Preliminary report from the Together Trial showing mortality RR 0.82 [0.44-1.52] and combined extended ER observation or hospitalization RR 0.91 [0.69-1.19].

The same trial's results for a previous treatment were initially reported as RR 1.0 [0.45-2.21] [ajtmh.org], while the final paper reported something very different — RR 0.76 [0.30-1.88] [jamanetwork.com].

The trial randomization chart does not match the protocol, suggesting major problems and indicating substantial confounding by time. For example, trial week 43, the first week for 3 dose ivermectin, shows ~3x patients assigned to ivermectin vs. placebo [reddit.com]. Treatment efficacy can vary significantly over time, for example due to overall improvement in protocols, changes in the distribution of variants, or changes in public awareness and treatment delays. [Zavascki] show dramatically higher mortality for Gamma vs non-Gamma variants (28 day mortality from symptom onset aHR 4.73 [1.15-19.41]), and the prevalence of the Gamma variant varied dramatically throughout the trial [ourworldindata.org]. This introduces confounding by time, which is common in COVID-19 retrospective studies and has often obscured efficacy (many retrospectives have more patients in the treatment group earlier in time when overall treatment protocols were significantly worse).

According to this analysis [reddit.com], the total number of patients for the ivermectin and placebo groups do not appear to match the totals in the presentation (the numbers for the fluvoxamine arm match) — reaching the number reported for ivermectin would require including some of the patients assigned to single dose ivermectin. Reaching the placebo number requires including placebo patients from the much earlier ivermectin single dose period, and from the early two week period when zero ivermectin patients were assigned. If these earlier participants were accidently included in the control group, this would dramatically change the results in favor of the control group according to the changes in Gamma variant prevalence.

Treatment delay is currently unknown, however the protocol allows very late inclusion and a companion trial reported mostly late treatment. Overall mortality is high for 18+ outpatients. Results may be impacted by late treatment, poor SOC, and may be specific to local variants [Faria, Nonaka, Sabino]. Treatment was administered on an empty stomach, greatly reducing expected tissue concentration [Guzzo] and making the effective dose about 1/5th of current clinical practice. The trial was conducted in Minas Gerais, Brazil which had substantial community use of ivermectin [otempo.com.br], and prior use of ivermectin is not listed in the excluson criteria.

Time from symptom onset to randomization is specified as within 7 days. However the schedule of study activities specifies treatment administration only one day after randomization, suggesting that treatment was delayed an additional day for all patients.

Mid-trial protocol changes appear to increase the probability of enrolling healthy young people. Specifically, the trial has a list of requirements for increased risk including age >50 and obesity. Version 3 of the ClinicalTrials.gov record adds "Fever >38C at baseline", allowing enrollement independent of increased risk.

This trial uses a soft primary outcome, easily subject to bias and event inflation in both arms (e.g., observe >6 hours independent of indication). There is also an unusual inclusion criteria: "patients with expected hospital stays of <= 5 days". This is similar to "patients less likely to need treatment beyond SOC to recover", and would make it very easy to reduce the effect seen. This is not in either of the published protocols.

The trial took place in an area of Brazil where the Gamma variant was prominent. Brazilian clinicians report that this variant is much more virulent, and that significantly higher dosage and/or earlier treatment is required, as may be expected for variants where the peak viral load is significantly higher and/or reached earlier [Faria, Nonaka].

RCTs have a fundamental bias against finding an effect for interventions that are widely available — patients that believe they need treatment are more likely to decline participation and take the intervention [Yeh], i.e. RCTs are more likely to enroll low-risk participants that do not need treatment to recover (this does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable). This trial was run in a community where ivermectin is widely known and used.

Reviewer 1 of the protocol notes that the DSMC is not independent [gatesopenresearch.org]. Prof. Thorlund is Vice President of the contract research organisation (CRO, Cytel), professor at the sponsoring university, and an author of the protocol. Dr. Haggstrom is an employee of the CRO.

Trial design, analysis, and presentation, along with previous public and private statements suggest investigator bias. Design: including very late treatment, additional day before administration, operation in a region with high community use, specifying administration on an empty stomach, limiting treatment to 3 days, using soft inclusion criterion and a soft primary outcome, easily subject to bias. Analysis: authors perform analysis excluding events very shortly after randomization for fluvoxamine but not ivermectin, and report viral load results for fluvoxamine but not ivermectin. Presentation: falsely describing positive but not statistically significant effects as "no effect, what so ever" [Amrhein, odysee.com]. Prior statements: [odysee.com].

For other issues see [twitter.com].

There are two published protocols, both are called "version 1", we refer to them as 1A (3/11/21 [drive.google.com] ) and 1B (8/5/21 [gatesopenresearch.org]. 1B deletes subgroup analysis by treatment delay, and deletes a statement requiring prior approval for amendments. 1B adds the statement: "we hypothesize that younger patients will benefit more than older patients."

The trial is associated with:

MMS Holdings - a company whose mission includes helping pharmaceutical companies get approval and designing scientific studies that help them get approval. One of their clients is Pfizer [mmsholdings.com].

Cytel Inc. - another statistical modelling company that helps pharmaceutical companies get approval - they work very closely with Pfizer [cytel.com].

One of the senior investigators was Dr. Craig Rayner, President of Integrated Drug Development at Certara - another company with a similar mission to MMS Holdings. They state on their website that: "Since 2014, our customers have received over 90% of new drug and biologic approvals by the FDA." One of their clients is Pfizer [certara.com].

A co-principal investigator works for Cytel and the Gates Foundation [empendium.com].

If you are a trial participant please contact us below. For other issues see: [twitter.com (B), twitter.com (C)].