EDITORIAL : The debate between the pro-hydroxychloroquine and those who are against it should not turn into a quarrel of belfast. The social networks are full of messages to inappropriate or even hateful or even defamatory between the two ” clans “. The results of the studies are auscultated in the opposite manner by each of the two groups. The debate is highly politicized on the boards tv, which leaves all too often doctors not having to treat patients or who have ties of interest with the pharmaceutical companies, gives a poor vision of medicine and science.
The sponsor of the controlled clinical studies would make some kind of “polls hyper-sophisticated” where we would, in fine, through a metric preset if there is a positive effect to treatment. Further, it would call for a mathematical treatment, to measure the statistical efficiency of the metric. Then this is not the effectiveness of the treatment as one measure, but the” effectiveness ” statistics of the measurement ! And this is perhaps where the perception gap lies.
On one side, the ” empiricists “, “practitioners” of observational medicine (medicine based on the facts), to evaluate the effectiveness of a treatment on each patient and, following successive observations, try to draw a protocol while keeping in mind that each patient is unique. With the advent of the controlled trials, patients are uniformly reduced to a collection of 2 dozen of clinicopathological features and cannot be distinguished from each other only by their number of inclusion. As if to compensate for this dehumanization, we should recall that medical research says it is now moving towards individualised treatment (see stem cell research) so that, from time immemorial, physicians have practiced an adaptation of individualised treatments to patients. On the other side, the supporters of the clinical trial (with all its sophistication : a randomized, double-blind, controlled…) test a or treatments and determine if there is a significant difference between them in performing statistical tests.
However, statistical tools are all too often poorly used. In most trials, one tries to measure the power ” p ” of a result through a statistical test. But this famous “p” is primarily a function of the initial assumptions.
To explain this, let’s take a simple example : in your car, to compensate for the loss of speed caused by the slope in a climb, you press the accelerator. You hold therefore account of external elements, such as slope and friction. The hypothesis commonly accepted is that it must accelerate in a climb to keep its speed constant. This would not come to the idea of the person to lift the foot off the accelerator to keep the same speed in a climb. We want to say that the evidence imposes on the action on the accelerator pedal to correct the loss of speed.
In principle, a clinical trial is the result of several empirical observations that a treatment has an effect on a disease. The question is whether this treatment is more effective than the drugs already commonly used. For his part, the doctor prescribes a drug because he believes, according to the knowledge of the time of the medicine, that this treatment will heal. The assumption by the doctor is that the treatment has an effect greater than no treatment (placebo effect) and not the reverse.
In clinical trials, the statistical tests used are often tests bilateral because the anticipated effects of new treatments are often marginal. When a drug works dramatically, there is no need to test. As the saying in the Pr. Raoult, the essay, the most significant is the or a single patient is cured of a certain disease just as certain. This is what happened when Pasteur saved the little Joseph Meister from rabies. N=1 and the demonstration was made until the certainty of the death of the boy was a highlight. If the little Meister was dead, then he would have had to consider testing on other patients, with less certainty as to the beneficial outcome of the vaccine. Not to mention this example, the Pr. Raoult said, with irony scarcely concealed this truth in his parliamentary hearing, eliciting criticism on the part of those who had lost sight of this reality.
To test for an effect defined a priori as greater than (or less if applicable), a statistical test unilateral just.
This would not come to the idea to a physician to test a drug with a known adverse effect. Well too often in clinical trials, such as hydroxychloroquine, molecule antiviral proven, physicians are the assumption and use a two-tailed test. They make the mistake of using tests that are somehow “too powerful” with the default associated with being too strict in the decision.
For a long time, the debate between macro economists and micro economists exist. The recent times give the feeling that the debate is between proponents of a medicine individual and the medicine of the greatest number, where the interest of the patient as an individual disappears in favor of statistics that it is easy to say everything and its opposite. The myth of the single treatment such as a vaccine has never been as intense as medical research states formally move towards personalised treatments. For a long time, the doctors prescribe through an “ordinance” after a personalised diagnosis.
How many times has there been observations deduced from laboratory tests not checked on the man in real-life situations ? How many economic theories observed in population-based samples have not found their place on a large scale ? The holy Grail of medicine would be to find the single-molecule for each disease. But we live in a world that is increasingly individualistic. Whether it is Nike or Peugeot, one can customize his shoe or his vehicle, thus generating multiple combinations to be satisfactory. So is it reasonable to want to eliminate all of the treatment options viable (such as hydroxychloroquine) in order to keep only one which would be the remdésivir waiting for a vaccine for a disease that is not fully understood ? This would be like asking Nike to make a shoe on a single solution to all the world.
In a pandemic, these pseudo-quarrels of scientists, tainted by conflicts of interest patents, have no place on the boards tv, and could give reason to the two camps, but on the time horizons are different. With thefailure of large controlled trials (Recovery and Discovery), the events come to show that these studies may not be put in place and produce reliable results in the course of the epidemic, giving reason to the’medical approach pragmatic. My grandmother often told me : “When you grow up, you change your mind “. Somehow, for her, I’d probably not have enough experience or perspective to me to see my mistakes.
Author(s): Xavier Azalbert – Director of the publication