BMJ...Department of Medicine, Centre de recherche du CHU de Sherbrooke, Sherbrooke, Quebec, Canada. 5. Department of Preventive Medicine, College of Medicine, Chosun University, Gwangju,

Confidential: For Review OnlyEffects of therapies for prophylaxis and treatment of

COVID-19: living systematic review and network meta-analysis

Journal: BMJ

Manuscript ID BMJ-2020-059724

Article Type: Research

BMJ Journal: BMJ

Date Submitted by the Author: 19-Jun-2020

Complete List of Authors: Siemieniuk, Reed; McMaster University, Department of Health Research Methods, Evidence, and ImpactBartoszko, Jessica; McMaster University, Department of Health Research Methods, Evidence, and ImpactGe, Long; Lanzhou University, Evidence Based Social Science Research Center, School of Public HealthZeraatkar, Dena; McMaster University, Health Research Methods, Evidence, and ImpactRochwerg, Bram; McMaster University, Department of Health Research Methods, Evidence and Impact; McMaster University, Department of MedicineLamontagne, Francois; Centre de recherche du CHU de Sherbrooke, Department of MedicineHan, Mi Ah; Chosun University, Department of Preventive Medicine, College of MedicineKum, Elena; McMaster University, Department of Health Research Methods, Evidence and ImpactLiu, Qin; Chongqing Medical University, Cochrane China Network; Chongqing Medical University, School of Public Health & ManagementAgarwal, Arnav; University of Toronto, Department of Medicine; McMaster University, Department of Health Research Methods, Evidence and ImpactAgoritsas, Thomas; McMaster University, Department of Health Research Methods, Evidence and Impact; University Hospitals of Geneva, Division of General Internal Medicine & Division of Clinical EpidemiologyAlexander, Paul; McMaster University, Department of Health Research Methods, Evidence and ImpactCheung, Kevin; Western University, Department of MedicineChu, Derek; McMaster University, Department of Health Research Methods, Evidence and Impact; McMaster University, Department of MedicineCouban, Rachel; McMaster University, Department of AnesthesiaDevji, Tahira; McMaster University, Department of Health Research Methods, Evidence and ImpactFang, Bo; Chongqing Medical University, School of Public Health and Management

https://mc.manuscriptcentral.com/bmj

BMJ

Confidential: For Review OnlyFang, Carmen; William Osler Health NetworkFlottorp, Signe; Norwegian Institute of Public Health; University of Oslo, Institute of Health and SocietyForoutan, Farid; McMaster University, Department of Health Research Methods, Evidence and Impact; Toronto General Hospital, Ted Rogers Center for Heart ResearchHeels-Ansdell, Diane; McMaster University, Department of Health Research Methods, Evidence and ImpactPardo-Hernandez, Hector; Sant Pau Biomedical Research Institute (IIB Sant Pau), Iberoamerican Cochrane Centre; CIBER de Epidemiología y Salud Pública (CIBERESP)Kimia, Honarmand; Western University, Department of MedicineHou, Xiaorong ; Chongqing Medical University, College of Medical InformaticsQuazi, Ibrahim; McMaster University, Department of Health Research Methods, Evidence and ImpactIzcovich, Ariel; Servicio de Clinica Médica del Hospital AlemánLoeb, Mark; McMaster University, Department of Health Research Methods, Evidence and ImpactMarcucci, Maura; McMaster University, Department of Health Research Methods, Evidence and Impact; McMaster University, Department of MedicineMcLeod, Shelley; Sinai Health System, Schwartz/Reisman Emergency Medicine Institute; University of Toronto, Department of Family and Community MedicineMotaghipisheh, Shahrzad; McMaster University, Department of Health Research Methods, Evidence and ImpactMurthy, Srinivas; The University of British Columbia, Department of PediatricsMustafa, Reem; University of Kansas Medical Center, Department of Medicine; McMaster University, Department of Health Research Methods, Evidence and ImpactNeary, John; McMaster University, Division of General Internal Medicine, Department of MedicineRada, Gabriel; Epistemonikos Foundation; UC Evidence Center, Cochrane Chile Associated Center, Pontificia Universidad Católica de ChileRiaz, Irbaz Bin; Mayo Clinic Rochester, Hematology and OncologySadeghirad, Behnam; McMaster University, Department of Anesthesia; McMaster University, Department of Health Research Methods, Evidence and ImpactSekercioglu, Nigar; McMaster University, Department of Health Research Methods, Evidence and ImpactSheng, Lulu; Chongqing Medical University, School of Public Health and ManagementSwitzer, Charlotte; McMaster University, Department of Health Research Methods, Evidence, and ImpactTendal, Britta; Monash University, School of Public Health and Preventive MedicineThabane, Lehana; McMaster University, Department of Health Research Methods, Evidence, and ImpactTomlinson, George; University Health Network, Department of MedicineTurner, Tari; Monash University, School of Public Health and Preventive MedicineVandvik, Per; University of Oslo, Institute of Health and SocietyVernooij, Robin; University Medical Center Utrecht, Department of Nephrology and Hypertension; University Medical Center Utrecht, Julius Center for Health Sciences and Primary CareViteri-García, Andrés ; Epistemonikos Foundation; Universidad UTE, Centro de Investigación de Salud Pública y Epidemiología Clínica (CISPEC), Facultad de Ciencias de la Salud Eugenio EspejoWang, Ying; Beijing Chao-Yang Hospital, Capital Medical University,

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Confidential: For Review OnlyDepartment of PharmacyYao, Liang; McMaster University, Department of Health Research Methods, Evidence, and ImpactYe, Zhikang; McMaster University, Department of Health Research Methods, Evidence, and ImpactGuyatt, Gordon; McMaster University, Department of Health Research Methods, Evidence, and ImpactBrignardello-Petersen, Romina; McMaster University, Department of Health Research Methods, Evidence, and Impact

Keywords: COVID-19, Network Meta-analysis, Living Systematic Review

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Effects of therapies for prophylaxis and treatment of COVID-19: living systematic review and network meta-analysis

Authors

Reed AC Siemieniuk,* methodologist, internist,1 Jessica J Bartoszko,* methodologist,1 Long Ge,* methodologist,2 Dena Zeraatkar,* methodologist,1 Bram Rochwerg, methodologist, critical care physician,1,3 Francois Lamontagne, methodologist, critical care physician,4 Mi Ah Han, methodologist,5 Elena Kum, methodologist,1 Qin Liu, professor,6,7 Arnav Agarwal, methodologist, internist,1,8 Thomas Agoritsas, methodologist, internist,1,9 Paul Alexander, methodologist, assistant professor,1 Kevin Cheung, methodologist, primary care physician,10 Derek K Chu, methodologist, immunologist,1,3 Rachel Couban, librarian,11 Tahira Devji, methodologist,1 Bo Fang, methodologist,7 Carmen Fang, methodologist, registered nurse,12 Signe Agnes Flottorp, senior researcher,13,14 Farid Foroutan, methodologist,1,15 Diane Heels-Ansdell, statistician,1 Hector Pardo-Hernandez, methodologist,16,17 Kimia Honarmand, methodologist, critical care physician,10 Xiaorong Hou, librarian,18 Quazi Ibrahim, statistician,1 Ariel Izcovich, methodologist, internist,19 Mark Loeb, methodologist, infectious disease physician,1 Maura Marcucci, methodologist, internist,1,3 Shelley L McLeod, methodologist, assistant professor,20,21 Sharhzad Motaghi, methodologist,1 Srinivas Murthy, clinical associate professor, pediatric critical care, infectious diseases physician,22 Reem A Mustafa, associate professor, nephrologist,1,23 John D Neary, methodologist, internist,3 Gabriel Rada, methodologist,24 Irbaz Bin Riaz, methodologist, internist,25 Behnam Sadeghirad, assistant professor,1,11 Nigar Sekercioglu, assistant professor,1 Lulu Sheng, methodologist,7 Charlotte Switzer, methodologist,1 Britta Tendal, methodologist,26 Lehana Thabane, professor,1 George Tomlinson, senior biostatistician,27 Tari Turner, senior research fellow,26 Per O Vandvik, methodologist, internist,14 Robin WM Vernooij, methodologist,28,29 Andrés Viteri-García, methodologist,24,30 Ying Wang, methodologist, pharmacist,31 Liang Yao, methodologist,1 Zhikang Ye, methodologist, pharmacist,1 Gordon H Guyatt, methodologist, internist,1 Romina Brignardello-Petersen, methodologist1

* These authors contributed equally to the project, and share co-first authorship.

2. Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, Gansu, China

3. Department of Medicine, McMaster University, Hamilton, Ontario, Canada4. Department of Medicine, Centre de recherche du CHU de Sherbrooke, Sherbrooke, Quebec,

Canada.5. Department of Preventive Medicine, College of Medicine, Chosun University, Gwangju,

Republic of Korea6. Cochrane China Network, Chongqing Medical University, Chongqing, China7. School of Public Health & Management, Chongqing Medical University, Chongqing, China8. Department of Medicine, University of Toronto, Toronto, Ontario, Canada9. Division of General Internal Medicine & Division of Clinical Epidemiology, University

Hospitals of Geneva, Geneva, Switzerland10. Department of Medicine, Western University, London, Ontario, Canada11. Department of Anesthesia, McMaster University, Hamilton, Ontario, Canada12. William Osler Health Network, Toronto, Ontario, Canada13. Norwegian Institute of Public Health, Oslo, Norway14. Institute of Health and Society, University of Oslo, Oslo, Norway15. Ted Rogers Center for Heart Research, Toronto General Hospital, Ontario, Canada16. Iberoamerican Cochrane Centre, Sant Pau Biomedical Research Institute (IIB Sant Pau),

Barcelona, Spain17. CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain18. College of Medical Informatics, Chongqing Medical University, Chongqing, China19. Servicio de Clinica Médica del Hospital Alemán, Buenos Aires, Argentina20. Schwartz/Reisman Emergency Medicine Institute, Sinai Health, Toronto, Ontario, Canada21. Department of Family and Community Medicine, University of Toronto, Toronto, Ontario,

Canada

1. Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada

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22. Department of Pediatrics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia.

23. Department of Medicine, University of Kansas Medical Center, Kansas City, Missouri, USA24. Epistemonikos Foundation, Santiago, Chile25. Hematology and Oncology, Mayo Clinic Rochester, Rochester, Minnesota, USA26. School of Public Health and Preventative Medicine, Monash University, Melbourne,

Australia27. Department of Medicine, University Health Network, Toronto, Ontario, Canada28. Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht,

The Netherlands29. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht,

Utrecht University, Utrecht, The Netherlands30. Centro de Investigación de Salud Pública y Epidemiología Clínica (CISPEC), Facultad de

Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito – Ecuador31. Department of Pharmacy, Beijing Chaoyang Hospital, Capital Medical University, Beijing,

China

Contributor and guarantor informationRAC, JB, DZ, LG, and RBP were the core team leading the systematic review. JB, RC, SAF, RV, PA, SM, YW, ZY, IR, TD, AI, CS, LY, FF, QL, XH, LLS, BF, and AV participated in study identification and selection. DZ, EK, NS, RV, AA, YW, KH, HPH, KC, MH, CF, SM, QL, LY, and FF participated in data collection. LG, BS, QI, DHA, GG, GT, and LT participated in data analysis. RBP, HPH, AI, RM, TD, NS, and DC participated in assessment of the certainty of the evidence. SM, FL, BR, TA, PV, GG, MM, JN, ML, TT, BT, FF, and GR provided advice at different stages. RAC, RBP and GHG drafted the manuscript. All authors approved the final version of the manuscript. RAC is the guarantor of this article.

Copyright/ license for publicationThe Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above

Competing interests declarationAll authors will complete the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and will declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work

Ethics approval: Not applicable. All the work was developed using published data.

Transparency declarationThe lead author* affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained.

Patient involvement Patients were involved in the interpretation of results and the generation of parallel recommendations, as part of the BMJ Rapid Recommendations initiative.

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Role of the funding sourceThis study was conducted without financial support.

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What is already known/ what this paper adds

Despite huge efforts to identify effective interventions for COVID-19 prevention and treatment evidence of effective treatment remains limited.

This living systematic review and network meta-analysis provides a comprehensive picture and assessment of the evidence published as of June 10, 2020; and will be updated periodically

The certainty of the evidence for most interventions tested thus far is low or very low.

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AbstractObjectives: To compare the effects of therapies for prophylaxis and treatment of COVID-19Design: Living systematic review and network meta-analysis (NMA).Data sources: U.S. Centers for Disease Control and Prevention (CDC) COVID-19 Research Articles Downloadable Database, which includes 25 electronic databases up to June 10, 2020Study selection: We included randomized clinical trials (RCTs) in which persons exposed to COVID-19 or with suspected, probable or confirmed COVID-19 received pharmaceuticals or blood products aimed at prophylaxis or treatment. Pairs of reviewers independently screened titles and abstracts, and full texts, of potentially eligible articles.Methods: After duplicate data abstraction, we conducted a Bayesian-random effects network meta-analysis for each outcome of interest. We assessed the risk of bias of the included studies using a modification of the Cochrane Risk of Bias 2.0 tool, and the certainty of the evidence using the GRADE approach for NMA. We classified interventions in groups from the most to the least effective/ harmful following GRADE guidance using a minimally contextualized approach. Results: As of June 10, 2020, we identified 22 RCTs and included 18 in NMAs for pharmacological treatment of patients with COVID-19. The other studies will be included in NMAs for blood products and prophylaxis. The certainty of the evidence for the majority of comparisons is very low. There is no convincing evidence that any of the interventions has benefits in mortality or viral clearance. Remdesivir is probably the most effective intervention in time to symptom resolution (mean difference 2.05 days, 95% credible interval -3.37 to -0.44 when compared to standard care) and duration of mechanical ventilation (-5.15, -8.28 to -2.02 days when compared to standard care). Lopinavir-ritonavir may reduce intensive care unit length of stay (-5.33 (-7.65 to -3.01 days when compared to standard care. Hydroxychloroquine may increase the risk of adverse events when compared to the other interventions. There was no convincing evidence that the other interventions resulted in benefits or harms.Conclusion: Remdesivir probably reduces time to symptom resolution and lopinavir ritonavir may reduce intensive care unit stay. Hydroxychloroquine may result in adverse events. Evidence for most interventions tested thus far is low or very low certainty.Protocol: Published in REF TO PROTOCOL

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BackgroundAs of 18 June 2020, over 8.5 million people have been infected with COVID-19; of these, 456,000 have died.1 Despite huge efforts to identify effective interventions for its prevention and treatment- which have resulted in almost 1,500 trials completed or under way-2 evidence of effective treatment remains limited.

Clinicians, patients, guideline bodies, and government agencies are facing the challenges of interpreting the results from trials that are being published at a rate never seen before. This environment makes it necessary to produce well-developed summaries that distinguish more from less trustworthy evidence.

Living systematic reviews (SRs) and network meta analyses (NMAs) address the main limitation of traditional reviews, that of providing a picture of the relevant evidence only at a specific timepoint.3 This is crucial in the context of COVID-19, in which the picture is constantly changing. The ability of living NMA to present a complete, broad, and updated view of the evidence makes it ideal to inform the development of practice recommendations.

The objective of this living SR and NMA is to compare the effects of therapies for prophylaxis and treatment of COVID-19. This SR is part of the BMJ Rapid Recommendations project, a collaborative effort from the MAGIC Evidence Ecosystem Foundation (www.magicproject.org) and The BMJ. Our living NMA will directly inform BMJ Rapid Recommendations4 on COVID-19 treatments, triggered to provide trustworthy, actionable, and living guidance to clinicians and patients soon after new and potentially practice-changing evidence becomes available.

MethodsA published protocol provides the detailed methods of this SR.(REF protocol) We report this living SR following the guidelines of the PRISMA checklist for NMA.5 Because of the relationship with the Rapid Recommendations the guideline panel approved all decisions relevant to data synthesis were approved.

Eligibility criteria We included randomized clinical trials (RCT) in persons exposed to COVID-19 or with suspected, probable or confirmed COVID-19 that compared pharmaceuticals or blood products aimed at prophylaxis or treatment against one another or against no intervention, placebo, or standard care. We included trials regardless of publication status (peer-reviewed, in press, or pre-print) or language. We applied no restriction based on severity of illness or setting and included trials of and Chinese medicines if the drug was one specific molecule.

We excluded RCTs evaluating vaccination, plasma exchange, nutrition, traditional Chinese herbal medicines that include more than one molecule or a molecule without specific molecular weighted dosing and non-drug supportive care interventions. RCTs including patients with COVID-19 that evaluated these interventions were identified and categorized separately, for potential future use.

Information sourcesWe perform daily searches Monday to Friday in the U.S. Centers for Disease Control and Prevention (CDC) COVID-19 Research Articles Downloadable Database for eligible studies—the most comprehensive database of COVID-19 research articles—from December 2019 to June 10 2020 6. The database includes 25 bibliographic and grey literature sources: Medline (Ovid and PubMed), PubMed Central, Embase, CAB Abstracts, Global Health, PsycInfo, Cochrane Library, Scopus, Academic Search Complete, Africa

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Wide Information, CINAHL, ProQuest Central, SciFinder, the Virtual Health Library, LitCovid, WHO COVID-19 website, CDC COVID-19 website, Eurosurveillance, China CDC Weekly, Homeland Security Digital Library, ClinicalTrials.gov, bioRxiv (preprints), medRxiv (preprints), chemRxiv (preprints), and SSRN (preprints).

The daily searches are designed to match the update schedule of the database and to capture eligible studies the day of or day after their publication. We filtered the results from the CDC’s database through a validated and highly sensitive machine learning model to identify randomized controlled trials (RCTs).7 We tracked preprints of RCTs until publication and updated data to match that in the peer-reviewed publication when discrepant and reconciled corrections and retractions.

In addition, we searched six Chinese databases on a biweekly basis: Wanfang, CBM, CNKI, VIP, Chinese Medical Journal Net (preprints), and ChinaXiv (preprints). We adapted the search terms for COVID-19 developed by the CDC to the Chinese language. For the Chinese literature search, we also included search terms for randomized trials. The Supplementary Material includes the search strategy.

We monitor living evidence retrieval services on an ongoing basis. These included the Living Overview of the Evidence (L-OVE) COVID-19 Repository by the Epistemonikos Foundation and the Systematic and Living Map on COVID-19 Evidence by the Norwegian Institute of Public Health, in collaboration with the Cochrane Canada Centre at McMaster University. 8

Study selectionUsing a SR software, Covidence,9 pairs of trained and calibrated reviewers independently screened all titles and abstracts followed by full texts of potentially eligible trials. A third reviewer adjudicated conflicts.

Data collectionFor each eligible trial, pairs of reviewers, following training and calibration exercises, extracted data independently using a standardised, pilot-tested data extraction form (reference protocol). Reviewers collected information on trial characteristics (trial registration, publication status, study status, design), patient characteristics (country, age, sex, smoking habits, comorbidities, setting and type of care, severity of COVID-19 symptoms for studies of treatment, and type of exposure to COVOD-19 for trials of prophylaxis), and outcomes of interest (means or medians and measures of variability for continuous outcomes and the number of participants analyzed and the number of participants that experienced an event for dichotomous outcomes).

Outcomes of interest were selected based on their importance to patients and were informed by clinical expertise in the SR team and in the linked guideline panel responsible for the BMJ Rapid Recommendations. The panel includes unconflicted clinical experts, recruited to ensure global representation, and patient-partners. Selected outcomes included mortality (closest to 90 days), mechanical ventilation (total number of patients, over 90 days), adverse events leading to discontinuation (within 28 days), viral clearance (closest to 7 days +/- 3 days), duration of hospitalization, ICU length of stay, time to symptom resolution or clinical improvement, and time to viral clearance. Outcomes of interest for prophylaxis of COVID-19 include mortality, infection with COVID-19, hospitalization, adverse events leading to discontinuation, and time to symptom resolution or clinical improvement.

Because of the inconsistent reporting observed across trials, in the updates we will use a hierarchy for the outcome mechanical ventilation in which we will include information

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from the total number of patients who received ventilation over a time period if available (as done for this analysis), but we will also include the number at the time point in which most of the patients were mechanically ventilated if that is the only way in which this outcome is reported.

Reviewers resolved discrepancies by discussion and, when necessary, by adjudication by a third party.

We update the data collected from included studies when they were published as pre-print or as soon as the peer-review publication becomes available.

Risk of bias within individual studiesFor each eligible trial, reviewers, following training and calibration exercises, used a revision of the Cochrane tool for assessing risk of bias in randomized trials (RoB 2.0)10 to rate trials as either ‘low risk of bias’, ‘some concerns – probably low risk of bias’, ‘some concerns – probably high risk of bias’ and ‘high risk of bias’, across the following domains: bias arising from the randomization process, bias due to departures from the intended intervention, bias due to missing outcome data, bias in measurement of the outcome, bias in selection of the reported results, and bias arising from early termination for benefit (reference protocol). We rated trials at high risk of bias overall if one or more domains were rated at ‘some concerns – probably high risk of bias’ or ‘high risk of bias’ and at low risk of bias if all domains were rated at ‘some concerns – probably low risk of bias’ or ‘low risk of bias’. Reviewers resolved discrepancies by discussion and, when not possible, by adjudication by a third party.

Data synthesisWe conducted NMA using a Bayesian framework.11 In this report, we conducted an NMA for pharmacological treatments of COVID-19 that included all patients, regardless of severity of disease. We plan to conduct separate NMAs for prophylaxis and blood products.

a. Summary measuresWe summarized the effect of interventions on dichotomous outcomes using the odds ratio (OR) and its 95% credible intervals (CI). For continuous outcomes, we used the mean difference (MD) and its 95% CI when the outcomes were not expected to vary importantly across subpopulations. For other continuous outcomes (time to symptom resolution and duration of hospitalization), we used the ratio of means (RoM) and its 95% CI.

b. Treatment nodesTreatments were grouped into common nodes based on molecule but not dose or duration. For intervention arms with more than one medication, we created a separate node and included drugs from the same class within the same node. Chloroquine and hydroxychloroquine were included in the same node for COVID-19 specific effects and separated for disease-independent adverse effects. We drew network plots using the networkplot command of Stata version 15.1 (StataCorp, College Station, Texas, USA) with thickness of edges of the nodes based on inverse variance.12

c. Statistical analysisFor most outcomes, we conducted random-effects NMAs using a Bayesian framework with the same priors for the variance and effect parameters.11 Because the network for the outcome time to symptoms resolution was sparse, we conducted fixed-effect NMA.13 For all analyses, we used three Markov-chains with 100,000 iterations after an initial burn-in of 10,000 and a thinning of 10. We used node-splitting models to assess local

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incoherence and to obtain indirect estimates.14 All NMAs were performed using the gemtc package of R version 4.0.0 (RStudio, Boston, MA).15

Certainty of the evidenceWe assessed the certainty of evidence using the GRADE approach for NMA.16-18 We rated the certainty for each comparison and outcome as high, moderate, low, or very low, based on considerations of risk of bias, inconsistency, indirectness, publication bias, intransitivity, incoherence, imprecision and coherence between direct and indirect evidence.18 Judgments of imprecision for this SR were made using a minimally contextualized approach, with a null effect as the threshold of importance.19 We created GRADE evidence summaries (Summary of Findings tables) in the MAGIC Authoring and publication platform (MAGICapp/ www.magicapp.org) to provide user-friendly formats for clinicians and patients, and allow re-use in the context of clinical practice guidelines for COVID-19.

Interpretation of resultsTo facilitate interpretation of the results, we calculated absolute effects for outcomes in which the summary measure was OR or RoM. For the outcomes mortality and mechanical ventilation, we used baseline risks from the International Severe Acute Respiratory and Emerging Infection COVID-19 database.20 For all other outcomes, we used the mean from all studies in which participants received standard of care for each outcome. We calculated absolute effects using the transitive risks model21 using R2jags package in R.22

For each outcome, we classified treatments in groups from the most to the least effective using the minimally contextualized framework that focuses on the treatment effect estimates and the certainty of the evidence.23

Subgroup and sensitivity analysisDue to the lack of sufficient data, we did not conduct any of the subgroup or sensitivity analyses specified in the protocol (REF TO PROTOCOL).

Results

Following screening of 4,714 titles and abstracts, and 93 full-texts, we identified 22 unique RCTs as of June 10 (Figure 1).24-44 Searches of living evidence retrieval services identified one additional eligible RCT.45 Thirteen RCTs have been published in peer-reviewed journals; and nine only as as preprints. Most trials were registered (21/22; 95%), published in English (20/22; 91%) and evaluated treatment in hospitalized patients with COVID-19 (20/22; 91%). Two-thirds were conducted in China (15/22; 68%), with the remainder conducted at sites globally. Our NMA was run on June 06, 2020 and includes 18 RCTs.25 26 28-33 35 37-44 Table 1 presents the characteristics of the 18 included studies.

The RCTs not included in the analysis are: 1) a trial evaluating 5 vs 10 day remdesivir which was excluded because both arms would have been classified in the same node,34 2) One trial evaluating convalescent plasma therapy that will be included in a separate meta-analysis when additional trials of blood products are published,36 and 3) two trials, one addressing ramipril24 and the second addressing hydroxychloroquine,27 for preventing SARS-CoV-2 infection and disease that will be included in future analyses of prophylaxis.

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Figure 1: Study selection

As of June 10, 2020: 4714 records identified from literature search

4428 English bibliographic databases and pre-print servers286 Chinese bibliographic databases and pre-print servers

4590 records excluded for not being relevant

93 full text articles assessed for eligibility

28 randomized trials included

4683 records after duplicates removed

65 full text articles excluded29 not a randomized trial14 randomized trial with no results2 not exposed to or infected with COVID-1920 wrong intervention

13 traditional Chinese medicine excluding specific 13 molecules at specific doses2 exercise/rehabilitation2 personal protective equipment1 diagnostic Imaging 1 psychological and educational 1 other

22 unique randomized trials included20 English and 2 Chinese texts13 published and 9 preprints20 treatment and 2 prophylaxis

3 pre-prints of published trials1 correction2 duplicates

18 unique randomized trials on treatment analyzed

1 Epistemonikos COVID-19 Evidence

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Risk of bias in included studiesThe supplementary material presents the assessment of risk of bias of the 18 included studies per outcome. Two studies were judged at low risk of bias in all domains.25 40 All other studies had probably high or high risk of bias in the domains of randomization or deviation from the intended interventions.

Effects of the interventionsThe supplementary material presents the network plots depicting the interventions included in the NMA of each outcome. Table 2 presents a summary of the effects of the interventions on the outcomes. The supplementary material presents detailed relative and absolute effect estimates and certainty of the evidence for all comparisons and outcomes. We did not detect statistical incoherence in any of the NMAs.

a. MortalityThe 13 RCTs including 2,055 participants25 28-31 33 35 37-41 44 that addressed mortality revealed no convincing evidence that any intervention reduced mortality. The certainty of the evidence was low for the comparison between remdesivir and standard of care, and very low for all other comparisons (Table 2).

b. Mechanical ventilation riskSix RCTs that enrolled 713 participants28 29 33 35 37 40 provided low certainty evidence that, when compared to standard of care, a combination of Ribavirin and Lopinavir-Ritonavir, as well as Ruxolitinib reduced the risk of mechanical ventilation (Table 2). There was low certainty evidence that baloxavir-marboxil increased the likelihood of mechanical ventilation. There was low certainty evidence that favipiravir, interferon beta 1a, and lopinavir-ritonavir did not reduce or increase the risk of mechanical ventilation when compred to standard of care (Table 2).

c. Adverse events leading to discontinuationEleven RCTs that enrolled 1,827 participants25 32 33 35 38-44 provided low certainty evidence that alpha lipoic acid, diammonium glycyrrhizinate, novaferon, a combination of novaferon and lopinavir ritonavir, remdesivir, and a combination of ribavirin and interferon beta did not incur additional harm beyond standard care though confidence intervals were sufficiently wide to render the results almost completely uninformative (Table 2). Results provided low certainty evidence that hydroxychloroquine, interferon beta 1a, and lopinavir-ritonavir resulted in adverse events beyond that observed with standard care (Table 2).

d. Viral clearance at 7 days (+/- 3 days) Nine RCTs enrolling 823 participants included28 31 37 39-42 44 45 provided no convincing evidence that any of the interventions increased the rate of viral clearance (Table 2). The certainty of the evidence was low for the comparison between remdesivir and standard care, and very low for all other comparisons.

e. Duration of hospitalizationSeven RCTs enrolling 807 participants28 29 31 33 35 40 45 provided low certainty evidence that a combination of ribavirin and interferon beta 1b reduced duration of hospitalization (MD -3.6 days, 95% CI -5.8 to -1.4) when compared to standard care. There was no convincing evidence that any of the other interventions reduced duration of hospitalization (Table 2).

f. ICU length of stayTwo RCTs enrolling 280 participants28 33 provided moderate certainty evidence that lopinavir-ritonavir has benefits in this outcome (MD [95% CI], -5.33 [-7.65 to -3.01] days

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when compared to standard care), and no convincing evidence that interferon beta 1a reduces intensive care unit length of stay (Table 2).

g. Duration of mechanical ventilationFour RCTs and 557 participants 28 29 33 40 provided moderate certainty evidence that remdesivir has a benefit in reducing the duration of mechanical ventilation (MD [95% CI], -5.15 [-8.28 to -2.02] days when compared to standard care). There was no convincing evidence that any of the other interventions reduced duration of mechanical ventilation (Table 2).

h. Time to symptom resolutionThirteen RCTs enrolling 2,239 participants25 28-33 35 37 39 40 44 45 provided moderate certainty evidence that remdesivir (MD [95% CI], -2.05 [-3.37 to -0.44] days when compared to standard care) reduced the time to symptoms resolution. Low certainty evidence suggested that hydroxychloroquine (MD -3.52, 95% CI -4.55 to -2.2 days when compared to standard care) and a combination of ribavirin and interferon beta 1b was also among the most effective interventions for this outcome (MD [95% CI], -0.88 [-1.61 to -0.29] day reductions when compared to standard care) (Table 2).

i. Time to viral clearanceNine RCTs enrolling 651 participants29 31 35 37 39 41 42 44 45 revealed no convincing evidence that any of the interventions reduced the time to viral clearance. The certainty of the evidence was very low for all comparisons (Table 2).

Discussion

This living SR and NMA provides a comprehensive picture of the evidence for treatments of COVID-19 up to June 10, 2020. The certainty of the evidence for the majority of the evidence is very low. There is no convincing evidence that any of the interventions reduce mortality or viral clearance. Remdesivir is the only intervention in which moderate certainty exists supporting reductions in both time to symptom resolution and duration of mechanical ventilation. Lopinavir-ritonavir probably reduces intensive care unit length of stay and may increase adverse events when compared to the other interventions. Hydroxychloroquine, lopinavir-ritonavir, and interferon beta 1-a may increase the risk of adverse events when compared to the other interventions. There was no convincing evidence that the other interventions resulted in benefits or harms.

We conducted this SR with the highest methodological standards. Our search strategy and eligibility criteria were comprehensive, without restrictions of language of publication, and provide a full picture of the current evidence. To ensure expertise in all areas, our team is composed of clinical and methods experts trained and calibrated for all stages of the review process. In order to minimize problems with counterintuitive results, the data analysis plan anticipated challenges that arise in NMA when data is sparse 13. We assessed the certainty of the evidence using the GRADE approach and interpreted the results considering absolute effects. In the future, when more data from more treatments are available, our classification of interventions from the most to the least effective will facilitate clear interpretation of results.

The main limitation of the systematic review is the very low quality of the evidence as a result of the current sparse data available. Despite safeguards in our analysis plan, the sparseness resulted in highly implausible point estimates for binary outcomes (death and mechanical ventilation rates at or near 100%, mechanical ventilation rates of 0, adverse event rates of 100%) (Table 2). There was also not sufficient evidence to conduct NMAs for blood products and prophylaxis for COVID-19. As the many ongoing trials are

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completed, we anticipate that the effect estimates will quickly become both plausible and informative as the quality of the evidence rises.

Another limitation of this SR is the limited quality of reporting. For some outcomes, the method in which the researchers measured and reported outcomes proved inconsistent across studies did not match across studies and thus such studies could not be included in the NMAs. This led the team to propose a hierarchy for the outcome mechanical ventilation as described in the methods. We expect that the relative effect will not vary importantly across methods of measurements and will an analysis using this hierarchy in the update.

Our living NMA is informing the development of the BMJ Rapid Recommendations. There is, however, an important difference in the methods for assessing the certainty of the evidence between the two. In this SR and living NMA, we are using a minimally contextualized approach for rating the certainty of the evidence, whereas the BMJ Rapid Recommendations are using a fully contextualized approach in which the thresholds of importance of magnitudes of effects depend on all other outcomes and factors involved in the decision.19 The contextualization explains potential differences in the certainty of the evidence between the two. The limitations of potentially misleading results when the network is sparse, and the desirability of focusing on direct estimates from larger studies when this is the case, explains differences in the details of the estimates of effect in this NMA and in the associated Remdisivir guidelines.

To date, we are aware of two other efforts similar to ours.46 47 We are collaborating with both teams to ensure replicability and mutual learning concerning methods and processes. The rationale for proceeding independently and using our approach was to fully inform the associated living guidance in BMJ Rapid Recommendations.

We will periodically update this SR and living NMA. The changes from each version with be highlighted to readers and the most updated version will be the one available in the publication platform. This SR and living NMA will also be accompanied by interactive infographics and a website for users to access the most updated results in a user-friendly format.

Conclusions The evidence suggests that remdesivir and lopinavir ritonavir probably improve time to symptoms resolution, and that hydroxycholoquine may result in adverse events. Most evidence is currently low certainty, and no convincing evidence exists that other interventions result in important benefits and harms in any outcomes.

AcknowledgmentsTo discuss wording to acknowledge collaboration with BMJ

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10. Sterne JAC SJ, Page MJ, Elbers RG, Blencowe NS, Boutron I, Cates CJ, Cheng H-Y, Corbett MS, Eldridge SM, Hernán MA, Hopewell S, Hróbjartsson A, Junqueira DR, Jüni P, Kirkham JJ, Lasserson T, Li T, McAleenan A, Reeves BC, Shepperd S, Shrier I, Stewart LA, Tilling K, White IR, Whiting PF, Higgins JPT. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ 2019;366:I4898.

11. Röver C. Bayesian random-effects meta-analysis using the bayesmeta R package. arXiv preprint arXiv:171108683 2017

12. Chaimani A, Higgins JP, Mavridis D, et al. Graphical tools for network meta-analysis in STATA. PLoS One 2013;8(10):e76654. doi: 10.1371/journal.pone.0076654 [published Online First: 2013/10/08]

13. Brignardello-Petersen R, Murad MH, Walter SD, et al. GRADE approach to rate the certainty from a network meta-analysis: avoiding spurious judgments of imprecision in sparse networks. J Clin Epidemiol 2019;105:60-67. doi: 10.1016/j.jclinepi.2018.08.022 [published Online First: 2018/09/27]

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14. van Valkenhoef G, Dias S, Ades AE, et al. Automated generation of node-splitting models for assessment of inconsistency in network meta-analysis. Res Synth Methods 2016;7(1):80-93. doi: 10.1002/jrsm.1167 [published Online First: 2015/10/16]

15. gemtc: Network Meta-Analysis Using Bayesian Methods [program]. R package version 0.8-4 version, 2020.

16. Brignardello-Petersen R, Bonner A, Alexander PE, et al. Advances in the GRADE approach to rate the certainty in estimates from a network meta-analysis. J Clin Epidemiol 2018;93:36-44. doi: 10.1016/j.jclinepi.2017.10.005 [published Online First: 2017/10/21]

17. Puhan MA, Schunemann HJ, Murad MH, et al. A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. Bmj 2014;349:g5630. doi: 10.1136/bmj.g5630 [published Online First: 2014/09/26]

18. Brignardello-Petersen R, Mustafa RA, Siemieniuk RAC, et al. GRADE approach to rate the certainty from a network meta-analysis: Addressing Incoherence. J Clin Epidemiol 2018 doi: 10.1016/j.jclinepi.2018.11.025 [published Online First: 2018/12/12]

19. Hultcrantz M, Rind D, Akl EA, et al. The GRADE Working Group clarifies the construct of certainty of evidence. J Clin Epidemiol 2017;87:4-13. doi: 10.1016/j.jclinepi.2017.05.006 [published Online First: 2017/05/23]

20. ISARIC (International Severe Acute Respiratory and Emerging Infections Consortium). COVID-19 Report: 08 June 2020, 2020.

21. Spineli L, Brignardello-Petersen R, Heen A, et al. Obtaining absolute effect estimates to facilitate shared decision making in the context of multiple comparisons. Global Evidence Summit. Cape Town, South Africa, 2017.

22. R2jags: Using R to Run 'JAGS' [program]. R package version 0.6-1 version, 2020.23. Brignardello-Petersen R, Florez I, Izcovich A, et al. GRADE approach to drawing conclusions

from a network meta-analysis using a minimally contextualized framework [Submitted for publication}. 2020

24. Amat-Santos IJ, Santos-Martinez S, López-Otero D, et al. Ramipril in High Risk Patients with COVID-19. Journal of American College of Cardiology 2020 doi: 10.1016/j.jacc.2020.05.040

25. Beigel JH, Tomashek KM, Dodd LE, et al. Remdesivir for the Treatment of Covid-19 - Preliminary Report. The New England journal of medicine 2020 doi: 10.1056/NEJMoa2007764

26. Borba MGS, Val FFA, Sampaio VS, et al. Effect of High vs Low Doses of Chloroquine Diphosphate as Adjunctive Therapy for Patients Hospitalized With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection: A Randomized Clinical Trial. JAMA Network Open 2020;3(4):e208857-e57. doi: 10.1001/jamanetworkopen.2020.8857

27. Boulware DR, Pullen MF, Bangdiwala AS, et al. A Randomized Trial of Hydroxychloroquine as Postexposure Prophylaxis for Covid-19. The New England journal of medicine 2020 doi: 10.1056/NEJMoa2016638

28. Cao B, Wang Y, Wen D, et al. A Trial of Lopinavir-Ritonavir in Adults Hospitalized with Severe Covid-19. N Engl J Med 2020;18:18. doi: https://dx.doi.org/10.1056/NEJMoa2001282

29. Cao Y, Wei J, Zou L, et al. Ruxolitinib in treatment of severe coronavirus disease 2019 (COVID-19): A multicenter, single-blind, randomized controlled trial. Journal of Allergy and Clinical Immunology 2020 doi: 10.1016/j.jaci.2020.05.019

30. Chen C, Huang J, Cheng Z, et al. Favipiravir versus Arbidol for COVID-19: A Randomized Clinical Trial. medRxiv 2020:2020.03.17.20037432. doi: 10.1101/2020.03.17.20037432

31. Chen Y-K, Huang Y-Q, Tang S-Q, et al. Comparative Effectiveness and Safety of Ribavirin Plus Interferon-Alpha, Lopinavir/Ritonavir Plus Interferon-Alpha and Ribavirin Plus Lopinavir/Ritonavir Plus Interferon-Alpha in Patients with Mild to Moderate Novel Coronavirus Pneumonia: Results of a Randomized, Open-Labeled Prospective Study. SSRN 2020

32. Chen Z, Hu J, Zhang Z, et al. Efficacy of hydroxychloroquine in patients with COVID-19: results of a randomized clinical trial. medRxiv 2020:2020.03.22.20040758. doi: 10.1101/2020.03.22.20040758

33. Davoudi-Monfared E, Rahmani H, Khalili H, et al. Efficacy and safety of interferon beta-1a in treatment of severe COVID-19: A randomized clinical trial. medRxiv 2020:2020.05.28.20116467. doi: 10.1101/2020.05.28.20116467

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34. Goldman JD, Lye DCB, Hui DS, et al. Remdesivir for 5 or 10 Days in Patients with Severe Covid-19. The New England journal of medicine 2020 doi: 10.1056/NEJMoa2015301

35. Hung IF-N, Lung K-C, Tso EY-K, et al. Triple combination of interferon beta-1b, lopinavir–ritonavir, and ribavirin in the treatment of patients admitted to hospital with COVID-19: an open-label, randomised, phase 2 trial. Lancet 2020 doi: https://doi.org/10.1016/S0140-6736(20)31042-4

36. Li L, Zhang W, Hu Y, et al. Effect of Convalescent Plasma Therapy on Time to Clinical Improvement in Patients With Severe and Life-threatening COVID-19: A Randomized Clinical Trial. Jama 2020 doi: 10.1001/jama.2020.10044

37. Lou Y, Liu L, Qiu Y. Clinical Outcomes and Plasma Concentrations of Baloxavir Marboxil and Favipiravir in COVID-19 Patients: an Exploratory Randomized, Controlled Trial. medRxiv 2020:2020.04.29.20085761. doi: 10.1101/2020.04.29.20085761

38. Zhong M, Sun A, Xiao T, et al. A Randomized, Single-blind, Group sequential, Active-controlled Study to evaluate the clinical efficacy and safety of α-Lipoic acid for critically ill patients with coronavirus disease 2019（COVID-19）. medRxiv 2020 doi: 10.1101/2020.04.15.20066266

39. Tang W, Cao Z, Han M, et al. Hydroxychloroquine in patients with mainly mild to moderate coronavirus disease 2019: open label, randomised controlled trial. BMJ 2020;369 doi: http://dx.doi.org/10.1136/bmj.m1849

40. Wang Y, Zhang D, Du G, et al. Remdesivir in adults with severe COVID-19: a randomised, double-blind, placebo-controlled, multicentre trial. Lancet 2020 doi: https://doi.org/10.1016/S0140-6736(20)31022-9

41. Yueping Li ZXWLWCCWYGXMJWYWPPXCWHGXJLLZF. Efficacy and safety of lopinavir/ritonavir or arbidol in adult patients with mild/moderate COVID-19: an exploratory randomized controlled trial. Cell Press 2020 doi: 10.1016/j.medj.2020.04.001

42. Zheng F, Zhou Y, Zhou Z, et al. A Novel Protein Drug, Novaferon, as the Potential Antiviral Drug for COVID-19. medRxiv 2020:2020.04.24.20077735. doi: 10.1101/2020.04.24.20077735

43. Waimin Z, Fuming Z, Banglong L, et al. Diamine glycyrrhizinate in common COVID-19 patients.

Clinical value in treatment. Chinese Journal of Virology 2020;36(2):160-64.44. Chen Jun, Liu Danping, Liu Li, et al. A preliminary study of hydroxychloroquine sulfate in

patients with common 2019 coronavirus disease (COVID-19). Journal of Zhejiang University (Medical Sciences) 2019;49(2):215-19.

45. Huang M, Tang T, Pang P, et al. Treating COVID-19 with Chloroquine. Journal of molecular cell biology 2020;12(4):322-25. doi: 10.1093/jmcb/mjaa014

46. Schandelmaier S, Briel M, Varadhan R, et al. A new instrument to assess the credibility of effect modification analyses (ICEMAN) in randomized controlled trials and meta-analyses CMAJ [In Press] 2020

47. Boutron I, Chaimani A, Devane D, et al. Interventions for preventing and treating COVID-19: protocol for a living mapping of research and a living systematic review. 2020

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https://doi.org/10.1016/S0140-6736(20)31042-4http://dx.doi.org/10.1136/bmj.m1849https://doi.org/10.1016/S0140-6736(20)31022-9

Confidential: For Review OnlyStudy

Publication statusRegistration

Number ofparticipants

Beigel, 2020 Published 1063ACTT-1 NCT04280705

Cao_1, 2020 Published 199LOTUS China ChiCTR2000029308

Cao_2, 2020 Published 43ChiCTR-OPN-2000029580

Chen_1, 2020 Pre-print 62ChiCTR2000029559

Chen_2, 2020 Pre-print 240ChiCTR2000030254

Chen_3, 2020 Published 101ChiCTR2000029387

Chen_4, 2020 Published 30NCT04261517

Davoudi-Monfared, Preprint 922020 IRCT20100228003449N28

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Confidential: For Review OnlyHuang, 2020 Published 22

ChiCTR2000029542

Hung, 2020 Published 127NCT04276688

Li, 2020 Pre-print 86ELACOI NCT04252885

Lou, 2020 Pre-print 30ChiCTR2000029544

Silva Borba, 2020 Published 81CloroCOVID-19 NCT04323527

Tang, 2020 Published 150ChiCTR2000029868

Wang, 2020 Published 237NCT04257656

Zheng, 2020 Pre-print 89

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ChiCTR2000029496

Zhong, 2020 Pre-print 17ChiCTR2000029851

Zhou, 2020 Published 104

NR: not reported

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Confidential: For Review OnlyCountry Mean age % Male Comorbidities Type of care

United States, Denmark, 58.9 64.3 Coronary artery disease (11.6%) InpatientUnited Kingdom, Greece, Congestive heart failure (5.0%)Germany, Korea, Mexico, Diabetes (29.7%)

Spain, Japan, Singapore Hypertension (49.6%)Asthma (11.4%)Chronic oxygen requirement (2.2%)Chronic respiratory disease (7.6%)

China 58.0 60.3 Cerebrovascular disease (6.5%) InpatientDiabetes (11.6%)

China 63.0 58.5 Coronary artery disease (7.3%) InpatientDiabetes (19.5%)Hypertension (39.0%)

China 44.7 46.8 NR Inpatient

China NR 46.6 Diabetes (11.4%) NRHypertension (28.0%)

China 42.5 45.5 Severe heart disease (0%) NRSevere lung disease (0%)

China 48.6 70.0 Severe heart disease (0%) InpatientDiabetes (6.7%) Intensive care (0%)Hypertension (26.7%)Chronic obstructive pulmonary disease (3.3%)Severe lung disease (0%)

Iran 57.8 53.1 Cardiovascular disease (28.4%) InpatientDiabetes (27.2%)

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Hypertension (38.3%)Asthma (1.2%)Chronic obstructive pulmonary disease (1.2%)

China 44.0 59.1 Cerebrovascular disease (4.5%) InpatientDiabetes (9.1%)Hypertension (18.2%)

China 51.3 53.5 Coronary artery disease (7.9%) InpatientCerebrovascular disease (1.6%)Diabetes (13.4%)Hypertension (28.4%)Obstructive sleep apnea (1.6%)Tuberculosis (1.6%)

China 49.4 46.5 Cardiovascular disease (2.3%) InpatientDiabetes (2.3%)Hypertension (10.5%)Respiratory condition (0%)

China 52.5 72.4 Cardiovascular disease (13.8%) InpatientDiabetes (6.9%) Intensive care (0%)Hypertension (20.7%)Chronic obstructive pulmonary disease (0%)

Brazil 51.1 75.3 Cardiovascular disease (9.1%) InpatientDiabetes (25.5%) Intensive care (45.7%)Hypertension (45.5%)Asthma (7.4%)Tuberculosis (3.6%)

China 46.1 55.0 Cardiovascular disease (0%) InpatientDiabetes (14.0%)Hypertension (6.0%)

China 65.0 59.3 Cardiovascular disease (7.2%) InpatientDiabetes (23.7%)Hypertension (43.2%)

China 46.7 47.2 Severe heart disease (0%) Inpatient

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Severe lung disease (0%)

China 63.0 76.5 Cardiovascular disease (5.9%) InpatientDiabetes (23.5%)Hypertension (47.1%)

China 52.1 57.7 Severe heart disease (0%) InpatientHypertension (0%) Intensive care (0%)Interstitial pneumonia (0%)

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Confidential: For Review OnlySeverity

% Mechanicalventilation

(at baseline)Mild/Moderate (11.3%) 44.1

Severe (88.7%)

Severe (100%) 16.1

Severe (100%) 12.2

Mild/Moderate (100%) NR

Mild/Moderate (88.6%) NRSevere (10.2%)Critical (1.3%)



Severe (100%) 29.6

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Confidential: For Review OnlyMild/Moderate (63.6%) NR

Severe (36.4%)

Mild/Moderate (100%) 0

Mild/Moderate (100%) 0

Critical (0%) 0

Severe (100%) NR

Mild/Moderate (99.0%) NRSevere (1.0%)

Severe (100%) 16.1

Mild/Moderate (94.4%) NR

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Severe (5.6%)

Critical (100%) 94.1


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Confidential: For Review OnlyTreatments (dose and duration) Outcomes

remdesivir (100 mg/day for 10 days) Mortalityplacebo Adverse effects leading to discontinuation

Time to symptom/clinical improvement

lopinavir-ritonavir (400 mg and 100 mg BID for 14 days) Mortalitystandard care Mechanical ventilation

Viral clearanceDuration of hospitalizationICU length of stayDuration of ventilationTime to symptom/clinical improvement

ruxolitinib (5 mg BID) Mortalityplacebo Mechanical ventilation

Duration of hospitalizationDuration of ventilationTime to symptom/clinical improvementTime to viral clearance

hydroxychloroquine (200 mg BID for 5 days) Adverse effects leading to discontinuationstandard care Time to symptom/clinical improvement

favipiravir (600 mg BID for 7 days) Mortalityumifenovir (200 mg TID for 7 days) Time to symptom/clinical improvement

ribavirin (400-600 mg TID for 14 days), interferon-⍺ (5 mg BID for 14 days)Mortalitylopinavir-ritonavir (400 mg and 100 mg BID for 14 days), interferon-⍺ (5 mg BID for 14 days)Viral clearanceribavirin (400-600 mg TID for 14 days), lopinavir-ritonavir (400 mg and 100 mg BID for 14 days), interferon-⍺ (5 mg BID for 14 days)Duration of hospitalization

Time to symptom/clinical improvementTime to viral clearance

hydroxychloroquine (400 mg/day for 5 days) Mortalitystandard care Adverse events leading to discontinuation

Viral clearanceTime to symptom/clinical improvementTime to viral clearance

interferon β-1a (44 μg/ml TIW for 14 days) Mortalitystandard care Mechanical ventilation

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Adverse events leading to discontinuationDuration of hospitalizationICU length of stayDuration of ventilationTime to symptom/clinical improvement

chloroquine (500 mg BID for 10 days) Viral clearancelopinavir-ritonavir (400 mg and 100 mg BID for 10 days) Duration of hospitalization


lopinavir-ritonavir (400 mg and 100 mg BID for 14 days), ribavarin (400 mg BID for 14 days), interferon-β 1b (1-3 mL QOD)Mortalitylopinavir-ritonavir (400 mg and 100 mg BID for 14 days) Mechanical ventilation

Adverse effects leading to discontinuationDuration of hospitalizationTime to symptom/clinical improvementTime to viral clearance

lopinavir-ritonavir (200 mg and 50 mg BID for 7 to 14 days) Mortalityumifenovir (200 mg TID for 7 to 14 days) Adverse effects leading to discontinuationstandard care Viral clearance

Time to viral clearance

baloxavir marboxil (80 mg/day for up to 3 doses on days 1, 4, and 7)Mortalityfavipiravir (600 mg TID for 14 days) Mechanical ventilationstandard care Viral clearance


chloroquine (600 mg BID for 10 days) Mortalitychloroquine (450 mg/day for 5 days)

hydroxychloroquine (800 mg/day for 14 to 21 days) Mortalitystandard care Adverse effects leading to discontinuation

Viral clearanceTime to symptom/clinical improvementTime to viral clearance

remdesivir (100 mg/day for 10 days) Mortalityplacebo Mechanical ventilation

Adverse events leading to discontinuationViral clearanceDuration of hospitalizationDuration of ventilationTime to symptom/clinical improvement

novaferon (20 μg BID for 7 to 10 days) Adverse events leading to discontinuation

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novaferon, lopinavir-ritonavir (200 mg and 50 mg BID for 7 to 10 days)Viral clearancelopinavir-ritonavir (200 mg and 50 mg BID for 7 to 10 days) Time to viral clearance

⍺-lipoic acid (1200 mg/day for 7 days) Mortalityplacebo Adverse events leading to discontinuation

diammonium glycyrrhizinate (150 mg TID for 14 days), lopinavir-ritonavir (500 mg BID for 14 days)Adverse events leading to discontinuationlopinavir-ritonavir (500 mg BID for 14 days)

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Mortality Mechanical ventilation Adverse events Viral clearanceDuration of

hospitalization ICU length of stayDuration of

mechanical ventilationTime to symptom

resolutionTime to viral

clearanceStandard care 330 per 1,000 116 per 1,000 17 per 1,000 557 per 1,000 7 days 10 days 10 days 15 days 9 daysα-lipoic acid -265.50 (-325.10 to 43.42) 902.52 (-16.4 to 983.6)baloxavir marboxil 670.00 (-330.00 to 670.00) 884 (67.27 to 884) 106.78 (-425.74 to 408.22) 11.03 (-3.48 ar 65.75) 7.77 (-7.77 to 58.81) 11.03 (-3.48 to 65.75)Diammonium Glycyrrhizinate 734.08 (-16.4 to 983.6)favipiravir 96.52 (-330.00 to 670.00) -116 (-116 to 884) -58.69 (-497.62 to 375.51) 4.25 (-8.65 to 44.58) 8.23 (-3.90 to 52.43)hydroxychloroquine 670.00 (-330.00 to 670.00) 983.60 (286.74 to 983.6) -148.17 (-435.33 to 167.41) -2.64 (-10 to 4.59) -3.52 (-4.55 to -2.20) 2.21 (-1.61 to 8.23)interferon beta-1a -30.77 (-95.44 to 170.50) 983.60 (917.35 tp 983.6) -0.81 (-4.56 to 2.91) 3.05 (-0.19) to (6.25) 2.35 (-1.47 to 7.33)lopinavir-ritonavir -70.90 (-197.54 to 107.64) -26.40 (-91.67 to 165.11) 983.60 (6.09 to 983.6) -216.82 (-497.62 to 56.05) -1.34 (-2.92 to 0.24) -5.33 (-7.65 to -3.01) -1.00 (-2.61) to (0.62) -0.88 (-1.61 to -0.29) -0.08 (-2.63 to 3.90)novaferon 43.48 (-16.4 to 983.60) 70.55 (-486.63 to 384.86) -1.10 (-4.07 to 4.16)novaferon,lopinavir-ritonavir 983.60 (-16.4 to 983.6) 162.55 (-455.15 to 404.71) -2.04 (-4.67 to 2.55)remdesivir -84.67 (-165.41 to 29.59) 1.04 (0.27 to 4.19) 4.18 (-7.97 to 45.68) 12.01 (-407.18 to 350.99) 0.32 (-3.78 to 4.40) -5.15 (-8.28 to -2.02) -2.05 (-3.37 to -0.44)ribavirin -330.00 (-330.00 to 670.00) -296.55 (-544.30 to 191.81) 1.3 (-4.56 to 7.30) 1.03 (-5.72 to 13.05) 2.04 (-2.38 to 10.10)ribavirin,interferon-beta 1b -165.41 (-330.00 to 670.00) 725.01 (-16.40 to 983.6) -3.60 (-5.81 to -1.40) -2.88 (-4.84 to 0.08)ribavirin, lopinavir-ritonavir 644.07 (-330.00 to 670.00) 0 (0 to 0.10) -332.59 (-544.3 to 157.51) -0.01 (-4.71 to 4.74) -1.61 (-8.65 to 13.20) 0.85 (-2.97 to 7.89)ruxolitinib 0 (0 to 0.16) 0.68 (-4.09 to 5.49) -0.73 (-4.25 to 4.25) 0.85 (-5.09 to 17.48)Umifenovir -330.00 (-330.00 to 670.00) 590.90 (-16.40 to 983.6) -317.76 (-544.3 to 91.93) 16.54 (-4.89 to 83.10) -0.08 (-2.71 to 3.99)

Most effective Not different from SC HarmfulHigh/ moderate certaintyLow/ very low certainty

* Number presented are absolute risk differences or mean difference when compared to standard care (95% CI) per 1000 patientsEmpty cells: there was no evidence for the specific intervention

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Search Strategy:

Database StrategyMedline (Ovid) 1946-

(coronavir* OR corona virus* OR betacoronavir* OR covid19 OR covid 19 OR nCoV OR novel CoV OR CoV 2 OR CoV2 OR sarscov2 OR 2019nCoV OR wuhan virus*).mp. OR ((wuhan OR hubei OR huanan) AND (severe acute respiratory OR pneumonia*) AND outbreak*).mp. OR Coronavirus Infections/ OR Coronavirus/ OR betacoronavirus/

Limits: 2020-

OR

(novel coronavir* OR novel corona virus* OR covid19 OR covid 19 OR nCoV OR novel CoV OR CoV 2 OR CoV2 OR sarscov2 OR 2019nCoV OR wuhan virus*).mp. OR ((wuhan OR hubei OR huanan) AND (severe acute respiratory OR pneumonia*) AND outbreak*).mp. OR ((wuhan OR hubei OR huanan) AND (coronavir* OR betacoronavir*)).mp.

Limits: 2019-

Embase (Ovid) 1947-

(coronavir* OR corona virus* OR betacoronavir* OR covid19 OR covid 19 OR nCoV OR novel CoV OR CoV 2 OR CoV2 OR sarscov2 OR 2019nCoV OR wuhan virus*).mp. OR ((wuhan OR hubei OR huanan) AND (severe acute respiratory OR pneumonia*) AND outbreak*).mp. OR Coronavirus infection/ OR coronavirinae/ OR exp betacoronavirus/

Limits: 2020-

OR


Limits: 2019-

CABAbstracts (Ovid) 1910-

(coronavir* OR corona virus* OR betacoronavir* OR covid19 OR covid 19 OR nCoV OR novel CoV OR CoV 2 OR CoV2 OR sarscov2 OR 2019nCoV OR wuhan virus*).mp. OR ((wuhan OR

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hubei OR huanan) AND (severe acute respiratory OR pneumonia*) AND outbreak*).mp. OR exp Betacoronavirus/

Limits: 2020-

OR


Limits: 2019-

Global Health (Ovid) 1910-

(coronavir* OR corona virus* OR betacoronavir* OR covid19 OR covid 19 OR nCoV OR novel CoV OR CoV 2 OR CoV2 OR sarscov2 OR 2019nCoV OR wuhan virus*).mp. OR ((wuhan OR hubei OR huanan) AND (severe acute respiratory OR pneumonia*) AND outbreak*).mp. OR exp Betacoronavirus/

Limits: 2020-

OR


Limits: 2019-

PsycInfo (Ovid) 1806-

(coronavir* OR corona virus* OR betacoronavir* OR covid19 OR covid 19 OR nCoV OR novel CoV OR CoV 2 OR CoV2 OR sarscov2 OR 2019nCoV OR wuhan virus*).mp. OR ((wuhan OR hubei OR huanan) AND (severe acute respiratory OR pneumonia*) AND outbreak*).mp.

Limits: 2020-

OR


Limits: 2019-

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Cochrane Library #1(coronavir* OR "corona virus" OR betacoronavir* OR covid19

OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus"):ti,ab,kw OR ((wuhan OR hubei OR huanan) AND ("severe acute respiratory"OR pneumonia*) AND outbreak*):ti,ab,kw #2MeSH descriptor: [Coronavirus] this term only#3MeSH descriptor: [Coronavirus Infections] this term only #4MeSH descriptor: [Betacoronavirus] this term only#5 #1 OR #2 OR #3 OR#4Limits: 2020-

OR

#1 ( "novel coronavirus" OR "novel corona virus" OR covid19 OR "covid 19" OR nCoV OR "novel CoV" OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "wuhan virus"):ti,ab,kw OR ((wuhan OR hubei OR huanan) AND ("severe acute respiratory" OR pneumonia*) AND outbreak*):ti,ab,kw OR ((wuhan OR hubei OR huanan) AND (coronavir* OR betacoronavir*)):ti,ab,kwLimits: 2019-

Scopus 1960- TITLE-ABS-KEY ( coronavir* OR "corona virus" OR

betacoronavir* OR covid19 OR "covid 19" OR ncov OR "CoV 2" OR cov2 OR sarscov2 OR 2019ncov OR "novel CoV" OR "wuhan virus" ) OR ( TITLE-ABS-KEY ( wuhan OR hubei OR huanan ) AND TITLE-ABS-KEY ( "severe acute respiratory" OR pneumonia* ) AND TITLE-ABS-KEY ( outbreak* ) ) AND ( LIMIT-TO ( PUBYEAR , 2020 ) )

OR

TITLE-ABS-KEY ( "novel coronavirus" OR "novel corona virus" OR covid19 OR "covid 19" OR ncov OR "CoV 2" OR cov2 OR sarscov2 OR 2019ncov OR "novel CoV" OR "wuhan virus" ) OR TITLE-ABS-KEY ( ( wuhan OR hubei OR huanan ) AND ( "severe acute respiratory" OR pneumonia* ) AND outbreak* ) OR TITLE-ABS-KEY ( ( wuhan OR hubei OR huanan ) AND ( coronavir* OR betacoronavir* ) ) AND ( LIMIT-TO ( PUBYEAR , 2020 ) OR LIMIT-TO ( PUBYEAR , 2019 ) )

Academic Search Complete (Ebsco)

TI,AB,SU( (coronavir* OR "corona virus" OR betacoronavir* OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus") OR ((wuhan OR hubei OR huanan) AND ("severe acute respiratory" OR pneumonia*) AND (outbreak*)) )

Limits: Dec. 2019-, peer-reviewed

Africa Wide Information (Ebsco)

TI,AB,SU( (coronavir* OR "corona virus" OR betacoronavir* OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus") OR

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((wuhan OR hubei OR huanan) AND ("severe acute respiratory" OR pneumonia*) AND (outbreak*)) )

Limits: 2020-, peer-reviewed

OR

TI,AB,SU( ("novel coronavirus" OR "novel corona virus" OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus") OR ((wuhan OR hubei OR huanan) AND ("severe acute respiratory" OR pneumonia*) AND outbreak*) OR ((wuhan OR hubei OR huanan) AND (coronavir* OR betacoronavir*)) )

Limits: 2019-, peer-reviewed

CINAHL(Ebsco)

TI,AB,SU( (coronavir* OR "corona virus" OR betacoronavir* OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus") OR ((wuhan OR hubei OR huanan) AND ("severe acute respiratory" OR pneumonia*) AND (outbreak*)) ) OR (MH "Coronavirus") OR (MH "Coronavirus Infections")


ProQuest Central (Proquest) 1952-

TI,AB,SU( (coronavir* OR "corona virus" OR betacoronavir* OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus") OR ((wuhan OR hubei OR huanan) AND ("severe acute respiratory" OR pneumonia*) AND (outbreak*)) )


PubMed Central

TITLE-ABSTRACT( (coronavirus OR "corona virus" OR coronavirinae OR coronaviridae OR betacoronavirus OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus" ) OR ((wuhan OR hubei OR huanan) AND ( "severe acute respiratory" OR pneumonia ) AND (outbreak)) ) OR "COVID-19" [Supplementary Concept] OR "severe acute respiratory syndrome coronavirus 2" [Supplementary Concept]

Limits: Dec. 2019-

Medline (PubMed)

TITLE-ABSTRACT( ( coronavirus OR "corona virus" OR coronavirinae OR coronaviridae OR betacoronavirus OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus" ) OR ((wuhan OR hubei OR huanan) AND ( "severe acute respiratory" OR pneumonia ) AND (outbreak)) ) OR "COVID-19" [Supplementary Concept] OR "severe acute respiratory syndrome coronavirus 2" [Supplementary Concept]

Limits: Dec. 2019-

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Confidential: For Review OnlyLitCovid (NLM)

https://www.ncbi.nlm.nih.gov/research/coronavirus/

SciFinder (CAS)

References ( coronavir* OR "corona virus" OR betacoronavir* OR covid19 OR covid OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus" )

Limits: 2020-

OR

References ( "novel coronavirus" OR "novel corona virus" OR covid19 OR covid OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus" )

Limits: 2019-

Virtual Health Library (WHO)

Filter VHL created: https://bvsalud.org/vitrinas/post_vitrines/novo_coronavirus/ Database changed on 6/16/2020 and integrated into the larger WHO databaseLimited: 2019-

OR

TI,AB:( (coronavirus OR "corona virus" OR coronavirinae OR coronaviridae OR betacoronavirus OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus" ) OR ((wuhan OR hubei OR huanan) AND ("severe acute respiratory" OR pneumonia) AND (outbreak)) )

Limits: 2020-

OR

TI,AB( "novel coronavirus" OR "novel corona virus" OR covid19 OR "covid 19" OR nCoV OR "CoV 2" OR CoV2 OR sarscov2 OR 2019nCoV OR "novel CoV" OR "wuhan virus") OR ((wuhan OR hubei OR huanan) AND ("severe acute respiratory" OR pneumonia) AND outbreak) OR ((wuhan OR hubei OR huanan) AND (coronavirus OR betacoronavirus))

Limits: 2019-WHO Novel Coronavirus page

Download of their global research on COVID 19 database: https://www.who.int/emergencies/diseases/novel-coronavirus- 2019/global-research-on-novel-coronavirus-2019-ncov

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https://www.ncbi.nlm.nih.gov/research/coronavirus/https://bvsalud.org/vitrinas/post_vitrines/novo_coronavirus/https://www.who.int/emergencies/diseases/novel-coronavirus-2019https://www.who.int/emergencies/diseases/novel-coronavirus-2019https://www.who.int/emergencies/diseases/novel-coronavirus-2019https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncovhttps://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov


OR

Hand searchCDC Novel Coronavirus page

https://www.cdc.gov/coronavirus/2019-ncov/publications.html

OR

Hand search

EuroSurveill ance

https://www.eurosurveillance.org/content/2019- ncov?pageSize=100&page=1

China CDC MMWR

Hand search

Homeland Security Digital Library

Title or Summary: Coronavirus OR “Corona virus” OR Betacoronavirus OR Coronaviridae OR coronavirinae OR Covid OR Covid19 OR nCoV OR CoV OR CoV2 OR Wuhan

Limits: 2019-ClinicalTrials Condition, disease, other term: Coronavirus OR “Corona virus”

OR Betacoronavirus OR Coronaviridae OR coronavirinae OR Covid OR Covid19 OR nCoV OR CoV OR CoV2 OR Wuhan

Limits: 2019-bioRxiv medRxiv chemRxiv (preprints)

Condition, disease, other term: Coronavirus OR “Corona virus” OR Betacoronavirus OR Coronaviridae OR coronavirinae OR Covid OR Covid19 OR nCoV OR CoV OR CoV2 OR Wuhan

Limits: 2019-SSRN(preprints)

Condition, disease, other term: Coronavirus OR “Corona virus” OR Betacoronavirus OR Coronaviridae OR coronavirinae OR Covid OR Covid19 OR nCoV OR CoV OR CoV2 OR Wuhan

Limits: 2019-

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https://www.cdc.gov/coronavirus/2019-ncov/index.htmlhttps://www.cdc.gov/coronavirus/2019-ncov/index.htmlhttps://www.cdc.gov/coronavirus/2019-ncov/index.htmlhttps://www.cdc.gov/coronavirus/2019-ncov/publications.htmlhttps://www.eurosurveillance.org/content/2019-ncov?pageSize=100&page=1https://www.eurosurveillance.org/content/2019-ncov?pageSize=100&page=1http://weekly.chinacdc.cn/http://weekly.chinacdc.cn/https://www.biorxiv.org/https://www.medrxiv.org/https://chemrxiv.org/https://www.ssrn.com/index.cfm/en/


中文数据库检索策略及结果

Search Strategy And Results in Chinese databases

Searches last ran on June 9, 2020

Database Strategy万方医学

(med.wanfangdata.com.cn)

#1 (主题:(2019 冠状病毒 OR 新型冠状病毒 OR 新冠肺炎)*主题:(临床试验 OR 系统评价 OR Meta 分析 OR 随机对照实验 OR 对照研究))*Date:2019-#2 (主题:(2019-nCoV OR SARS-CoV-2 OR Novel coronavirus OR nCoV OR new coronavirus)*主题 :(临床试验 OR 系统评价 OR Meta 分析 OR 随机对照实验 OR 对照研究))*Date:2019-#3 #1 OR #2

CBM (("2019 冠状病毒"[常用字段:智能] OR "新型冠状病毒"[常用字段:智能] OR "新冠肺炎"[常用字段:智能] OR "2019-nCoV"[常用字段:智能] OR "SARS-CoV-2"[常用字段:智能] OR "Novel coronavirus"[常用字段:智能] OR "nCoV"[常用字段:智能] OR "Emerging Coronaviruses"[常用字段 :智能 ] OR "new coronavirus"[常用字段 :智能 ] OR "COVID-19"[常用字段 :智能 ] OR "coronavirus"[常用字段 :智能 ] AND ( "Wuhan"[常用字段 ] OR "Hubei"[常用字段 ] OR "China"[常用字段])) AND 2019-2020[日期]) AND ("循证文献"[文献类型] OR "临床试验"[文献类型] OR "随机对照试验"[文献类型] OR "综述"[文献类型] OR "Meta 分析"[文献类型])

CNKI 在期刊文献类型下：#1 主题=("2019 冠状病毒" OR "新型冠状病毒"OR "新冠肺炎") AND （主题=临床试验 OR 系统评价 OR 随机对照实验 OR Meta 分析）#2 主题=(2019-nCoV OR SARS-CoV-2 OR Novel coronavirus OR nCoV) AND (主题=临床试验 OR 系统评价 OR 随机对照实验 OR Meta 分析)2019-[日期]

维普 #1 (主题:(2019冠状病毒 OR 新型冠状病毒 OR 新冠肺炎)*主题:(临床试验 OR 系统评价

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http://www.sinomed.ac.cn/javascript:toDoRelimitSearch();http://www.sinomed.ac.cn/javascript:toDoRelimitSearch();http://www.sinomed.ac.cn/javascript:toDoRelimitSearch();http://www.sinomed.ac.cn/javascript:toDoRelimitSearch();http://www.sinomed.ac.cn/javascript:toDoRelimitSearch();http://www.sinomed.ac.cn/javascript:toDoRelimitSearch();http://www.sinomed.ac.cn/javascript:toDoRelimitSearch();


OR Meta 分析 OR 随机对照实验 OR 对照研究))*#2 主题=( SARS-CoV-2 OR Novel coronavirus OR nCoV) AND (主题=临床试验 OR 系统评价 OR 随机对照实验 OR Meta 分析)Date:2019-

中华医学期刊网（预

印本）

http://medjournals.cn/2019NCP/index.do

#1 主题=("2019 冠状病毒" OR "新型冠状病毒"OR "新冠肺炎") AND （主题=临床试验 OR 系统评价 OR 随机对照实验 OR Meta 分析）#2 主题=(2019-nCoV OR SARS-CoV-2 OR Novel coronavirus OR nCoV) AND (主题=临床试验 OR 系统评价 OR 随机对照实验 OR Meta 分析)2019-[日期]

中科院预印本

http://chinaxiv.org/home.htm

#1 主题=("2019 冠状病毒" OR "新型冠状病毒"OR "新冠肺炎") AND （主题=临床试验 OR 系统评价 OR 随机对照实验 OR Meta 分析）#2 主题=(2019-nCoV OR SARS-CoV-2 OR Novel coronavirus OR nCoV) AND (主题=临床试验 OR 系统评价 OR 随机对照实验 OR Meta 分析)2019-[日期]

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http://medjournals.cn/2019NCP/index.dohttp://medjournals.cn/2019NCP/index.dohttp://chinaxiv.org/home.htmhttp://chinaxiv.org/home.htm

Confidential: For Review OnlyLow risk of biasProbably low risk of biasProbably high risk of biasHigh risk of bias

Author (trial registration) Rand

omiza

tion

Devi

atio

ns fr

om th

e in

tend

ed

inte

rven

tion

Miss

ing

outc

ome

data

Mea

sure

men

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utco

me

Sele

ctio

n of

the

repo

rted

re

sults

MortalityBeigel (NCT04280705)

Cao_1 (ChiCTR2000029308)Cao_2 (ChiCTR-OPN-2000029580)

Chen_2 (ChiCTR2000030254)Chen_3 (ChiCTR2000029387)

Chen_4 (NCT04261517)Davoudi-Monfared (IRCT20100228003449N28)

Hung (NCT04276688)Li (NCT04252885)

Lou (ChiCTR2000029544)Tang (ChiCTR2000029868)

Wang (NCT04257656)Zhong (ChiCTR2000029851)

Mechanical ventilationCao_1 (ChiCTR2000029308)

Cao_2 (ChiCTR-OPN-2000029580)Davoudi-Monfared (IRCT20100228003449N28)

Hung (NCT04276688)Lou (ChiCTR2000029544)

Wang (NCT04257656)

Adverse events leading to discontinuationBeigel (NCT04280705)

Chen_1 (ChiCTR2000029559)Chen_4 (NCT04261517)

Davoudi-Monfared (IRCT20100228003449N28)Hung (NCT04276688)

Li (NCT04252885)Tang (ChiCTR2000029868)

Wang (NCT04257656)Zheng (ChiCTR2000029496)Zhong (ChiCTR2000029851)

Zhou

Viral clearanceCao_1 (ChiCTR2000029308)


Huang (ChiCTR2000029542)Li (NCT04252885)


Wang (NCT04257656)Zheng (ChiCTR2000029496)

Duration of hospitalizationCao_1 (ChiCTR2000029308)

Cao_2 (ChiCTR-OPN-2000029580)Chen_3 (ChiCTR2000029387)

Davoudi-Monfared (IRCT20100228003449N28)Huang (ChiCTR2000029542)

Hung (NCT04276688)Wang (NCT04257656)

ICU length of stayCao_1 (ChiCTR2000029308)

Davoudi-Monfared (IRCT20100228003449N28)

Duration of ventilationCao_1 (ChiCTR2000029308)

Cao_2 (ChiCTR-OPN-2000029580)Davoudi-Monfared (IRCT20100228003449N28)

Wang (NCT04257656)

Time to symptom resolution/clinical improvementBeigel (NCT04280705)

Cao_1 (ChiCTR2000029308)Cao_2 (ChiCTR-OPN-2000029580)

Chen_1 (ChiCTR2000029559)Chen_2 (ChiCTR2000030254)Chen_3 (ChiCTR2000029387)

Chen_4 (NCT04261517)Davoudi-Monfared (IRCT20100228003449N28)

Huang (ChiCTR2000029542)Hung (NCT04276688)


Wang (NCT04257656)

Time to viral clearanceCao_2 (ChiCTR-OPN-2000029580)


Huang (ChiCTR2000029542)Hung (NCT04276688)

Li (NCT04252885)Lou (ChiCTR2000029544)

Tang (ChiCTR2000029868)Zheng (ChiCTR2000029496)

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Documents

BMJ...Department of Medicine, Centre de recherche du CHU de Sherbrooke, Sherbrooke, Quebec, Canada. 5. Department of Preventive Medicine, College of Medicine, Chosun University, Gwangju,