Benefits and Risks of Chloroquine and Hydroxychloroquine in The Treatment of Viral Diseases: A Meta-Analysis of Placebo Randomized Controlled Trials

  1. Jing Wang
  2. Li Yu
  3. Kefeng Li

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Abstract

Background and Objective

Recently, in the scramble to find drugs to treat COVID-19, chloroquine (CQ) and its derivative hydroxychloroquine (HCQ) have rapidly gained the public’s attention. In this study, we conducted a meta-analysis of randomized clinical trials (RCTs) to evaluate the efficacy and safety of CQ and HCQ in the treatment of viral diseases.

Methods

We searched PubMed, EMBASE, Cochrane Central, Web of Science, Clinical Trials Registries, CNKI, Wanfang Data, CQVIP, and Preprint Servers through April 4, 2020, for randomized controlled trials (RCTs) that examined the efficacy and safety of CQ and HCQ against viral infection. We analyzed pooled data on the overall efficacy, the relative risks over the placebo, and the prevalence of adverse events. Trial sequential analysis (TSA) was also performed to evaluate the random errors in the meta-analysis. Potential moderators of drug-placebo efficacy differences were analyzed by meta-regression.

Results

The analysis included 11 RCTs with 2613 adult patients. Both the plasma viral load (standard mean difference: 0.29, 95% CI: −1.19 - 1.76, P = 0.70) and the improvement of clinical symptoms (odds ratio: 2.36, 95% CI: 0.81 - 6.92, P = 0.11) were not different between the intervention and placebo arm. There was significant heterogeneity for the efficacy assessment, which was primarily explained by the mean patients’ age and the sample size. Compared to the placebo, CQ and HCQ had increased risk of mild adverse events (risk ratio: 1.51, 95% CI: 1.35 - 1.70, P < 0.05, TSA adjusted 95% CI: 1.31 - 2.19), which were statistically significant in nervous, integumentary, and gastrointestinal systems. The most common adverse events were observed in the nervous system, with the pooled prevalence of 31.4 % (95% CI: 10.5% - 56.7%).

Conclusions

Insufficient data were available to support the antiviral efficacy of CQ and HCQ due to the high heterogeneity caused by patients’ age. Mild side effects are expected for the current antiviral dose regimens of CQ and HCQ. Treatment outcomes may be enhanced by better-selected patients based on age and well-controlled adverse events.

This meta-analysis was registered on OSF (ID: https://osf.io/386aw )

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  1. ScreenIT

    SciScore for 10.1101/2020.04.13.20064295: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationInclusion and exclusion criteria: The PICOS inclusion criteria for selecting the studies for this meta-analysis were as follows: (1) Participants: patients with the viral infection and treated with chloroquine (CQ) or hydroxychloroquine (HCQ); (2) Interventions: CO or HCQ versus placebo; (3) Outcomes: primary outcomes included plasma viral load, the improvement of clinical symptoms, and adverse events associated with CQ (or HCQ) treatment; (4) Type of studies: In this meta-analysis, only randomized controlled trials (RCTs) were included.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy: We performed a comprehensive literature search of articles through the following databases without date limitation: PubMed, EMBASE, The Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, and CQVIP.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    Cochrane Library
    suggested: (Cochrane Library, RRID:SCR_013000)
    We also searched clinical trial registries, including ClinicalTrials.gov, Chinese Clinical Trial Registry, and EU Clinical Trials Register.
    ClinicalTrials
    suggested: (ClinicalTrials.gov, RRID:SCR_002309)
    Data synthesis and meta-analysis: The conventional meta-analysis was conducted using MedCalc 19.2.0 (MedCalc Software Ltd, Belgium).
    MedCalc
    suggested: (MedCalc, RRID:SCR_015044)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our analysis has some limitations. First, we did not conduct a subgroup analysis for the efficacy of CQ and HCQ on different types of viruses due to the small sample size in each study and the high heterogeneity among the included RCTs. Second, we assumed that the non-reporting of adverse event data was the result of no adverse event since the report of adverse events in RCTs had been required in the Consolidated Standards of Reporting Trials (CONSORT) extension for harms in 2004(33). If the adverse events were observed, but not reported, then there is the possibility that we may have overestimated the drugs’ safety. Third, adverse events in clinical trials are usually reported using the Common Terminology of Clinical Adverse Events (CTCAE). The process is highly subjective and relies on investigators’ recognition and identification of syndromes of interest.

    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.

  2. Version published to 10.1101/2020.04.13.20064295v1 on medRxiv