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HCQ study #91 of 280
7/16 Early treatment study
Skipper et al., Annals of Internal Medicine, doi:10.7326/M20-4207 (Peer Reviewed)
Hydroxychloroquine in Nonhospitalized Adults With Early COVID-19: A Randomized Trial
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~70 to 140 hour (inc. shipping) delayed outpatient treatment with HCQ reduced combined hospitalization/death by 50%, p=0.29 (5 HCQ cases, 10 control cases), and reduced hospitalization by 60%, p=0.17. There was one hospitalized control death and one non-hospitalized HCQ death. It is unclear why there was a non-hospitalized death, external factors such as lack of standard care may be involved. Excluding that case results in one control death and zero HCQ deaths (not statistically significant but noted as reducing mortality is the most important outcome). Details for the hospitalizations and deaths such as medication adherence and treatment delay may be informative but are not provided.
The paper states the end point was changed from hospitalization/death to symptom severity because they would have required 6,000 participants. However, if the observed trend continued, they would hit 95% significance on the reduction in hospitalization at ~725 patients, and 95% on the reduction in combined hospitalization/death at ~1,145 patients, which is a lot less than 6,000, and also less than the original plan of 1,242 patients. We hope the trial can be continued for statistical significance.
Treatment is relatively late, ~70 to 140 hours after symptoms, including the shipping delay. The paper does not mention the shipping delay but partial details are provided in the study protocol. They are not clear but indicate no shipping on the weekends and a possible 12pm cutoff for same day dispensing and mailing. Assuming that enrollments were evenly distributed between 6am and 12am each day, we get an average of ~46 hours shipping delay. We have asked for shipping details and will update with more accurate values when available. In any case the treatment delay is quite long and there is no overlap with the more typical delays used such as 0 - 36 hours for oseltamivir.
The paper compares 0 - 36 hour delayed treatment with oseltamivir (influenza) and ~70 to 140 hour delayed treatment with HCQ (COVID-19), noting that oseltamivir seemed more effective. However, a more comparable study is McLean (2015) who showed that 48 - 119 hour delayed treatment with oseltamivir has no effect. This suggests that HCQ is more effective than oseltamivir, and that HCQ may still have significant effect for some amount of delay beyond the delay where oseltamivir is effective.
6 people were included that enrolled with >4d symptoms, although they do not match the study inclusion criteria. This reduces observed effectiveness. The paper says 56% (236) were enrolled within 1 day of symptoms, but results show only 40% for "<1d", 56% is possibly for <48hrs, we have asked for clarification.
Patients in this study are relatively young and most of them recover without assistance. This reduces the room for a treatment to make improvements. The maximum improvement of an effective treatment would be expected before all patients approach recovery, as shown in the figure below. Authors focus on the end result where most have recovered, but it is more informative to examine the curve and the point of maximum effectiveness. Authors did not collect data for every day but they do have interim results for days 3, 5, 10. The results are consistent with an effective treatment and show a statistically significant improvement, p = 0.05, at day 10 (other unreported days might show increased effectiveness).
Results also show a larger treatment effect for those >50, not statistically significant due to the small sample, but noted as COVID-19 risk dramatically increases with age. The effect may be more visible here because younger patients may on average have more mild cases with less room for improvement. In general patients in this study have relatively mild symptoms on average, limiting the chance to observe improvement.
The study relies on Internet surveys. Known fake surveys were submitted to the similar PEP trial and there could be an unknown number of undetected fake surveys in both trials. The study shows a high incidence of side effects in the placebo arm, which could be in part due to fake entries [1].
The granularity change in the histograms of Figure S4 raise concerns [2]. Data on increasing severity, less affected by the lower bound where everyone has recovered, also supports effectiveness [3].
Research shows the placebo used in the US may be protective for COVID-19 [4] so the true effectiveness of HCQ could be higher than observed. Also see [5].
Treatment delay reporting has changed from the companion PEP trial which reported results for enrollment delays 1, 2, 3, and 4 separately (and from which we can confirm a statistically significant delay-response relationship), while this trial combines 1-2 and 3-4, and adds <1. Since the two trials share reporting (some patients were moved between trials) it's not clear how the new category was added.
RCT of 423 patients with Internet surveys. Medication adherence was only 77% so the true effect of treatment is likely higher. Analysis of primarily low risk patients, authors note the results are not generalizable to the COVID high-risk population. We will update when hearing back on questions asked.
In summary, we believe the results of this study are positive for HCQ being an effective treatment, however we have classified this study as inconclusive for now pending feedback and further analysis.
Also see: [6] and [7] regarding flaws in this study.

Skipper et al., 7/16/2020, Randomized Controlled Trial, USA, North America, peer-reviewed, 24 authors, dosage 800mg once, followed by 600mg in 6 to 8 hours, then 600mg daily for 4 more days.
risk of hospitalization, 51.7% lower, RR 0.48, p = 0.19, treatment 5 of 201 (2.5%), control 10 of 194 (5.2%).
risk of no recovery at day 14, 20.0% lower, RR 0.80, p = 0.21.

Effect extraction follows pre-specified rules prioritizing more serious outcomes. For an individual study the most serious outcome may have a smaller number of events and lower statistical signficance, however this provides the strongest evidence for the most serious outcomes when combining the results of many trials.
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