On the surface, it looks very promising, doesn’t it? The percentage of patients PCR-positive for SARS-CoV-2 is lower in the hydroxychloroquine-treated group and drops to zero by day 5. Of course, there are no error bars. Why might that be? Let’s go to the source:
“We enrolled 36 out of 42 patients meeting the inclusion criteria in this study that had at least six days of follow-up at the time of the present analysis. A total of 26 patients received hydroxychloroquine and 16 were control patients. Six hydroxychloroquine-treated patients were lost in follow-up during the survey because of early cessation of treatment. Reasons are as follows: three patients were transferred to intensive care unit, including one transferred on day2 post-inclusion who was PCR-positive on day1, one transferred on day3 post-inclusion who was PCR-positive on days1-2 and one transferred on day4 post-inclusion who was PCR- positive on day1 and day3; one patient died on day3 post inclusion and was PCR-negative on day2; one patient decided to leave the hospital on day3 post-inclusion and was PCR-negative on days1-2; finally, one patient stopped the treatment on day3 post-inclusion because of nausea and was PCR-positive on days1-2-3. The results presented here are therefore those of 36 patients (20 hydroxychloroquine-treated patients and 16 control patients). None of the control patients was lost in follow-up.”
So basically, an intent-to-treat analysis was not done, and patients who dropped out in the treatment group because they got sicker were excluded from the analysis. This is not how things are done. These patients were obviously sicker and could easily have had higher viral loads. Leaving them out of the final analysis was not justifiable. What is an intent-to-treat analysis and why is it important? Basically, it is a design in which the results of a trial are analyzed based on the initial treatment to which the patient was assigned, not the final actual treatment administered, requiring that subjects be included even if they do not adhere to the protocol. Intent-to-treat is designed to avoid misleading artifacts in the data that can come about from problems such as unequal dropout between groups (which this study definitely had) or crossover. Of course, intent-to-treat makes the analysis more difficult, because it’s not infrequent that there are missing data points, but there are statistical methods to deal with missing data.