Table Of Contents
What Is Absolute Risk Reduction (ARR)?
Absolute Risk Reduction is the variation in event rates between two interventions. This calculation reveals the difference between the risks involved in an event in a study's control and treated groups. It is otherwise known as the risk difference.
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The concept can be applied to the study of various fields and aids in assessing whether the benefits in a context outweigh the negative points. In other words, ARR reveals the associated risks involved in experiments. It is one of the most useful ways to aid decision-making, and presenting research results facilitates the process.
Key Takeaways
- Absolute risk reduction is the variation in event rates between two interventions. This calculation reveals the difference between the risks involved in an event in the control and treated groups in a study.
- The ARR analyzes the differences between two risks and helps determine the number needed to treat (NNT). It is otherwise known as the risk difference.
- It helps reflect the risk reduction related to the treatment and the underlying risk associated with access to the treatment. ARR is used to evaluate risk reduction along with relative risk reduction.
Absolute Risk Reduction Explained
Absolute risk reduction (ARR) is the value that reveals the difference in the event rates between treatment and control groups. ARR uses statistics as a base for calculation, especially in medical or health-related studies. The calculation takes the difference between an event's risk in a control group and an event's risk in the treated group. It is one of the basic and simple measures used in controlled studies.
Absolute risk is the total chance of a risk happening, and risk is the chance of something bad happening. Furthermore, the risk reduction process is approached through absolute and relative risk reduction. Relative risk reduction (RRR) shows the proportionality of risk changes between the two groups. On the other hand, the ARR analyzes the differences between two risks and helps in knowing the number of treatments needed (NNT).
ARR as a measure is simple and easy to compute. It may be expressed as a percentage (such as 1%), a decimal (such as 0.01), or as a count (such as 10 out of 100), etc. The method of expression makes it easy to interpret, especially for medical issues. It helps reflect the risk reduction related to the treatment and the underlying risk associated with access to treatment. However, a major drawback is that differences in the risk of fixed sizes could be significant when they are close to 0 or 1, as opposed to when they are close to the middle of the range.
Formula
Absolute risk reduction calculations can be done through the following formula:
ARR = EER-CER
Where,
EER is the experimental event rate (treatment group), and CER is the control event rate (control group).
Examples
Let us check the instances to below to understand the concept even better:
Example #1
Let's consider the following values for understanding the concept: If, in a study, the risk of having a disease for those who took medicine A was 0.5 and the risk of developing the disease for those who took medicine B was 0.3, the ARR would be calculated by subtracting both values,
ARR = EER-CER
= 0.5-0.3 = 0.2
Thus, the ARR of developing the disease is 0.2.
Example #2
According to an article, AstraZeneca, a global biopharmaceutical business, defended itself in a legal case concerning vaccine efficacy. The claimants have argued that the company overstated the efficacy of vaccines that it manufactured for COVID-19 was focused more on the relative risk. The absolute risk involved was given less value. Relative risk represents the risk of developing the virus in vaccinated individuals versus those unvaccinated. Absolute risk, on the other hand, represents the actual percentage of those individuals who are likely to develop the disease. The claimants argued that the relative risk could be a more informative method and could be a better choice in case of a low prevalence of the virus.
Absolute Risk Reduction vs Relative Risk Reduction vs Attributable Risk
| Key points | Absolute Risk Reduction | Relative Risk Reduction | Attributable Risk
|
| Concept | ARR is the difference between an event's risk in a control group and an event's risk in the treated group.
| Relative risk reduction (RRR) shows the risk of negative outcomes reduced due to treatment relative to the group that does not have access to treatment.
| Attributable risk (AR) shows how many disease cases among those exposed can be linked to that exposure.
|
Formula
| ARR = EER-CER
| Relative Risk Reduction (RRR) = absolute risk of events in the control group minus the absolute risk of events in the treatment group / Absolute risk of events in the control group.
| AR (in population) = incidence rate (incidence in exposed subjects) incidence rate unexposed.
|
Example
| It helps determine the effectiveness of introducing a new treatment, such as administering a new malarial drug in a group and determining the success rate. | The degree of risk reduction is found through RRR; for example, if the death rate of tumor patients in the old treatment method was 70% and with the new treatment method it was reduced to 50%, the rate of degree of reduction would be 70-50/70 =0.28. This means that the death rate is 20% less in the new method.
| For instance, 70% of individuals who developed brain tumors were exposed to a factor that increased the risk of developing the tumor, whereas 30% of individuals did not.
|
Frequently Asked Questions (FAQs)
Can absolute risk reduction be negative?
How to calculate absolute risk reduction from relative risk?
How to interpret absolute risk reduction?
When to use absolute risk reduction?
