by Ivan Iriarte MD, Simon Phoenix PhD
The recent controversy about vaccines approved for emergency use against COVID-19 has elicited much discussion regarding Relative Risk Reduction (RRR) and Absolute Risk Reduction (ARR). In broad terms, the ARR compares the overall outcomes of one event versus another; how much is the overall probability of an outcome reduced or increased? The RRR ignores overall improvement—it just compares the benefit, no matter how small, of one event versus another.
Relative to what?
Although we’re focusing on risk here, it’s worth noting the use (and misuse) of relative and absolute measures applies to many medical and scientific results. We must be careful not to rely purely on a relative measure, particularly if this relative measure is used in a headline-grabbing way. Suppose, for example, we have two cancer drugs, A and B. We are told that the tumour size reduction achieved by drug B was 100% better than that achieved by drug A. Drug B sounds very effective, doesn’t it? However, let’s suppose that in absolute terms drug A reduces the size of the tumour by 0.1% which would mean that drug B reduces the tumour by 0.2%. Neither drug could be said to be very effective in overall or absolute terms, but drug B is certainly more effective than drug A in relative terms.
Should you wear a rubber suit?
It’s often helpful to consider extreme examples when understanding technical ideas. Let’s imagine the invention of a rubberized, hooded suit that is designed to keep the wearer safe against lightning. It is found that the suit cuts lightning deaths so that for every 100 deaths by lightning in non-suit wearers there is only one death in suit wearers. This is an example of a high relative risk reduction (RRR). The absolute risk reduction (ARR) will be very small, however, because lightning strikes on people are very rare. In other words, wearing the suit changes an extremely small risk into an even smaller risk.
The real question is whether it is useful for everyone to wear rubberized suits to protect themselves from lightning? One might expect that most of us would probably answer “no”, even though the suits are very effective at preventing death from lightning. That assumes however no coercion, propaganda, or irrational fear influences the decision – a poor assumption in the era of COVID. Still, there may be occupations, such as communication tower maintenance, where wearing the suit would be sensible.
Thus, the ARR is an important consideration when trying to answer the question of whether something is worth doing. We might even argue that the ARR is a vital consideration, particularly in issues of societal impact.
In addition to understanding the definitions and meanings of ARR and RRR, it is important to understand how they should and should not be used. Although these concepts have acquired notoriety in the context of the COVID-19 immunizations, they have been used for decades as standard indicators to measure the efficacy of any preventive intervention.
For example, they are used to screen for the early detection of prostate cancer to help prevent death. Consequently, studies have been designed to compare the risk of death in individuals who receive screening compared to those who do not.
Does a randomized controlled trial always produce useful results?
These kinds of studies are usually randomized controlled trials (RCTs), generally considered the gold standard in validating the effect of any medical intervention. With a RCT, the investigators are able to avoid many of the limitations and biases that are likely to occur with other research methods. However, results from a RCT are not problem-free and should be interpreted with caution. Here once again the implications of RRR and ARR must be understood.
Typically, in a RCT, investigators will select subjects with specific criteria, and randomly assign them to one of two groups, the intervention group and the control or comparison group. Usually, the comparison group receives a placebo, which is an inert substance with no biological effect such as saline solution or sugar pill, and the intervention group receives the intervention being studied. Both the subjects and the investigators are blinded from knowing who is receiving the real intervention, eliminating a potential bias in the observations and reporting of data.