Original Article

Efficacy of Hydroxychloroquine for Outpatient COVID-19 Prophylaxis and Treatment: A Systematic Review and Meta-Analysis

Sarah Yang, BHSc1, Ali Eshaghpour, MD2, Allen Li, BHSc*1, Adrian Salopek1, Sofia Ivanisevic, BHSc3, Lawrence Mbuagbaw, MD, MPH, PhD4, Mark Crowther, MD, MSc2, John Eikelboom, MBBS, MSc2

1Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada;

2Department of Medicine, McMaster University, Hamilton, Ontario, Canada;

3Temerty School of Medicine, University of Toronto, Toronto, Ontario, Canada;

4Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada

Abstract

Early in the coronavirus disease 2019 (COVID-19) pandemic, hydroxychloroquine was suggested as its possible treatment. In order to determine its utility for outpatient prophylaxis and treatment, we performed a review and meta-analysis of randomized controlled trials (RCTs) in the following three groups of outpatients: (a) at high risk of COVID-19, (b) with suspected risk of COVID-19, and (c) with confirmed COVID-19. A comprehensive search of MEDLINE, EMBASE, and medRxiv was performed on July 1, 2021. The initial search yielded 859 studies, 11 of which remained for data extraction. Categories of data extracted included general study characteristics, baseline patient characteristics, intervention details, COVID-19 incidence, number of hospitalizations, and mortality. Cochrane’s risk of bias tool was used to assess bias. All studies were superiority RCTs, utilized varying dosages of hydroxychloroquine, and targeted pre-exposure, post-exposure, and/or confirmed COVID-19 populations. Hydroxychloroquine did not significantly reduce COVID-19 infection, hospitalization, or mortality, overall or in separate outpatient groups.

Résumé

Au début de la pandémie de la maladie à coronavirus 2019 (COVID-19), l’hydroxychloroquine a été suggérée comme traitement possible contre cette maladie. Pour déterminer son utilité en prophylaxie ambulatoire et comme traitement ambulatoire, nous avons effectué une revue et une méta-analyse d’essais cliniques randomisés chez trois groupes de patients ambulatoires : a) cas présentant un risque élevé de contracter la COVID-19; b) cas soupçonnés de COVID-19; c) cas confirmés de COVID-19. Une recherche exhaustive des bases de données MEDLINE, EMBASE et MedRxiv a été effectuée le 1er juillet 2021. La recherche initiale a donné 859 études, dont 11 pour lesquelles les données ne sont pas encore extraites. Les catégories de données extraites sont les caractéristiques générales de l’étude, les caractéristiques initiales des patients, les détails de l’intervention, l’incidence de la COVID-19, le nombre d’hospitalisations et le nombre de décès. L’outil Risque de biais du centre Cochrane a été utilisé pour évaluer les biais. Toutes les études sont des essais cliniques randomisés qui évaluent la supériorité, utilisent différentes posologies d’hydroxychloroquine et ciblent des populations pré-exposées à la COVID-19, post-exposées à la COVID-19 ou atteintes de la COVID-19 (cas confirmés). L’hydroxychloroquine ne diminue pas considérablement l’infection par la COVID-19, ni les hospitalisations et les décès, que ce soit dans l’ensemble des groupes de patients ambulatoires ou dans chacun des groupes.

Key words: COVID-19, hydroxychloroquine, randomized controlled trials (RCT)

Corresponding Author: Allen Li A: ali167@uottawa.ca

Submitted: 1 October 2021; Accepted: 1 January 2022; Published: 15 August 2022

Doi: http://dx.doi.org/10.22374/cjgim.v17i3.581

All articles published in DPG Open Access journals
This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)(https://creativecommons.org/licenses/by-nc/4.0/).

Introduction

Since its initial outbreak in Wuhan, China, SARS-CoV-2 has led to the coronavirus disease 2019 (COVID-19) global pandemic. Transmission of the virus is efficient; modelling suggests that 50% or more of secondary transmission is attributed to asymptomatic, pre-symptomatic, or minimally symptomatic individuals.1 While many patients with COVID-19 remain asymptomatic or become only minimally symptomatic, some develop progressive disease with acute respiratory distress syndrome (ARDS) and other organ dysfunction, resulting in significant morbidity and mortality. Many studies have examined interventions for limiting viral transmission, preventing hospitalization and ARDS, and reducing mortality.2,3

Early in the pandemic, hydroxychloroquine (HCQ) was encouraged for use as a prophylactic and therapeutic agent against SARS-CoV-2 because of its in vitro activity against the virus.4 This led to numerous investigations of its efficacy in preventing infection, hospitalization, and mortality. Owing to different phases of the pandemic that had different aims of patient care such as prophylaxis or treatment of the hospitalized COVID-19 patients along with varying quality of evidence, the literature that analyzed HCQ has been heterogenous in terms of endpoints, outcomes, and study design, leading to mixed findings.5 Given these heterogeneous findings in the literature, we performed a meta-analysis of RCTs that evaluated the efficacy of HCQ in the following three groups of outpatients: (a) at high risk of COVID-19, (b) with suspected risk of COVID-19, and (c) confirmed to have COVID-19. Further, given the increasing number of systematic reviews and meta-analyses published on this topic and heterogeneity of the studies, a plus point of the present study was that we changed composite outcomes to improve consistency in combining studies.

Methods

This systematic review is reported following standards outlined in the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) statement.6 The research -protocol was formulated prospectively and is available online at osf.io/3c82g/.

Patient and public involvement

Patients and the public were not involved in this study.

Search strategy

We conducted a comprehensive search of MEDLINE, EMBASE, and medRxiv on July 1, 2021 with the aid of a medical librarian at McMaster University, Hamilton, ON, Canada. We searched for articles in MEDLINE and EMBASE using the following terms: “COVID-19” or “SARS-CoV-2” or “2019-nCoV” or “2019 novel coronavirus” or “Wuhan coronavirus” or “new coronavirus,” or “coronavirus” and “hydroxychloroquine,” limiting to randomized controlled trials (RCTs). Preprint site medRxiv was searched using these terms: “hydroxychloroquine AND covid-19 OR 2019-nCoV OR SARS-CoV-2 OR 2019 novel coronavirus OR Coronavirus, AND randomized." The period of the search spanned from inception of the database to July 1, 2021, which constitutes 1946 in case of MEDLINE, 1974 for EMBASE, and June 2019 in case of medRxiv. The full search strings are provided online in supplemental Figure S4 given in the supplementary file. While we recognize that the search string for COVID can be more comprehensive, given the topic has evolved quickly, our addition of terms “hydroxychloroquine AND randomized” likely meant most studies that met our inclusion criteria were captured, and anything missed would likely not have yielded different results.

Study selection

Titles and abstracts were uploaded to Covidence (Veritas Health Innovation Ltd, Melbourne, Australia), and study screening was performed in duplicate across two stages. First, two review authors (S Yang and A Salopek) independently assessed titles and abstracts. Next, included articles underwent full-text analysis by the same two authors to assess eligibility for data extraction. Any discrepancies in eligibility during a given stage were resolved through joint discussions with a third reviewer (S Ivanisevic). Inclusion criteria included the following: RCT, examined HCQ as intervention for outpatient COVID-19 patients, outcome included laboratory--confirmed COVID-19 infection, hospitalization, and/or death, and comparator patients treated with placebo or no intervention. Exclusion criteria included the following: full text could not be found, or not published in English language.

Data extraction

Data were collected independently by two authors (S Yang and S Ivanisevic) and discrepancies were addressed through discussion until a consensus was reached. Data extracted included country of research, journal, date of publication, RCT design (equivalence, superior, or non-inferior), number of patients, gender breakdown of patients, patient status at enrolment (symptomatic/asymptomatic), infection status at baseline (duration of being symptomatic or asymptomatic before assignment to intervention), age, intervention details (including dosage), intervention timing (duration of treatment), control used, mortality, number of hospitalizations, and COVID-19 incidence if applicable.

Methods of data analysis and synthesis

Descriptive data were recorded using Microsoft Excel (Microsoft, Redmond, WA) and summarized in the given tables. The random-effects meta-analysis was conducted using Review Manager V.5.3 (The Cochrane Collaboration, Copenhagen, Denmark). For each outcome (hospitalization, mortality, or infection), we computed risk ratios (RR) and 95% confidence interval (CI) for each study using the number of patients receiving HCQ versus control. A two-sided P < 0.05 was regarded as significant. We assessed heterogeneity using I2 statistics (test of heterogeneity), with I2 > 50% indicating heterogeneity. Study quality was examined independently by two reviewers using the Cochrane risk of bias (ROB) tool for RCTs.7 The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) tool was used to assess overall quality of studies.8 Subgroup analyses were conducted with pre-exposure, post-exposure, and COVID-19-confirmed groups for each outcome, and the number of events was converted to log RR for combining purpose. Sensitivity analyses were conducted on two approaches of including cluster RCT data; first, by using inflated standard errors, and second, by using the effective sample size estimation according to the Cochrane handbook.9 In the first method, inflated variances for each study are calculated by multiplying the standard error of the log RR by the root of a quantity called the “design effect,” given as 1 + (M - 1) ICC, where M is the cluster size and ICC is the intraclass correlation coefficient, and pooling using the generic inverse variance approach. In the second method, we reduce the size of each trial to its “effective sample size.” The effective sample size of a single intervention group in a cluster RCT is its original sample size and number of events divided by the “design effect.” We reported our results using the first approach; however, both meta-analyses can be found in supplemental Figure S3. Publication bias was assessed by visually inspecting funnel plots with 95% confidence limits, which can be found in supplemental Figure S2.

Results

Search results

The search resulted in a total of 859 studies. After removing 22 duplicates, 837 studies were included for screening. In all, 826 studies were excluded during title and abstract screening, leaving 11 studies for full-text screening.5,1019 The 11 studies included for data extraction are described in Table 1. The PRISMA flow chart of study selection is given in supplemental Figure S1.

Table 1. Included studies and characteristics

Study Country Number of -participants (in each group)a Gender breakdown of participants by number of females (% of females)a Disease severity at baseline Intervention timing Type of control
(a) Pre-Exposure Prophylaxis of COVID-19 Outpatients Studies
Abella et al.10 USA 125 (P: 61, C: 64) 86 (69%) No known infection Pre-symptomatic, pre-diagnosis Placebo
Barnabas et al.11 USA 823 (P: 422, HCQ: 406) P: 249 (59%), I: 248 (61%) No known infection Pre-symptomatic, pre-diagnosis Placebo
Rajasingham et al.12 USA 1483 (P: 494; once: 494; twice: 495) P: 241 (48.8%), 1x HCQ: 261 (52.8%), 2x HCQ: 258 (52.1%) No exposure Pre-symptomatic, pre-diagnosis Placebo
Rojas-Serrano et al.13 Mexico 127 (P: 65, HCQ: 62) P: 42 (64.6%), I: 29 (46.6%) No known infection Pre-symptomatic, pre-diagnosis Placebo
Syed et al.14 Pakistan 200 (P: 46, HCQ group 1: 48, HCQ group 2: 51, HCQ group 3: 55) P: 23 (50%) Group 1: 24 (50%), Group 2: 26 (51%), Group 3: 18 (32.7%) No known infection Pre-symptomatic, pre-diagnosis Placebo
(b) Post-Exposure Prophylaxis of COVID-19 Outpatients Studies
Mitja et al.15 Spain 2314 (C: 1198, HCQ: 1116) C: 875 (73%), I: 812 (72.8%) Asymptomatic for 2 weeks before enrolment Pre-symptomatic, pre-diagnosis Nothing
Boulware et al.16 USA 821 (P: 407, HCQ: 414) P: 206 (50.6%), I: 218 (52.7%) Asymptomatic 4 days after exposure Pre-symptomatic, pre-diagnosis Placebo
(c) Post-Diagnosis Treatment of COVID-19 Outpatients Studies
Mitja et al.17 Spain 293 (C: 157, HCQ: 136) C: 104 (65.6%), I: 98 (72.1%) 5 days or less of symptoms Post-symptom onset, post-diagnosis Nothing
Amaravadi et al.18 USA 34 (P: 17, HCQ: 17) P: 9 (53%), I: 12 (71%) ≤4 days since first COVID-19 symptom and testing Post-symptom onset, post-diagnosis Placebo
Schwartz et al.19 Canada 148 (P: 37, HCQ: 111) P: 20 (54.1%), I: 46 (41.4%) Symptomatic within previous 12 days Post-symptom onset, post-diagnosis Placebo
Skipper et al.5 USA 491 (P: 247, HCQ: 244) P: 135 (54.5%), I: 142 (58%) 4 or fewer days of symptoms Post-symptom onset, post-diagnosis Placebo

Table created by the authors.

aP = placebo, C = control, I = intervention, HCQ = hydroxychloroquine.

General characteristics of studies

The general characteristics of the included studies are summarized in Table 1. A more detailed chart with key characteristics of participants, follow-up periods, comorbidities, HCQ dosage and number of infections, hospitalizations, or mortality can be found in supplemental Tables S1S3. All studies were superiority RCTs, and one RCT was a cluster trial (Mitja et al.).15 Follow-up periods ranged from 14 days to 12 weeks. Most studies included healthcare workers at high risk of exposure to COVID-19. Most study participants were Caucasian. Studies followed varying regimens of HCQ dosage, between 200 mg and 800 mg orally per day or week, and were placebo-controlled. None of the studies included hospitalized patients; 7/11 included only asymptomatic participants, and 4/11 included only symptomatic participants. The ROB assessment can be found in supplemental Table S4. Overall, studies were found to have a low to moderate ROB, with most concern noted for blinding to treatment allocation and incomplete outcome data. GRADE ratings depicted high-quality evidence for infection and hospitalization outcomes, but low-quality evidence for mortality. Across all outcomes, there was the greatest concern for imprecision because of wide confidence intervals. The evidence profiles are given in supplemental Table S5. As only RCTs were included in this review, all are level 1, evidence-based studies on the Oxford Centre for Evidence-based Medicine.20

Meta-analysis

Infection in pre-exposure and post-exposure groups

There was no significant difference in the rate of infection between HCQ and controls in pre-exposure group (RR = 1.19[95% CI: 0.81, 1.76; P = 0.37]) or post-exposure groups (RR = 0.84 [95% CI: 0.60, 1.18; p = 0.31]). There was no -significant difference in the rates of infection (RR = 1.05 [95% CI: 0.78, 1.40; p =0.77]) in all groups combined as seen in Figure 1.

Figure 1. Meta-analysis of infection in pre-exposure and post-exposure groups.

Hospitalization in pre-exposure, post-exposure, and COVID-19--confirmed groups

There was no significant difference in the rate of hospitalization between HCQ and controls in pre-exposure (RR = 0.64 [95% CI: 0.28, 1.48; P = 0.30]), post-exposure (RR = 0.98 [95% CI: 0.12, 7.82; P = 0.99]), or confirmed COVID-19 groups (RR = 0.71 [95% CI: 0.37, 1.37; P = 0.31]). There was no significant difference in the rate of hospitalization (RR = 0.70 [95% CI: 0.42, 1.15; P = 0.16]) in all groups combined as shown in Figure 2.

Figure 2. Meta-analysis of hospitalization in pre-exposure, post-exposure, and COVID-19-confirmed groups.

Mortality in pre-exposure, post-exposure and COVID-confirmed groups

There was no significant difference in the rate of mortality between HCQ and controls in pre-exposure (RR = nonestimable), post-exposure (RR = 0.67 [95% CI: 0.01, 49.99; P = 0.86], or confirmed COVID-19 groups (RR = 1.01 [95% CI: 0.06, 16.09; P = 0.99]). It is important to note that both post-exposure and COVID-19-confirmed groups contained studies with nonestimable data because of no mortality, thus there is only one study driving the calculated RR. Further, as both pre-exposure studies resulted in no mortality, RR was nonestimable. There was no significant difference in the rate of mortality (RR = 0.90 [95% CI: 0.09, 9.21; P = 0.93]) in all groups combined as shown in Figure 3.

Figure 3. Differences in the rate of mortality in all groups.

Combined analysis

In order to recreate the methods of meta-analysis by Ladapo et al.,21 we used “mortality” or “hospitalization, or these two terms together as the outcome of interest, or using the newly occurring COVID-19 infection if there were less than one unexposed, deceased, or hospitalized subject. There was no significant difference in the rates of infection, hospitalization, or mortality (RR = 0.86 [95% CI: 0.66, 1.12; P = 0.26]) as shown in Figure 4.

Figure 4. Differences in the rates of infection, hospitalization, or mortality.

Sensitivity analysis

Our sensitivity analysis did not demonstrate any major difference between the “effective sample size” approach and the “inflated standard errors” approach.

Publication bias

Visual inspection of the funnel plots (shown in supplemental Figure S2) demonstrated symmetry in the combined analysis. The infection and hospitalization plots depicted slight asymmetry, suggesting potential overestimation of the intervention effect. However, it is important to mention that because there were less than 10 studies in the infection, hospitalization, and mortality meta-analyses, the power of the inspections was low.

Discussion

In this systematic review and meta-analysis, we analyzed 11 RCTs that examined HCQ in the pre-exposure, post--exposure, and confirmed COVID-19 groups. There was no statistically significant difference in infection rate, hospitalization, or mortality between HCQ and comparator in the pre-exposure and post-exposure groups. When pre--exposure, post-exposure, and confirmed COVID-19 groups were combined, there was no significant difference in any outcome. There was no significant difference between HCQ and comparator for the composite outcome of infection, hospitalization, and mortality in this population. These observations support the existing treatment guidelines that recommend against the use of HCQ for COVID-19 prophylaxis and treatment.22

A strength of this study is that we analyzed each outcome (infection, hospitalization, and mortality) and group (pre-exposure, post-exposure, and known infection) separately. While this reduces the overall sample size for each analysis, we believe each group and outcome to be sufficiently different such that a separate analysis is warranted. This is especially true in an era of increasing vaccination rates where primary goal is to reduce mortality and hospitalization to aid overwhelmed hospital systems. Our study did not reveal any statistically significant benefit for any of the singular outcomes or composite outcomes.

Another strength of this study is that we exclusively examined RCTs. While other study designs would help provide more power in the analysis, RCTs are the gold standard designs especially when trying to prove causality.23 Early in the pandemic, observational studies dominated the literature, given the desire for quick evidence, which initially sparked interest in HCQ as an intervention. However, cohort studies are subject to significant biases, many of which are avoided or minimized in RCTs. Over time, increasing numbers of RCTs have been published, allowing for more reliable inferences drawn exclusively from RCTs with their inherent reduction in bias. An example of this is the recent cluster randomized trial by Mitja and colleagues, which found no benefit of HCQ in prevention of symptomatic COVID-19 disease or infection.15

The present study has limitations. There was some degree of heterogeneity among the studies. The small number of studies and outcomes for many of our comparisons resulted in wide confidence intervals about individual estimates, which impede the ability to rule out HCQ interventions as having significant clinical benefit, not harm. This review is further limited by the moderate risk of bias of the included studies. We did not analyze for adverse effects within the studies. However, these effects have been well described in the literature, with a recent meta-analysis analyzing a similar population demonstrating a statistically significant difference in gastrointestinal adverse effects between HCQ and placebo, with uncertain effects in other events such as arrhythmia and visual abnormalities.24

Finally, therapeutics for COVID-19 are evolving rapidly, and as such our results may have reduced applicability due to advances in co-interventions (such as use of monoclonal antibodies in a pre-hospital setting) and the different effects of interventions in partially or fully immunized individuals. In the current era of COVID-19, prevention with the use of vaccination has been depicted to be the most effective strategy in terms of infection, hospitalization, and mortality. Apart from this, there have been over 2000 studies on different therapeutics for COVID-19, with certain therapies, such as remdesivir, tocilizumab, and dexamethasone, depicting benefit. Notably, benefits of these therapeutics are typically limited to the critically ill patients requiring hospitalization and oxygen supplementation while also being very expensive.25 This contrasts with HCQ, which is significantly cheaper, administered orally, and has a relatively benign side effect profile.26 Given these favorable characteristics, a high-quality review of HCQ was necessary.

Conclusion

Our meta-analysis of RCTs suggests that HCQ does not have a large beneficial effect when administered in the pre--exposure, post-exposure, or the confirmed COVID-19 setting when measured in terms of prevention of infection, hospitalization, or mortality.

Declaration of Competing Interests

Allen Li reports grants and funding from the University of Ottawa and the American Society of Hematology

Mark Crowther reports grants and other benefits from Bayer, personal fees from Pfizer, other benefits from Alnylam, and personal fees from CSL Behring, Servier Canada, DiagnosticaStago, and Asahi Kasei.

John Eikelboom reports consulting fees and/or honoraria from the following: Astra-Zeneca, Bayer Boehringer-Ingelheim, Bristol-Myer-Squibb, Daiichi-Sankyo, Eli-Lilly, Glaxo-Smith-Kline, Pfizer, Janssen, Sanofi-Aventis, and Servier; and grants and/or in-kind support from: Astra-Zeneca, Bayer, Boehringer-Ingelheim, Bristol-Myer-Squibb, Glaxo-Smith-Kline, Pfizer, Janssen, and Sanofi-Aventis.

Funding Statement

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Author Contributions

Sarah Yang designed the search strategy, performed statistical analyses, interpreted the results, and wrote and revised the manuscript. Ali Eshaghpour and Allen Li designed the study and search strategy, interpreted the results, and wrote and revised the manuscript. Sofia Ivanisevic and Adrian Salopek selected studies, extracted data, and revised the manuscript. Lawrence Mbuagbaw provided statistical assistance and revised the manuscript. John Eikelboom and Mark Crowther designed the study and the search strategy, interpreted the results, and revised the manuscript.

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Supplemental

Table S1. Pre-exposure prophylaxis of COVID-19 group studies and their characteristics

Study Journal Location Date of Publication Agea(years) Number of Participants (in each group)a Gender breakdown of participants (by n [%] female)a Key characteristics noted Key comorbiditiesa
Abella et al.10 Jama Internal Medicine USA September 30, 2020 Median: 33 125 (P: 61 C: 64) 86 (69%) All healthcare workers, majority White/Caucasian, without pre-existing medical conditions N/A
Barnabas et al.11 Annals of Internal Medicine USA December 8, 2020 Median, P: 38, I: 40 823 (P: 422, HCQ: 406) P: 249 (59%), I: 248 (61%) Groups of households, received HCQ dose within 5 days of exposure, majority White/Caucasian Metabolic disease: P: 16%, I: 18%
Rajasingham et al.12 Clinical Infectious Disease USA and Manitoba, Canada October 17, 2020 Mean, P: 40; once: 42; twice: 41 1483 (P: 493; once: 490; twice: 493) P: 241 (48.8%), 1x HCQ: 261 (52.8%), 2x HCQ: 258 (52.1%) Healthcare workers with ongoing exposure to COVID-19, predominantly White/Caucasian None
Rojas-Serrano et al.13 PLoS One Mexico May 14, 2021 Median, P: 31.9, I: 31 127 (P: 65, HCQ: 62) P: 42 (64.6%), I: 29 (46.6%) Majority healthcare workers Smoking (P: 35.4%, I: 32.3%), obesity (P: 23.1%, I: 11.3%)
Syed et al.14 Cureus) Pakistan May 17, 2021 Mean, P: 39.9, Group 1: 30.4, Group 2: 28.2, Group 3: 32 200 (P: 46, HCQ group 1: 48, HCQ group 2: 51, HCQ group 3: 55) P: 23 (50%) Group 1: 24 (50%), Group 2: 26 (51%), Group 3: 18 (32.7%) All healthcare personnel, mostly doctors with no comorbidities Nonsignificant

aC, control; P, placebo; I, intervention; HCQ, hydroxychloroquine.

Study Patient status Infection status at baseline Follow-up period Intervention (exposure timing; dosage) Intervention timing Control Number of infectionsa Number of hospitalizationsa Number of deaths Hazard ratio (or equivalent measure)
Abella et al.10 Asymptomatic No known infection 8 weeks Pre-exposure; 600 mg daily Presymptomatic, pre-diagnosed Placebo P: 4, HCQ: 4 0 0 N/A
Barnabas et al.11 Asymptomatic No known infection 14 days Pre-exposure; 400 mg daily for 3 days, followed by 200 mg daily for 11 days Presymptomatic, pre-diagnosis Placebo P: 48, HCQ: 58 P: 1, HCQ: 1 0 Infection: adjusted hazard ratio 1.16 [95% CI 0.77, 1.73; P > 0.20]
Rajasingham et al.12 Asymptomatic No exposure 12 weeks Pre-exposure; 400 mg once or twice weekly, for 12 weeks Presymptomatic, pre-diagnosis Placebo P: 6 once: 4 twice: 7 P: 9; HCQ once: 3; HCQ twice: 8 0 Infection: Once weekly: 0.65 [95% CI 0.18, 2.32], twice weekly: 1.18 [95% CI 0.40, 3.51]
Rojas-Serrano et al.13 Asymptomatic No known infection 60 days Pre-exposure; 200 mg daily for 60 days Presymptomatic, pre-diagnosis Placebo P: 6, I: 1 0 0 Infection: 0.18 [95% CI: 0.02, 1.48; P = 0.09]
Syed et al.14 Asymptomatic No known infection 12 weeks Pre-exposure; group 1: 400 mg twice on day 1 followed by 400 mg weekly for 12 weeks, group 2: 400 mg once every 3 weeks, group 3: 200 mg weekly every 3 weeks Presymptomatic, pre-diagnosis Placebo P: 7, Group 1: 15, Group 2: 19, Group 3: 8 0 0 N/A

aC, control; P, placebo; I, intervention; HCQ, hydroxychloroquine.

Table S2. Post-exposure prophylaxis of COVID-19 group studies and their characteristics

Study Journal Location Date of Publication Agea(years) Number of participants (in each group)a Gender breakdown of participants (by n [%] female)a Key characteristics noted Key comorbiditiesa
Mitja et al.15 The New England Journal of Medicine Catalonia, Spain February 4, 2021 Mean, C: 48.7; I: 48.6 2314 (C: 1198; HCQ: 1116) C: 875 (73%), I: 812 (72.8%) Majority household contact followed by nursing care worker, majority routine use of mask Cardiovascular disease: C: 14.9%, I: 11.6%; respiratory disease: C: 3.9%, I: 5.7%; metabolic disease: C: 7.8%, I: 8.9%; nervous system disease: C: 14.2%, I: 15.2%
Boulware et al.16 The New England Journal of Medicine USA, Canada (Quebec, Manitoba, and Alberta) August 6, 2020 Median, P: 40; I: 41 821 (P: 407; HCQ: 414) P: 206 (50.6%), I: 218 (52.7%) Majority healthcare workers who experienced high-risk exposure while no PPE worn, mostly Caucasian Hypertension, P: 11.8%, I: 12.3%; asthma, P: 7.6%, I: 7.5%

aC, control; P, placebo; I, intervention; HCQ, hydroxychloroquine; PPE, personal protective equipment.

Study Patient status Infection status at baseline Follow-up period Intervention (exposure timing; dosage) Intervention timing Control Number of infectionsa Number of hospitalizationsa Number of deathsa Hazard ratio (or equivalent measure)
Mitja et al.15 Asymptomatic Asymptomatic for 2 weeks before enrollment 14 days Post-exposure; HCQ 800 mg once, followed by 400 mg daily for 6 days Presymptomatic, pre-diagnosis Nothing C: 74; HCQ: 64 C: 12; HCQ: 11 C: 8; HCQ: 5 Infection: Risk ratio 0.89 [95% CI 0.54, 1.46]
Boulware et al.16 Asymptomatic Asymptomatic 4 days after exposure 4–6 weeks Post-exposure; 800 mg once, followed by 600 mg in 6 to 8 h, then 600 mg daily for 4 more days Presymptomatic, pre-diagnosis Placebo P: 58; HCQ: 49 P: 1; HCQ: 1 0 N/A

aC, control; P, placebo; I, intervention; HCQ, hydroxychloroquine.

Table S3. Post-diagnosis treatment of COVID-19 group studies and their characteristics

Study Journal Location Date of Publication Agea(years) Number of participants (in each group)a Gender breakdown of participants (by n [%] female)a Key characteristics noted Key comorbiditiesa
Mitja et al.17 Clinical Infectious Diseases Catalonia, Spain July 16, 2020 Median, C: 41.7; I: 41.6 293 (C: 157; HCQ: 136) C: 104 (65.6%), I: 98 (72.1%) Majority healthcare workers, majority had a coexisting disease Cardiovascular disease: C: 9.6%, I: 14.7%; respiratory disease: C: 6.4%, I: 5.1%; metabolic disease: C: 9.0%, I: 6.6%; nervous system disease: C: 13.4%, I: 14.0%
Amaravadi et al.18 medRxiv (preprint) Pennsylvania, USA February 26, 2021 Median, P: 49, I: 56 34 (P: 17, HCQ: 17) P: 9 (53%), I: 12 (71%) All ≥40 years old, majority Black Hypertension: P: 18%, I: 24%; diabetes (P: 0%, I: 18%); asthma (P: 6%, I: 18%)
Schwartz et al.19 CMAJ Open Alberta, Canada June 18, 2021 Mean, P: 46.9, I: 46.7 148 (P: 37, HCQ: 111) P: 20 (54.1%), I: 46 (41.4%) Community-dwelling individuals, majority Asian, all had one risk factor of severe disease Hypertension: P: 32.4%, I: 26.1%; diabetes: P: 29.7%, I: 16.2%; asthma: P: 21.6%, I: 10.8%; smoker: P: 13.5%, I: 14.4%
Skipper et al.5 Annals of Internal Medicine USA, Canada (Quebec, Manitoba, and Alberta) July 16, 2020 Mean, P: 39; I: 41 491 (P: 247; HCQ: 244) P: 135 (54.5%), I: 142 (58%) Majority experienced high-risk exposure, healthcare workers None

aC, control; P, placebo; I, intervention; HCQ, hydroxychloroquine.

Study Patient status Infection status at baseline Follow-up period Intervention (exposure timing; dosage) Intervention timing Control Number of infections Number of hospitalizationsa Number of deathsa Hazard ratio (or equivalent measure)
Mitja et al.17 Symptomatic 5 days or less of symptoms 28 days Post-exposure; 800 mg once, followed by 400 mg daily for 6 days Post-symptomatic onset, post-diagnosis Nothing N/A C: 12; HCQ: 8 0 Hospitalization: risk ratio 0.75 [95% CI 0.32, 1.77]
Amaravadi et al.18 Symptomatic ≤4 days since first COVID-19 symptom and testing 19 days Post-exposure; 400 mg twice daily up to 14 days Post-symptomatic onset, post-diagnosis Placebo N/A P: 0, HCQ: 1 0 N/A
Schwartz et al.19 Symptomatic Symptomatic within previous 12 days 30 days Post-exposure; 400 mg twice on day 1, followed by 200 mg twice daily for 4 days Post-symptomatic onset, post-diagnosis Placebo N/A P: 0, HCQ: 4 0 N/A
Skipper et al.5 Symptomatic 4 or fewer days of symptoms 14 days Post-exposure; 800 mg once, followed by 600 mg within 6 to 8 h, then 600 mg daily for 4 more days Post-symptomatic onset, post-diagnosis Placebo N/A P: 10; HCQ: 4 P: 1; HCQ: 1 N/A

aC, control; P, placebo; I, intervention; HCQ, hydroxychloroquine.

Table S4. Cochrane Risk of Bias (RoB) assessment

Table S5. GRADE evaluation of studies

Outcome Factors that reduce quality of evidence Factors that increase quality of evidence
Risk of bias Inconsistency Imprecision Indirectness Publication bias Magnitude of effect Confounding effect Dose-response gradient Overall rating
Infection Serious (–1) Not serious (0) Not serious (0) Not serious (0) Undetected (0) Do not raise (0) Raise up (+1) Do not raise (0) High
Hospitalization Not serious (0) Not serious (0) Serious (–1) Not serious (0) Undetected (0) Do not raise (0) Raise up (+1) Do not raise (0) High
Death Very serious (–2) Not serious (0) Serious (–1) Not serious (0) Undetected (0) Do not raise (0) Raise up (+1) Do not raise up (0) Low

Figure S1. PRISMA flowchart.

Figure S2. Funnel plots with 95% confidence limits evaluating publication bias.

Figure S3A. Sensitivity analysis of infection in HCQ group vs. control group for post-exposure group.

Figure S3B. Sensitivity analysis of hospitalization in HCQ group vs. control group for post-exposure group.

Figure S3C. Sensitivity analysis of death in HCQ group vs. control group for post-exposure group.

Figure S3D. Sensitivity analysis of infection in HCQ group vs. control group in all groups combined.

Figure S3E. Sensitivity analysis of hospitalization in HCQ group vs. control group in all groups combined.

Figure S3F. Sensitivity analysis of death in HCQ group vs. control group in all groups combined.

Figure S3G. Sensitivity analysis of infection, hospitalization, and death in all included studies.

Figure S4. Search keywords and search strings.