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BackgroundResults from observational studies and randomized clinical trials (RCTs) have led to the consensus that hydroxychloroquine (HCQ) and chloroquine (CQ) are not effective for COVID-19 prevention or treatment. Pooling individual participant data, including unanalyzed data from trials terminated early, enables more detailed investigation of the efficacy and safety of HCQ/CQ among subgroups of hospitalized patients. MethodsWe searched ClinicalTrials.gov in May and June 2020 for US-based RCTs evaluating HCQ/CQ in hospitalized COVID-19 patients in which the outcomes defined in this study were recorded or could be extrapolated. The primary outcome was a 7-point ordinal scale measured between day 28 and 35 post enrollment; comparisons used proportional odds ratios. Harmonized de-identified data were collected via a common template spreadsheet sent to each principal investigator. The data were analyzed by fitting a prespecified Bayesian ordinal regression model and standardizing the resulting predictions. ResultsEight of 19 trials met eligibility criteria and agreed to participate. Patient-level data were available from 770 participants (412 HCQ/CQ vs 358 control). Baseline characteristics were similar between groups. We did not find evidence of a difference in COVID-19 ordinal scores between days 28 and 35 post-enrollment in the pooled patient population (odds ratio, 0.97; 95% credible interval, 0.76-1.24; higher favors HCQ/CQ), and found no convincing evidence of meaningful treatment effect heterogeneity among prespecified subgroups. Adverse event and serious adverse event rates were numerically higher with HCQ/CQ vs control (0.39 vs 0.29 and 0.13 vs 0.09 per patient, respectively). ConclusionsThe findings of this individual participant data meta-analysis reinforce those of individual RCTs that HCQ/CQ is not efficacious for treatment of COVID-19 in hospitalized patients.
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Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aimed to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We conducted a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality was extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses included patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine was 1.11 (95% CI: 1.02, 1.20; I2=0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I2=0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine was associated with increased mortality in COVID-19 patients, and there was no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.
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BackgroundUnderstanding the epidemiology of SARS-CoV-2 is essential for public health control efforts. Social, demographic, and political characteristics at the US county level might be associated with the trajectories of SARS-CoV-2 case incidence. ObjectiveTo understand how underlying social, demographic, and political characteristics at the US county level might be associated with the trajectories of SARS-CoV-2 case incidence. DesignRetrospective analysis of the trajectory of reported SARS-CoV-2 case counts at the US county level during June 1, 2020 - June 30,2020 and social, demographic, and political characteristics of the county. SettingUnited States. ParticipantsReported SARS-CoV-2 cases. ExposuresMetropolitan designation, Social Deprivation Index (SDI), 2016 Republican Presidential Candidate Victory. Main Outcomes and MeasuresSARS-CoV-2 case incidence. Results1023/3142 US counties were included in the analysis. 678 (66.3%) had increasing SARS-CoV-2 case counts between June 1 - June 30, 2020. In univariate analysis, counties with increasing case counts had a significantly higher SDI (median 48, IQR 24 - 72) than counties with non-increasing case counts (median 40, IQR 19 - 66; p=0.009). In the multivariable model, metropolitan areas of 250,000 - 1 million population, higher percentage of Black residents and a 10-point or greater Republican victory were independently associated with increasing case counts. LimitationsThe data examines county-level voting patterns and does not account for individual voting behavior, subjecting this work to the potential for ecologic fallacy. ConclusionIncreasing case counts of SARS-CoV-2 in the US are likely driven by a combination of social disadvantage, social networks, and behavioral factors. Addressing social disadvantage and differential belief systems that may correspond with political alignment will be essential for pandemic control.
