A systematic review and meta-analysis on chloroquine and hydroxychloroquine as monotherapy or combined with azithromycin in COVID-19 treatment

  1. Ramy Mohamed Ghazy
  2. Abdallah Almaghraby
  3. Ramy Shaaban
  4. Ahmed Kamal
  5. Hatem Beshir
  6. Amr Moursi
  7. Ahmed Ramadan
  8. Sarah Hamed N. Taha

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Abstract

Many recent studies have investigated the role of either Chloroquine (CQ) or Hydroxychloroquine (HCQ) alone or in combination with azithromycin (AZM) in the management of the emerging coronavirus. This systematic review and meta-analysis of either published or preprint observational studies or randomized control trials (RCT) aimed to assess mortality rate, duration of hospital stay, need for mechanical ventilation (MV), virologic cure rate (VQR), time to a negative viral polymerase chain reaction (PCR), radiological progression, experiencing drug side effects, and clinical worsening. A search of the online database through June 2020 was performed and examined the reference lists of pertinent articles for in-vivo studies only. Pooled relative risks (RRs), standard mean differences of 95% confidence intervals (CIs) were calculated with the random-effects model. Mortality was not different between the standard care (SC) and HCQ groups (RR = 0.99, 95% CI 0.61–1.59, I 2  = 82%), meta-regression analysis proved that mortality was significantly different across the studies from different countries. However, mortality among the HCQ + AZM was significantly higher than among the SC (RR = 1.8, 95% CI 1.19–2.27, I 2  = 70%). The duration of hospital stay in days was shorter in the SC in comparison with the HCQ group (standard mean difference = 0.57, 95% CI 0.20–0.94, I 2  = 92%), or the HCQ + AZM (standard mean difference = 0.77, 95% CI 0.46–1.08, I 2  = 81). Overall VQR, and that at days 4, 10, and 14 among patients exposed to HCQ did not differ significantly from the SC [(RR = 0.92, 95% CI 0.69–1.23, I 2  = 67%), (RR = 1.11, 95% CI 0.26–4.69, I 2  = 85%), (RR = 1.21, 95% CI 0.70–2.01, I 2  = 95%), and (RR = 0.98, 95% CI 0.76–1.27, I 2  = 85% )] respectively. Exposure to HCQ + AZM did not improve the VQR as well (RR = 3.23, 95% CI 0.70–14.97, I 2  = 58%). The need for MV was not significantly different between the SC and HCQ (RR = 1.5, 95% CI 0.78–2.89, I 2  = 81%), or HCQ + AZM (RR = 1.27, 95% CI 0.7–2.13, I 2  = 88%). Side effects were more reported in the HCQ group than in the SC (RR = 3.14, 95% CI 1.58–6.24, I 2  = 0). Radiological improvement and clinical worsening were not statistically different between HCQ and SC [(RR = 1.11, 95% CI 0.74–1.65, I 2  = 45%) and (RR = 1.28, 95% CI 0.33–4.99), I 2  = 54%] respectively. Despite the scarcity of published data of good quality, the effectiveness and safety of either HCQ alone or in combination with AZM in treating COVID-19 cannot be assured. Future high-quality RCTs need to be carried out.

PROSPERO registration : CRD42020192084.

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  1. Version published to 10.1038/s41598-020-77748-x
  2. ScreenIT

    SciScore for 10.1101/2020.07.25.20162073: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Inclusion and Exclusion Criteria: Outcomes Conceptualization: Data Extraction: A computer literature searches of (PubMed, Google Scholar, Cochrane, Scopus, Web of Science, Segle, VLH, COVID-Inato, COVID-Trial-Clinical Trial.gov) was conducted till June 5th, 2020 using the following keywords (Chloroquine OR Hydroxychloroquine) AND (2019 novel Coronavirus disease OR COVID-19 OR SARS-CoV-2 OR novel Coronavirus infection OR 2019-ncov infection OR Coronavirus disease 2019 OR Coronavirus disease-19 OR 2019-ncov disease OR COV OR Coronavirus).
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    Cochrane
    suggested: (Cochrane Library, RRID:SCR_013000)
    References remaining after this step were exported to a Microsoft Excel file with essential information for screening.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitation: Our analysis must be interpreted in the context of the limitations of the available data; despite the huge number of published articles during the COVID-19 pandemic, many of these studies lack a good quality and may contain inconsistent results. In fact, there is an urgent need for high-quality randomized control trials that address the issue of HCQ treatment. Consequently, we depended on our analysis of the few published or even cited preprints. Moreover, we included many observational studies due to the scarcity of randomized control trials. It is well established that observational studies cannot discover causality. This fact also contributed to the highly found heterogeneity of analysis especially for the study of Haung (2020). (3) After leaving one sensitivity analysis the heterogeneity drops to acceptable value in many outcomes. Another important source of bias in patient selection bias; as some studies did not classify patients according to their disease’s severity. This source of bias may significantly affect the course of illness. Differences in HCQ and AZM in dose, duration of treatment, and route of administration may also affect the consistency of our results.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. ScreenIT

    SciScore for 10.1101/2020.07.25.20162073: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variable( HCQ: 60% males SC: 46.7 ± 3.6 SC:80% males 11 Mean age (SD) ( Intervention 44.1 (16.1) Standard care 45.2 (14.7) 51.55± 12.54 Treatment Intervention Duration (days) Primary Outcomes 23 Mar –

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    References remaining after this step were exported to a Microsoft Excel file with essential information for screening.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    The risk of bias in the individual studies included for meta-analysis was assessed using the Cochrane risk assessment tool in cases of Randomized Control Trials (RCT) (19), study quality assessment tools for observational study (20), and Robins-1 for Non-Randomized control trial (21).
    Cochrane risk assessment tool
    suggested: None

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

    Limitation Our analysis must be interpreted in the context of the limitations of the available data; despite the huge number of published articles during the COVID-19 pandemic, many of these studies lack a good quality and may contain inconsistent results. In fact, there is an urgent need for high-quality randomized control trials that address the issue of HCQ treatment. Consequently, we depended on our analysis of the few published or even cited preprints. Moreover, we included many observational studies due to the scarcity of randomized control trials. It is well established that observational studies cannot discover causality. This fact also contributed to the highly found heterogeneity of analysis especially for the study of Haung (2020). (3) After leaving one sensitivity analysis the heterogeneity drops to acceptable value in many outcomes. Another important source of bias in patient selection bias; as some studies did not classify patients according to their disease’s severity. This source of bias may significantly affect the course of illness. Differences in HCQ and AZM in dose, duration of treatment, and route of administration may also affect the consistency of our results. Conclusion HCQ prolonged the duration of hospital stay and did not increase the overall virological cure or more specifically on days 4, 10, or 14. In addition, it did not affect duration till conversion to negative PCR, need for MV, radiological progression, clinical worsening of the disease, or death. Furthermore, treatment with AZM and HCQ did not affect the virological cure, the need for MV. However, it increased the duration of hospital stay and mortality. Future randomized clinical trials are needed to confirm these conclusions. Conflict of Interest No conflict of interest

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. ScreenIT

    SciScore for 10.1101/2020.07.25.20162073: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.RandomizationFuture randomized control trials need to be carried out to verify this conclusion.Blindingnot detected.Power AnalysisThe studies’ sample size ranged from (30 to 1438) participants.Sex as a biological variable120 64.3 ± 13.4 76.7%; HCQ/CQ/A ZM/ LOPI 15 raiech, 20(32) acías. 4 SC: 71% males HCQ 400 bid on day1 then 200 bid on days 2 to 5 AZM either 500mg daily or 500 mg on day1 followed by 250mg daily on days 2-5.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data Extraction A computer literature searches of (PubMed, Google Scholar, Cochrane, Scopus, Web of Science, Segle, VLH, COVID-Inato, COVID-Trial- Clinical Trial.gov) was conducted till June 5th, 2020 using the following keywords (Chloroquine OR Hydroxychloroquine) AND (2019 novel Coronavirus disease OR COVID-19 OR SARS-CoV-2 OR novel Coronavirus infection OR 2019-ncov infection OR Coronavirus disease 2019 OR Coronavirus disease-19 OR 2019- ncov disease OR COV OR Coronavirus).
    PubMed
    suggested: (PubMed, SCR_004846)
          <div style="margin-bottom:8px">
        <div><b>Google Scholar</b></div>
        <div>suggested: (Google Scholar, <a href="https://scicrunch.org/resources/Any/search?q=SCR_008878">SCR_008878</a>)</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>Cochrane</b></div>
        <div>suggested: (Cochrane Library, <a href="https://scicrunch.org/resources/Any/search?q=SCR_013000">SCR_013000</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">References remaining after this step were exported to a Microsoft Excel file with essential information for screening.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Microsoft Excel</b></div>
        <div>suggested: (Microsoft Excel, <a href="https://scicrunch.org/resources/Any/search?q=SCR_016137">SCR_016137</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The risk of bias in the individual studies included for meta-analysis was assessed using the Cochrane risk assessment tool in cases of Randomized Control Trials (RCT) (19), study quality assessment tools for observational study (20), and Robins-1 for Non-Randomized control trial (21).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Cochrane risk assessment tool</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr></table>

    Data from additional tools added to each annotation on a weekly basis.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  5. Version published to 10.1101/2020.07.25.20162073v1 on medRxiv