A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19.
Identifieur interne : 000792 ( Main/Exploration ); précédent : 000791; suivant : 000793A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19.
Auteurs : Oliver James Hulme [Danemark, Royaume-Uni] ; Eric-Jan Wagenmakers [Pays-Bas] ; Per Damkier [Danemark] ; Christopher Fugl Madelung [Danemark] ; Hartwig Roman Siebner [Danemark] ; Jannik Helweg-Larsen [Danemark] ; Quentin F. Gronau [Pays-Bas] ; Thomas Lars Benfield [Danemark] ; Kristoffer Hougaard Madsen [Danemark]Source :
- PloS one [ 1932-6203 ] ; 2021.
Descripteurs français
- KwdFr :
- MESH :
- administration et posologie : Antiviraux, Azithromycine, Hydroxychloroquine.
- Adolescent, Adulte, Adulte d'âge moyen, Charge virale, Enfant, Femelle, Humains, Mâle, Sujet âgé.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Aged (MeSH), Antiviral Agents (administration & dosage), Azithromycin (administration & dosage), COVID-19 (blood), COVID-19 (drug therapy), Child (MeSH), Female (MeSH), Humans (MeSH), Hydroxychloroquine (administration & dosage), Male (MeSH), Middle Aged (MeSH), SARS-CoV-2 (metabolism), Viral Load (MeSH).
- MESH :
- chemical , administration & dosage : Antiviral Agents, Azithromycin, Hydroxychloroquine.
- blood : COVID-19.
- drug therapy : COVID-19.
- metabolism : SARS-CoV-2.
- Adolescent, Adult, Aged, Child, Female, Humans, Male, Middle Aged, Viral Load.
Abstract
Gautret and colleagues reported the results of a non-randomised case series which examined the effects of hydroxychloroquine and azithromycin on viral load in the upper respiratory tract of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients. The authors reported that hydroxychloroquine (HCQ) had significant virus reducing effects, and that dual treatment of both HCQ and azithromycin further enhanced virus reduction. In light of criticisms regarding how patients were excluded from analyses, we reanalysed the original data to interrogate the main claims of the paper. We applied Bayesian statistics to assess the robustness of the original paper's claims by testing four variants of the data: 1) The original data; 2) Data including patients who deteriorated; 3) Data including patients who deteriorated with exclusion of untested patients in the comparison group; 4) Data that includes patients who deteriorated with the assumption that untested patients were negative. To ask if HCQ monotherapy was effective, we performed an A/B test for a model which assumes a positive effect, compared to a model of no effect. We found that the statistical evidence was highly sensitive to these data variants. Statistical evidence for the positive effect model ranged from strong for the original data (BF+0 ~11), to moderate when including patients who deteriorated (BF+0 ~4.35), to anecdotal when excluding untested patients (BF+0 ~2), and to anecdotal negative evidence if untested patients were assumed positive (BF+0 ~0.6). The fact that the patient inclusions and exclusions are not well justified nor adequately reported raises substantial uncertainty about the interpretation of the evidence obtained from the original paper.
DOI: 10.1371/journal.pone.0245048
PubMed: 33606702
PubMed Central: PMC7894854
Affiliations:
- Danemark, Pays-Bas, Royaume-Uni
- Angleterre, Grand Londres, Hollande-Septentrionale
- Amsterdam, Londres
- Université d'Amsterdam
Links toward previous steps (curation, corpus...)
Le document en format XML
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<term>Adult (MeSH)</term>
<term>Aged (MeSH)</term>
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<term>Azithromycin (administration & dosage)</term>
<term>COVID-19 (blood)</term>
<term>COVID-19 (drug therapy)</term>
<term>Child (MeSH)</term>
<term>Female (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Hydroxychloroquine (administration & dosage)</term>
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<term>Adulte (MeSH)</term>
<term>Adulte d'âge moyen (MeSH)</term>
<term>Antiviraux (administration et posologie)</term>
<term>Azithromycine (administration et posologie)</term>
<term>Charge virale (MeSH)</term>
<term>Enfant (MeSH)</term>
<term>Femelle (MeSH)</term>
<term>Humains (MeSH)</term>
<term>Hydroxychloroquine (administration et posologie)</term>
<term>Mâle (MeSH)</term>
<term>Sujet âgé (MeSH)</term>
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<term>Azithromycin</term>
<term>Hydroxychloroquine</term>
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<front><div type="abstract" xml:lang="en">Gautret and colleagues reported the results of a non-randomised case series which examined the effects of hydroxychloroquine and azithromycin on viral load in the upper respiratory tract of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients. The authors reported that hydroxychloroquine (HCQ) had significant virus reducing effects, and that dual treatment of both HCQ and azithromycin further enhanced virus reduction. In light of criticisms regarding how patients were excluded from analyses, we reanalysed the original data to interrogate the main claims of the paper. We applied Bayesian statistics to assess the robustness of the original paper's claims by testing four variants of the data: 1) The original data; 2) Data including patients who deteriorated; 3) Data including patients who deteriorated with exclusion of untested patients in the comparison group; 4) Data that includes patients who deteriorated with the assumption that untested patients were negative. To ask if HCQ monotherapy was effective, we performed an A/B test for a model which assumes a positive effect, compared to a model of no effect. We found that the statistical evidence was highly sensitive to these data variants. Statistical evidence for the positive effect model ranged from strong for the original data (BF+0 ~11), to moderate when including patients who deteriorated (BF+0 ~4.35), to anecdotal when excluding untested patients (BF+0 ~2), and to anecdotal negative evidence if untested patients were assumed positive (BF+0 ~0.6). The fact that the patient inclusions and exclusions are not well justified nor adequately reported raises substantial uncertainty about the interpretation of the evidence obtained from the original paper.</div>
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<ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0245048</ELocationID>
<Abstract><AbstractText>Gautret and colleagues reported the results of a non-randomised case series which examined the effects of hydroxychloroquine and azithromycin on viral load in the upper respiratory tract of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients. The authors reported that hydroxychloroquine (HCQ) had significant virus reducing effects, and that dual treatment of both HCQ and azithromycin further enhanced virus reduction. In light of criticisms regarding how patients were excluded from analyses, we reanalysed the original data to interrogate the main claims of the paper. We applied Bayesian statistics to assess the robustness of the original paper's claims by testing four variants of the data: 1) The original data; 2) Data including patients who deteriorated; 3) Data including patients who deteriorated with exclusion of untested patients in the comparison group; 4) Data that includes patients who deteriorated with the assumption that untested patients were negative. To ask if HCQ monotherapy was effective, we performed an A/B test for a model which assumes a positive effect, compared to a model of no effect. We found that the statistical evidence was highly sensitive to these data variants. Statistical evidence for the positive effect model ranged from strong for the original data (BF+0 ~11), to moderate when including patients who deteriorated (BF+0 ~4.35), to anecdotal when excluding untested patients (BF+0 ~2), and to anecdotal negative evidence if untested patients were assumed positive (BF+0 ~0.6). The fact that the patient inclusions and exclusions are not well justified nor adequately reported raises substantial uncertainty about the interpretation of the evidence obtained from the original paper.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Hulme</LastName>
<ForeName>Oliver James</ForeName>
<Initials>OJ</Initials>
<Identifier Source="ORCID">0000-0003-3139-4324</Identifier>
<AffiliationInfo><Affiliation>Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>London Mathematical Laboratory, London, United Kingdom.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Wagenmakers</LastName>
<ForeName>Eric-Jan</ForeName>
<Initials>EJ</Initials>
<AffiliationInfo><Affiliation>Department of Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Damkier</LastName>
<ForeName>Per</ForeName>
<Initials>P</Initials>
<AffiliationInfo><Affiliation>Department of Clinical Chemistry & Pharmacology, Odense University Hospital, Odense, Denmark.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Madelung</LastName>
<ForeName>Christopher Fugl</ForeName>
<Initials>CF</Initials>
<Identifier Source="ORCID">0000-0002-0827-217X</Identifier>
<AffiliationInfo><Affiliation>Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Clinical Chemistry & Pharmacology, Odense University Hospital, Odense, Denmark.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Siebner</LastName>
<ForeName>Hartwig Roman</ForeName>
<Initials>HR</Initials>
<AffiliationInfo><Affiliation>Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen NV, Denmark.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen NV, Denmark.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Helweg-Larsen</LastName>
<ForeName>Jannik</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>Department of Infectious Diseases, Rigshospitalet, Copenhagen University Hospital, Copenhagen NV, Denmark.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Gronau</LastName>
<ForeName>Quentin F</ForeName>
<Initials>QF</Initials>
<AffiliationInfo><Affiliation>Department of Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Benfield</LastName>
<ForeName>Thomas Lars</ForeName>
<Initials>TL</Initials>
<Identifier Source="ORCID">0000-0003-0698-9385</Identifier>
<AffiliationInfo><Affiliation>Department of Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen NV, Denmark.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Infectious Diseases, Amager Hvidovre Hospital, Hvidovre, Denmark.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Madsen</LastName>
<ForeName>Kristoffer Hougaard</ForeName>
<Initials>KH</Initials>
<AffiliationInfo><Affiliation>Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D003160">Comparative Study</PublicationType>
<PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2021</Year>
<Month>02</Month>
<Day>19</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>PLoS One</MedlineTA>
<NlmUniqueID>101285081</NlmUniqueID>
<ISSNLinking>1932-6203</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList><Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D000998">Antiviral Agents</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>4QWG6N8QKH</RegistryNumber>
<NameOfSubstance UI="D006886">Hydroxychloroquine</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>83905-01-5</RegistryNumber>
<NameOfSubstance UI="D017963">Azithromycin</NameOfSubstance>
</Chemical>
</ChemicalList>
<SupplMeshList><SupplMeshName Type="Protocol" UI="C000705127">COVID-19 drug treatment</SupplMeshName>
</SupplMeshList>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000998" MajorTopicYN="N">Antiviral Agents</DescriptorName>
<QualifierName UI="Q000008" MajorTopicYN="Y">administration & dosage</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D017963" MajorTopicYN="N">Azithromycin</DescriptorName>
<QualifierName UI="Q000008" MajorTopicYN="Y">administration & dosage</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000086382" MajorTopicYN="N">COVID-19</DescriptorName>
<QualifierName UI="Q000097" MajorTopicYN="Y">blood</QualifierName>
<QualifierName UI="Q000188" MajorTopicYN="Y">drug therapy</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006886" MajorTopicYN="N">Hydroxychloroquine</DescriptorName>
<QualifierName UI="Q000008" MajorTopicYN="Y">administration & dosage</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000086402" MajorTopicYN="N">SARS-CoV-2</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D019562" MajorTopicYN="Y">Viral Load</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<CoiStatement>Dr. Benfield reports grants from Pfizer, grants from Novo Nordisk Foundation, grants from Simonsen Foundation, grants and personal fees from GSK, grants and personal fees from Pfizer, personal fees from Boehringer Ingelheim, personal fees from Gilead, personal fees from MSD, outside the submitted work; Dr. Siebner reports personal fees from Sanofi Genzyme, personal fees from Novartis, personal fees from Elsevier publishers, other from Springer publishers, outside the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials</CoiStatement>
</MedlineCitation>
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<Month>05</Month>
<Day>15</Day>
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<PubMedPubDate PubStatus="accepted"><Year>2020</Year>
<Month>11</Month>
<Day>16</Day>
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<ArticleId IdType="doi">10.1371/journal.pone.0245048</ArticleId>
<ArticleId IdType="pii">PONE-D-20-11807</ArticleId>
<ArticleId IdType="pmc">PMC7894854</ArticleId>
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<ReferenceList><Reference><Citation>Behav Res Methods. 2015 Dec;47(4):913-917</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25271090</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Int J Antimicrob Agents. 2020 Jul;56(1):105949</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32205204</ArticleId>
</ArticleIdList>
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<affiliations><list><country><li>Danemark</li>
<li>Pays-Bas</li>
<li>Royaume-Uni</li>
</country>
<region><li>Angleterre</li>
<li>Grand Londres</li>
<li>Hollande-Septentrionale</li>
</region>
<settlement><li>Amsterdam</li>
<li>Londres</li>
</settlement>
<orgName><li>Université d'Amsterdam</li>
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<tree><country name="Danemark"><noRegion><name sortKey="Hulme, Oliver James" sort="Hulme, Oliver James" uniqKey="Hulme O" first="Oliver James" last="Hulme">Oliver James Hulme</name>
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<name sortKey="Damkier, Per" sort="Damkier, Per" uniqKey="Damkier P" first="Per" last="Damkier">Per Damkier</name>
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<name sortKey="Madelung, Christopher Fugl" sort="Madelung, Christopher Fugl" uniqKey="Madelung C" first="Christopher Fugl" last="Madelung">Christopher Fugl Madelung</name>
<name sortKey="Madsen, Kristoffer Hougaard" sort="Madsen, Kristoffer Hougaard" uniqKey="Madsen K" first="Kristoffer Hougaard" last="Madsen">Kristoffer Hougaard Madsen</name>
<name sortKey="Madsen, Kristoffer Hougaard" sort="Madsen, Kristoffer Hougaard" uniqKey="Madsen K" first="Kristoffer Hougaard" last="Madsen">Kristoffer Hougaard Madsen</name>
<name sortKey="Siebner, Hartwig Roman" sort="Siebner, Hartwig Roman" uniqKey="Siebner H" first="Hartwig Roman" last="Siebner">Hartwig Roman Siebner</name>
<name sortKey="Siebner, Hartwig Roman" sort="Siebner, Hartwig Roman" uniqKey="Siebner H" first="Hartwig Roman" last="Siebner">Hartwig Roman Siebner</name>
<name sortKey="Siebner, Hartwig Roman" sort="Siebner, Hartwig Roman" uniqKey="Siebner H" first="Hartwig Roman" last="Siebner">Hartwig Roman Siebner</name>
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<country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Hulme, Oliver James" sort="Hulme, Oliver James" uniqKey="Hulme O" first="Oliver James" last="Hulme">Oliver James Hulme</name>
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<country name="Pays-Bas"><region name="Hollande-Septentrionale"><name sortKey="Wagenmakers, Eric Jan" sort="Wagenmakers, Eric Jan" uniqKey="Wagenmakers E" first="Eric-Jan" last="Wagenmakers">Eric-Jan Wagenmakers</name>
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<name sortKey="Gronau, Quentin F" sort="Gronau, Quentin F" uniqKey="Gronau Q" first="Quentin F" last="Gronau">Quentin F. Gronau</name>
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