Absolute risk communication starts with an outcome, a time period and an appropriate baseline risk. A relative reduction alone is not enough. RealRisk can help translate research findings into more understandable quantities, but the clinician still has to establish what was measured and whether the comparison applies to the person in front of them.
Read the measure before touching the calculator
RealRisk, checked on 19 September 2026, is a research-communication tool that accepts relative risks, odds ratios and hazard ratios alongside relevant baseline information. It also links to mathematical explanations through RealRisk Light.
The distinction between those measures matters. A risk ratio compares probabilities over a specified period. An odds ratio compares odds. A hazard ratio concerns event rates over time. They are not interchangeable labels for the same number, and multiplying baseline risk by any reported ratio will not always be valid.
Before entering anything, write one sentence: "This study compared this intervention with this alternative, for this outcome, in this population, over this period." A missing part of that sentence is a reason to return to the paper, not to guess an input.
An original example, with the arithmetic visible
The following numbers are hypothetical teaching data created for this article on 19 September 2026. They do not describe a medicine, an actual trial or an iatroX evaluation.
Suppose a trial reports that an unwanted event occurred in 10 out of 100 people receiving usual care over five years. In the intervention group it occurred in 7 out of 100 over the same period.
The intervention-group risk divided by the comparison-group risk is 7/10, giving a risk ratio of 0.70. The relative reduction is 30%. The absolute difference is 3 percentage points, or 3 fewer events per 100 people over five years.
Those statements describe the same hypothetical result, but they answer different questions. "Thirty per cent lower" describes the proportional change. "Three fewer in every hundred over five years" describes the difference using a common population and time horizon.
Do not describe the absolute reduction as 3% of the original risk. That would mean something different. Percentage points compare two percentages directly.
A second baseline changes the practical meaning
For a separate hypothetical illustration, assume the same risk ratio could validly apply to a group with a five-year baseline risk of 2 in 100. Multiplying 2% by 0.70 gives 1.4%, an absolute difference of 0.6 percentage points. Using a denominator of 1,000 avoids awkward fractions: 20 events without the intervention and 14 with it, or 6 fewer per 1,000.
The phrase "assume the same risk ratio could validly apply" is doing important work. This calculation demonstrates arithmetic, not transportability. A study in one population does not prove that its relative effect holds in another.
The baseline should not be selected because it makes the intervention look impressive. Nor should a personal risk estimate be invented from a vaguely similar study. Where applicability is uncertain, say so and retain that uncertainty in the conversation.
What the conversation might sound like
A fictional patient asks whether "a 30% improvement" means that almost a third of people are helped.
A clearer explanation would be: "In this example, the event happened to about 10 in every 100 people over five years without the intervention, and 7 in every 100 with it. That is about 3 fewer events per 100 people. It does not tell us in advance which individuals would benefit."
Then ask what the patient understood. "Could you tell me how you would describe the difference?" invites an explanation without turning the conversation into a test of intelligence. Correcting the denominator is often more useful than repeating the relative figure more slowly.
The wording should also distinguish an average result from a guarantee. A person may make a reasonable choice that differs from someone else with the same estimated risk because their priorities, treatment burden and tolerance of uncertainty differ.
Put harms on the same page
Now add another explicitly hypothetical result: an adverse effect occurred in 2 per 100 people in the comparison group and 5 per 100 in the intervention group during the same five-year period. That is 3 additional adverse effects per 100 people.
It would be misleading to describe benefit as a relative reduction but harm only as a small percentage, or to switch between denominators without explanation. Use the same population size and period wherever the data support doing so.
Equal numerical differences do not mean equal clinical importance. Preventing one kind of event and causing another are not necessarily equivalent. Explain their nature, severity and reversibility rather than inviting the patient to subtract counts as though all outcomes were interchangeable.
The example deliberately omits a confidence interval because no real study is being reported. In an actual consultation, inspect the study's uncertainty and avoid presenting a calculated point estimate as exact knowledge.
A quick audit before sharing the number
Check that the denominator is people rather than events when that is what the statement implies. Check whether follow-up was comparable and whether the number refers to a composite outcome whose components differ in importance. Establish whether the result is an association or an effect supported by the study design.
Finally, read the sentence without the calculator visible. Does it name the outcome and period? Does it make clear whether the baseline comes from the study or a separate estimate? Could a reader mistake it for a personalised prediction? These are editorial checks, not additional mathematical functions.
Where learning tools help
This comparison is published by iatroX, which has a different role from RealRisk. RealRisk addresses quantitative communication; iatroX can support learning about the underlying concepts and rehearsing an explanation. Neither the arithmetic nor an articulate conversation establishes that a treatment is appropriate for a particular patient.
The Socratic Tutor described by iatroX on 19 September 2026 starts from an attempted question and uses targeted follow-ups. An appropriate learning prompt would ask why an odds ratio cannot automatically be interpreted as a risk ratio, or why the same relative effect can correspond to different absolute differences. The aim is understanding that survives a change of numbers, not memorising this example.
Frequently asked questions
Can I multiply baseline risk by any reported relative measure?
No: risk ratios, odds ratios and hazard ratios require different treatment and assumptions. Identify the measure and use the appropriate method before interpreting the result.
Is absolute risk always an individual patient's risk?
No: it may describe a study population or a modelled group. Personal applicability must be assessed separately and uncertainty explained.
Should I avoid relative risk altogether?
Relative measures can be useful, but they should not be the only explanation when absolute information is available. Present the outcome, baseline, comparison and time horizon together.