Why Aren’t Hydroxychloroquine and Oleandrin Used for COVID?

Frederick L. Coolidge and Dhwani P. Sadaphal

In the last year, hundreds of medical doctors and some world leaders recommended hydroxychloroquine to prevent and treat the COVID-19 virus. Also, within the past year, hundreds of medical doctors recommended Oleandrin to treat COVID-19 patients. Hydroxychloroquine was a well-established antimalarial drug and is used to treat lupus erythematosus and rheumatoid arthritis. Oleandrin is a compound found in Nerium oleander, a species of poisonous plants found around the world in tropical zones. So, why haven’t both drugs been prescribed to prevent and/or treat COVID-19? It seems that the crux of the problem is understanding how medical opinion differs from medical research and the understanding of what constitutes a randomized trial.

Recently, we heard an anecdotal report of a medical doctor who recommended taking Vitamin C and zinc before receiving a COVID-19 vaccine to minimize any side effects. This, of course, qualifies as a medical opinion. It is not, however, medical research. It may be an example of a false but benign hypothesis, that is, vitamin C and zinc are not harmful, indeed they may be beneficial when ingested in appropriate amounts. However, there is no medical research that demonstrates their benefits for curbing the side effects of a vaccine.

So, what constitutes a randomized trial, which is the essence of medical research at determining whether a drug really works or does not really work? The gold standard for this determination actually has a really lousy name—it is sometimes called the “scientific method,” which is way too vague, or the “two-group design,” which is also vague. However, the phrase “a randomized trial” leaves people wondering also. At the start of a randomized trial in a classic two-group design, scientists theoretically begin with a null hypothesis which means, in the case of determining whether a drug works or not, they believe that the drug does not work any better than pure chance. In their hearts, they often believe that an alternative hypothesis is true, that is, the drug works as they hope it would—it either prevents a disease or treats the disease effectively. The word “null” comes from mathematics, and it means “a set without any members.” It is also called “the empty set.”

Why would scientists begin a study where their starting position is that they do not believe a drug works or they believe it is actually ineffective? The reason is that scientists must be conservative, because their mistakes can be deadly or maybe even worse. For example, the drug thalidomide was widely prescribed in Germany in the early 1960s as a medication to treat anxiety, depression, and insomnia. Within a very short time, it was realized that it was causing terrible birth defects and spontaneous abortions. Apparently, the initial trials were performed on animals but the scientists were unaware of any birth defects or thalidomide did not cause any birth defects in the animals they tested. Thus, this is the reason that scientists must be very careful and conservative, as the repercussions of their erroneous conclusions can be monumental.

So, a randomized trial that tests the efficacy or effectiveness of a new drug begins with a large sample of people or patients. They are often recruited through advertising like social media, flyers, and newspapers, to ascertain that participants volunteer for the study. Sometimes the participants are paid, and sometimes they will simply volunteer nobly for science. Therefore, the resulting sample is called a “sample of convenience.” Next, the participants are randomly assigned to one of two groups, either the experimental group (who will receive the new drug) or the control group. The control group receives a placebo, which is an inert drug or a fake pill/injection that cannot be distinguished from the new drug that the experimental group received. This procedure is necessary to control for the placebo effect—that is, some percentage of the control group will respond positively to the placebo drug or placebo treatment even though they were given an inert drug or sugar pill. Remember that the starting position for the study is the null hypothesis—that is, the drug does not work. The percentage of participants who respond positively to the drug in the experimental group must exceed beyond chance the percentage of participants who respond positively to the drug in the control group. The branch of the mathematics that determines whether the new drug works beyond chance is, of course, called statistics. If, through a statistical analysis, the percentage of positive respondents in the experimental group exceeds the percentage of positive respondents in the control group, then the null hypothesis can be rejected and the alternative hypothesis will be promoted. The findings, in this case, will be labeled “statistically significant.” The word “significant” is not a value judgment, and it does not mean that the finding is important or worthy. The latter might be the case, but in statistics, “significant” means that the null hypothesis has been rejected and that the probability of being wrong is less than or equal to 5%. Thus, it is common to see in published scientific studies the statistical notation p < .05 (or p < .01 or p < .001). If a new drug does not work beyond chance, or does not work to any greater extent than a placebo, then the findings will be called “non-significant” or “not significant,” and the accompanying statistical notation will be p > .05 or p = ns (non-significant).

In summary, both hydroxychloroquine and Oleandrin did not produce significant results in randomized trials (which means numerous two-group experiments). Yes, hundreds and perhaps thousands of medical doctors had the opinion that these drugs worked, and indeed they might have in some patients. However, according to the gold standard of medical research, randomized trials, these drugs did not work better than pure chance.