Relative risk trials

In general, it is important to keep in mind that one should always report the time period to which the risk applies. None declared. The results presented in this article have not been published previously in whole or part. Rothman KJ. An Introduction. Google Scholar. Google Preview. Measuring disease occurrence. Kidney Int ; 72 : — When do we need competing risks methods for survival analysis in nephrology?

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Int J Epidemiol ; 2 : — Nephrol Dial Transplant ; 30 : — Risk of end-stage renal disease following live kidney donation. JAMA ; : — Prediction versus aetiology: common pitfalls and how to avoid them. Nephrol Dial Transplant ; 32 Suppl 2 : ii1 — ii5. Influence of method of reporting study results on decision of physicians to prescribe drugs to lower cholesterol concentration.

BMJ ; : — Hochman M , McCormick D. Endpoint selection and relative versus absolute risk reporting in published medication trials. J Gen Intern Med ; 26 : — Ratio measures in leading medical journals: structured review of accessibility of underlying absolute risks. BMJ ; : BMJ ; : c Ann Intern Med ; : — Ann Intern Med ; : W — W PloS One ; 11 : e Oxford University Press is a department of the University of Oxford.

It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account. Sign In. Advanced Search. Search Menu. Article Navigation. Close mobile search navigation Article Navigation. Volume Article Contents Abstract. Relative risk versus absolute risk: one cannot be interpreted without the other. Marlies Noordzij , Marlies Noordzij. Oxford Academic. Merel van Diepen.

Fergus C. Kitty J. Select Format Select format. Permissions Icon Permissions. Abstract For the presentation of risk, both relative and absolute measures can be used.

Outcome of interest. Person time. Incidence rate:. Relative measure of the effect:. Absolute measure of the effect:. Open in new tab. In Figures 1 and 2 , it is illustrated how two completely different scenarios with different background risks can lead to the same relative risk.

We present a hypothetical study including subjects: 60 in the group exposed to an environmental factor and 60 in the unexposed group. At the end of the follow-up period of 2 years the occurrence of the outcome of interest is measured in both groups. In Figure 1 , we see the situation in which the outcome of interest is rare. These risks resulted in a relative risk of 1. In Figure 2 , a similar study is presented that found exactly the same relative risk of 1.

These figures clearly show why reporting only the relative risk gives incomplete information. Open in new tab Download slide.

Google Scholar Crossref. Search ADS. All rights reserved. Suppose, for example, we have two cancer drugs, A and B. 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.

It is found that the suit cuts lightning deaths so that for every 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?

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 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. 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. 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. Figure 1: the basic structure of a RCT in which participants are either given the trial medication or a placebo.

The numbers of people who become ill can be compared in the two groups and a relative risk reduction is estimated. Note that the test group must be split randomly so that each treatment group is truly comparable.

Many studies fail at this basic step because the treatment groups are biased, and not truly equivalent populations. The investigators randomly assigned 21, subjects 16 years and older to receive two doses of the new vaccine, and 21, subjects to receive two doses of placebo.

They followed the subjects for a median of two months after the intervention. It is also important to take into account the trial design itself.

In this case Pfizer designed the trial, and they are highly experienced in setting up trials for success. The trial compared the case numbers in the vaccinated vs control placebo groups where a case of COVID was defined as an individual who experienced symptoms and had a positive test for SARS-CoV-2 infection.

This is arguably a weak endpoint, as incidence of severe disease and death, the very outcomes one would hope the vaccine prevents, were not considered.

Other data was collected, including the incidence of serious side effects. This illustrates why considering the ARR may be helpful. But the issue becomes even more complex to interpret. In addition, the risk of getting the disease in different sectors of the population, and in different geographical locations, may also be different. There is a final important point to consider relative to trial design and reported outcomes.

Whilst it is important to determine whether the vaccines are effective at reducing infection, it is equally important to know whether they improve health outcomes overall — is the benefit sufficient to justify the potential risk? Given that, for the vast majority, COVID is not a serious illness , adverse events arising during the trials should also factor into our decision about overall suitability of the proposed measure.

The logical conclusion is that the RRR and ARR of an intervention in this case a vaccine reported in a RCT should be interpreted carefully when making decisions about the desirability of implementing the intervention in the general population. The decisions to implement interventions in the population should use results of a RCT as valuable information, but should also take into account many factors such as the actual risk of getting COVID in different populations geographical locations, different ages, other medical conditions… , the probability of getting sick with COVID during different seasons, and the probability of adverse events following vaccination among others.

Olifaro, P. COVID vaccine efficacy and effectiveness—the elephant not in the room. Screening and prostate-cancer mortality in a randomized European study. N Engl J Med. Pollack, FP. Et al. Photo by Mat Napo on Unsplash. Some of the posts we share are controversial and we do not necessarily agree with them in the whole extend. Sometimes we agree with the content or part of it but we do not agree with the narration or language. We strongly encourage you to have a critical approach to all the content, do your own research and analysis to build your own opinion.

Skip to content. Straight to the point Enjoying free speech since Your daily dose of anti-propaganda! Posted on by: George Orwell. Erickson Dr. Ioannidis Dr. Judy Mikovits Dr. Shiva Dr. By: Panda Posted on 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?