Response to Magagnoli, MedRxiv, 2020
Matthieu MILLION1,2, Yanis ROUSSEL1,2, Didier RAOULT1,21

IHU-Méditerranée Infection, Marseille, France2

Aix Marseille Univ, IRD, AP-HM, MEPHI, Marseille, France

In the current period, it seems that passion dominates rigorous and balanced scientific analysis andmay lead to scientific misconduct. The article by Magagnoli et al. (Magagnoli, 2020) is an absolutely
spectacular example of this. Indeed, in this work, it is concluded, in the end, that hydroxychloroquine(HCQ) would double the mortality in patients with COVID with a fatality rate of 28% (versus 11% in
the NoHCQ group), which is extraordinarily hard to believe. The analysis of the data shows two major
biases, which show a welling to be convinced before starting the work :The first is that lymphopenia is twice as common in the HCQ groups (25% in the HCQ, 31% in theHCQ+AZ group versus 14% in the no HCQ group, p =.02) and there is an absolute correlation between
lymphopenia (<0.5G/L) and fatality rate, which is well known (Tan, 2020) and confirmed here : 28%deaths, 22% and 11% in the HCQ, HCQ+AZ and No HCQ group, respectively. Lymphopenia is the mostobvious criterion of patient severity (in our cohort, lymphocytes in dead individuals (n=22, mean ±standard deviation, 0.94 ± 0.45), versus in the living (n=2405, 1.79 ± 0.84, p < .0001)). As the authors
acknowledge, the severity of the patients in the different groups was very different, and theiranalysis can only make sense if there is a selection of patients with the same degree of severity, i.e.
the same percentage of lymphopenia.
The second major bias is that in an attempt to provide meaningful data, by eliminating the initial
severity at the time of treatment, two tables are shown: one table where drugs are prescribed before
intubation, and which shows no significant difference in the 3 different groups (9/90 (10%) in theHCQ group, 11/101 (10. 9%) HCQ+AZ, and 15/177 (8.5%) in the group without HCQ, chi-square =0.47, ddl = 2, p = 0.79), and one table, where it is not clear when the drugs were prescribed, where
there are significant differences. These differences are most likely related to the fact that thepatients had been intubated for some before receiving hydroxychloroquine in desperation. It isnotable that this is unreasonable at the time of the cytokine storm, as it is unlikely thathydrochloroquine alone would be able to control patients at this stage of the disease.
Moreover, incomprehensibly, the “untreated” group actually received azithromycin in 30% of cases,
without this group being analyzed in any distinct way. Azithromycin is also a proposed treatment for
COVID (Gautret, 2020) with in vitro efficacy (Andreani, 2020), and to mix it with patients who aresupposedly untreated is something that is closer to scientific fraud than reasonable analysis.
Altogether these 3 voluntary biases are all pushing to the idea of dangerosity of hydroxychloroquinesafest drug as reported on nearly 1 million people (Lane, 2020).
All in all, this is a work that shows that, in this period, it is possible to propose things that do notstand up to any methodological analysis to try to demonstrate that one is right.

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