Ryan Field, Suzanne C. Freeman, Claudia Geue, Ping-Hsuan Hsieh, Kris McGill, Clareece R. Nevill, Dikshyanta Rana, Alex Sutton, Martin Taylor Rowan, Yiqiao Xin

Published in: BMC Medicine | Issue 1/2021

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Abstract

Background

Following the initial identification of the 2019 coronavirus disease (covid-19), the subsequent months saw substantial increases in published biomedical research. Concerns have been raised in both scientific and lay press around the quality of some of this research. We assessed clinical research from major clinical journals, comparing methodological and reporting quality of covid-19 papers published in the first wave (here defined as December 2019 to May 2020 inclusive) of the viral pandemic with non-covid papers published at the same time.

Methods

We reviewed research publications (print and online) from The BMJ, Journal of the American Medical Association (JAMA), The Lancet, and New England Journal of Medicine, from first publication of a covid-19 research paper (February 2020) to May 2020 inclusive. Paired reviewers were randomly allocated to extract data on methodological quality (risk of bias) and reporting quality (adherence to reporting guidance) from each paper using validated assessment tools. A random 10% of papers were assessed by a third, independent rater. Overall methodological quality for each paper was rated high, low or unclear. Reporting quality was described as percentage of total items reported.

Results

From 168 research papers, 165 were eligible, including 54 (33%) papers with a covid-19 focus. For methodological quality, 18 (33%) covid-19 papers and 83 (73%) non-covid papers were rated as low risk of bias, OR 6.32 (95%CI 2.85 to 14.00). The difference in quality was maintained after adjusting for publication date, results, funding, study design, journal and raters (OR 6.09 (95%CI 2.09 to 17.72)). For reporting quality, adherence to reporting guidelines was poorer for covid-19 papers, mean percentage of total items reported 72% (95%CI:66 to 77) for covid-19 papers and 84% (95%CI:81 to 87) for non-covid.

Conclusions

Across various measures, we have demonstrated that covid-19 research from the first wave of the pandemic was potentially of lower quality than contemporaneous non-covid research. While some differences may be an inevitable consequence of conducting research during a viral pandemic, poor reporting should not be accepted.
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Literature
4.
go back to reference Glasziou Paul P, Sanders Sharon, Hoffmann Tammy. Waste in Covid-19 research BMJ 2020; 369:m1847. Glasziou Paul P, Sanders Sharon, Hoffmann Tammy. Waste in Covid-19 research BMJ 2020; 369:m1847.
5.
go back to reference London AJ, Kimmelman J. Against pandemic research exceptionalism. Science. 2020;368:476–7.CrossRef London AJ, Kimmelman J. Against pandemic research exceptionalism. Science. 2020;368:476–7.CrossRef
6.
go back to reference Armstrong S. How a scramble for COVID-19 evidence is leaving clinicians and the public wanting. BMJ. 2020;369:m2045.CrossRef Armstrong S. How a scramble for COVID-19 evidence is leaving clinicians and the public wanting. BMJ. 2020;369:m2045.CrossRef
7.
go back to reference Glasziou P, Vandenbroucke J. Assessing the quality of research. BMJ. 2004;328:39–41.CrossRef Glasziou P, Vandenbroucke J. Assessing the quality of research. BMJ. 2004;328:39–41.CrossRef
8.
go back to reference Harrison JK, Reid J, Quinn TJ, Shenkin SD. Using quality assessment tools to critically appraise ageing research: a guide for clinicians. Age Ageing. 2017;46:359–65.CrossRef Harrison JK, Reid J, Quinn TJ, Shenkin SD. Using quality assessment tools to critically appraise ageing research: a guide for clinicians. Age Ageing. 2017;46:359–65.CrossRef
9.
go back to reference Dechartres A, Trinquart L, Atal I, et al. Evolution of poor reporting and inadequate methods over time in 20 920 randomised controlled trials included in Cochrane reviews: research on research study. BMJ. 2017;357:j2490.CrossRef Dechartres A, Trinquart L, Atal I, et al. Evolution of poor reporting and inadequate methods over time in 20 920 randomised controlled trials included in Cochrane reviews: research on research study. BMJ. 2017;357:j2490.CrossRef
10.
go back to reference Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535.CrossRef Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535.CrossRef
11.
go back to reference Higgins JPT, Altman DG, Gøtzsche PC, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.CrossRef Higgins JPT, Altman DG, Gøtzsche PC, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.CrossRef
12.
go back to reference Schulz KF, Altman DG, Moher D. CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c332.CrossRef Schulz KF, Altman DG, Moher D. CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c332.CrossRef
14.
go back to reference von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007;335:806–8.CrossRef von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007;335:806–8.CrossRef
15.
go back to reference Whiting PF, Rutjes AWS, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529–36.CrossRef Whiting PF, Rutjes AWS, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529–36.CrossRef
16.
go back to reference Bossuyt PM, Reitsma JB, Bruns DE, et al. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ. 2015;351:h5527.CrossRef Bossuyt PM, Reitsma JB, Bruns DE, et al. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ. 2015;351:h5527.CrossRef
17.
go back to reference Shea BJ, Reeves BC, Wells G, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.CrossRef Shea BJ, Reeves BC, Wells G, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.CrossRef
19.
go back to reference Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19:349–57.CrossRef Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19:349–57.CrossRef
20.
go back to reference Wolff RF, Moons KGM, Riley RD, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170:51–8.CrossRef Wolff RF, Moons KGM, Riley RD, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170:51–8.CrossRef
21.
go back to reference Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ. 2015;350:g7594.CrossRef Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ. 2015;350:g7594.CrossRef
22.
go back to reference Higgins JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration, 2011. Available from www.handbook.cochrane.org. Accessed May 2020. Higgins JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration, 2011. Available from www.​handbook.​cochrane.​org. Accessed May 2020.
23.
go back to reference Altman DG, Simera I, Hoey J, Moher D, Schulz K. EQUATOR: reporting guidelines for health research. Open Med. 2008;2:e49–50.PubMedPubMedCentral Altman DG, Simera I, Hoey J, Moher D, Schulz K. EQUATOR: reporting guidelines for health research. Open Med. 2008;2:e49–50.PubMedPubMedCentral
25.
go back to reference Nijenhuis VJ, Brouwer, Delewi R, et al. Anticoagulation with or without clopidogrel after transcatheter aortic-valve implantation. NEJM. 2020;382:1696–707.CrossRef Nijenhuis VJ, Brouwer, Delewi R, et al. Anticoagulation with or without clopidogrel after transcatheter aortic-valve implantation. NEJM. 2020;382:1696–707.CrossRef
26.
go back to reference Guan WJ, Ni Z, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China. NEJM. 2020;382:1708–20.CrossRef Guan WJ, Ni Z, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China. NEJM. 2020;382:1708–20.CrossRef
27.
go back to reference Wilson C, Kerr D, Noel-Storr A, Quinn TJ. Associations with publication and assessing publication bias in dementia diagnostic test accuarcy studies. Int j Geri Psych. 2015;30:1250–6.CrossRef Wilson C, Kerr D, Noel-Storr A, Quinn TJ. Associations with publication and assessing publication bias in dementia diagnostic test accuarcy studies. Int j Geri Psych. 2015;30:1250–6.CrossRef
29.
go back to reference Agresti A, Caffo B. Simple and effective confidence intervals for proportions and difference of proportions result from adding two successes and two failures. Am Stat. 2000;54:280–8. Agresti A, Caffo B. Simple and effective confidence intervals for proportions and difference of proportions result from adding two successes and two failures. Am Stat. 2000;54:280–8.
30.
go back to reference Hutton B, Salantia G, Caldwell DM, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions. Ann Intern Med. 2015;162:777–84.CrossRef Hutton B, Salantia G, Caldwell DM, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions. Ann Intern Med. 2015;162:777–84.CrossRef
31.
go back to reference Stewart LA, Clarke M, Rovers M, et al. Preferred reporting items for a systematic review and meta-analysis of individual participant data. JAMA. 2015;313:1657–65.CrossRef Stewart LA, Clarke M, Rovers M, et al. Preferred reporting items for a systematic review and meta-analysis of individual participant data. JAMA. 2015;313:1657–65.CrossRef
32.
go back to reference Akl EA, Meerpohl JJ, Elliott J, et al. Living systematic reviews: 4. Living guideline recommendations. J Clin Epidemiol. 2017;91:47–53.CrossRef Akl EA, Meerpohl JJ, Elliott J, et al. Living systematic reviews: 4. Living guideline recommendations. J Clin Epidemiol. 2017;91:47–53.CrossRef
33.
go back to reference Wyants L, Calster BV, Collins GS, et al. Prediction models for diagnosis and prognosis of covid-19:systematic review and critical appraisal. BMJ. 2020;369:m1328.CrossRef Wyants L, Calster BV, Collins GS, et al. Prediction models for diagnosis and prognosis of covid-19:systematic review and critical appraisal. BMJ. 2020;369:m1328.CrossRef
36.
go back to reference Colson P, Rolain JM, Lagier JC, Brouqui P, Raoult D. Chloroquine and hydroxychloroquine as available weapons to fight COVID-19. Int J Antimicrob Agents. 2020;55:105932.CrossRef Colson P, Rolain JM, Lagier JC, Brouqui P, Raoult D. Chloroquine and hydroxychloroquine as available weapons to fight COVID-19. Int J Antimicrob Agents. 2020;55:105932.CrossRef
37.
go back to reference RECOVERY Trial Chief Investigators. No clinical benefit from use of hydroxychloroquine in hospitalised patients with covid-19. RECOVERYtrial.net. Last Accessed June 2020. RECOVERY Trial Chief Investigators. No clinical benefit from use of hydroxychloroquine in hospitalised patients with covid-19. RECOVERYtrial.​net. Last Accessed June 2020.
38.
go back to reference Alexander PE, Debono VB, Mammen MJ, et al. Covid-19 coronavirus research has overall low methodological quality this far: case in point for chloroquine /hydroxychloroquine. J Clin Epi. 2020;123:120–6.CrossRef Alexander PE, Debono VB, Mammen MJ, et al. Covid-19 coronavirus research has overall low methodological quality this far: case in point for chloroquine /hydroxychloroquine. J Clin Epi. 2020;123:120–6.CrossRef
40.
go back to reference Turner L, Shamseer L, Altman DG, et al. Consolidated standards of reporting trials (CONSORT) and the completeness of reporting of randomised controlled trials (RCTs) published in medical journals. Cochrane Database Syst Rev. 2012;11:MR000030.PubMed Turner L, Shamseer L, Altman DG, et al. Consolidated standards of reporting trials (CONSORT) and the completeness of reporting of randomised controlled trials (RCTs) published in medical journals. Cochrane Database Syst Rev. 2012;11:MR000030.PubMed
42.
go back to reference Knottnerus JA, Tugwell P. Methodological challenges in studying the covid-19 pandemic crisis. J Clin Epi. 2020;121:A5–7.CrossRef Knottnerus JA, Tugwell P. Methodological challenges in studying the covid-19 pandemic crisis. J Clin Epi. 2020;121:A5–7.CrossRef
Metadata
Title
Following the science? Comparison of methodological and reporting quality of covid-19 and other research from the first wave of the pandemic
Authors
Terence J. Quinn
Jennifer K. Burton
Ben Carter
Nicola Cooper
Kerry Dwan
Ryan Field
Suzanne C. Freeman
Claudia Geue
Ping-Hsuan Hsieh
Kris McGill
Clareece R. Nevill
Dikshyanta Rana
Alex Sutton
Martin Taylor Rowan
Yiqiao Xin
Publication date
01-12-2021
Publisher
BioMed Central
Keyword
COVID-19
Published in
BMC Medicine / Issue 1/2021
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-021-01920-x

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