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In France, pharmacies have been overwhelmed by demands for Plaquenil, leading one pharmacist quoted by Le Monde to exclaim: “Perhaps Raoult is right, but instead of taking the time to carry out a serious study, he has given us two months of theatrics.” Critics argue that not only were there too few subjects in the chloroquine study, but that some of them dropped out during the trial, potentially skewing the results. In addition, Raoult has not released the raw data from the trial, which, remarkably, was not double-blinded. According to Dominique Costagliola, chief epidemiologist at the Pasteur Institute, the trial was so slapdash that “it is impossible to interpret the described result as being attributable to the hydroxychloroquine treatment.”
Auszug aus Molina et al.: No Evidence of Rapid Antiviral Clearance or Clinical Benefit with the Combination of Hydroxychloroquine and Azithromycin in Patients with Severe COVID-19 Infection.
Auszug aus Science Integrity Digest: Thoughts on the Gautret et al. paper about Hydroxychloroquine and Azithromycin treatment of COVID-19 infections
The patients were recruited at different “centers”, but it is not very clear which patient was located in which hospital. The HQ treated patients were all in Marseille, while the controls were located in Marseille or other centers. One can imagine that hospitals might differ in treatment plans, ward layouts, availability of staff, disinfection routines, etc. It is not clear if controls and treated patients were all recruited and treated at the same hospital?
Although the study started with 26 patients in the HQ or HQ+AZ group, data from only 20 treated patients are given, because not all patients completed the 6-day study. The data for these 20 patients looks incredibly nice; especially the patients who were given both medications all recovered very fast.
What happened to the other six treated patients? Why did they drop out of the study? Three of them were transferred to the intensive care unit (presumably because they got sicker) and 1 died. The other two patients were either too nauseous and stopped the medication, or left the hospital (which might be a sign they felt much better).
So 4 of the 26 treated patients were actually not recovering at all. It seems a bit strange to leave these 4 patients who got worse or who died out of the study, just on the basis that they stopped taking the medication (which is pretty difficult once the patient is dead). As several people wrote sarcastically on Twitter: My results always look amazing if I leave out the patients who died, or the experiments that did not work.
Auszug aus einem post-publication review von Frits Rosendaal
The index group and control group were drawn from different centres. The information that is given about characteristics of index group and control group is minimal, and still major differences are evident from all three variables shown (age, sex, presence of symptoms). The authors have performed statistical tests on these baseline characteristics, which is inappropriate. In the text they emphasise the absence of statistically significant differences between groups, implying that absence of statistical significance proves equality, which shows a lack of understanding of basic statistics.
It is remarkable that in a randomised trial, when only chance may have introduced differences between groups, authors go out of their way to present a long list of baseline characteristics to lend credibility to the fairness of comparing outcome occurrence between groups, where here, in a non-randomised comparison of patients from different centres who clearly do differ, authors have not made the slightest effort to present such baseline characteristics. The reviewer can only come to the conclusion that the comparison with the control group is meaningless.
It is reported that 42 patients met the eligibility criteria, and of these 16 were in the control group, and 26 in the treated group. Of these 26, six were excluded (and incorrectly labelled as lost to follow-up): three were transferred to the ICU, one died, and two terminated treatment or were discharged. Firstly, it is noteworthy that 4/26 treated patients deteriorated and 0/16 control patients, which emphasises that the groups were different. More importantly, excluding patients who deteriorated from the analyses introduces severe selection bias, since it selectively excludes people who did not do well (as an extreme example: if 25/26 treated patients had died, and one had virus clearance at day 6, would a claim of 100% clearance be valid?).
Auszug aus NDR: Drosten kritisiert Chloroquin-Studie:
Auszug aus Toumi & Aballea: Commentary on “Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open label non-randomized clinical trial” by Gautret et al.
Auszug aus: Expressis-Verbis: Professor Didier Raoult, Sinnbild eines Widerstands französischer Prägung
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