How to Use the Calculator
- Select Data Format: Choose the type of data you have:
- Percentage Results: Data from the control and experimental groups expressed as percentages.
- Event Data: Data based on the number of events in each group over a specific period (e.g., patient years).
- Input Measurements: Enter the following:
- Control Group (%): The success rate or outcome percentage for the control group.
- Experimental Group (%): The success rate or outcome percentage for the experimental group.
- Outcomes (Optional): If applicable, input specific outcomes such as the number of repeated words.
- View Results: The calculator will compute:
- Absolute Risk Reduction (ARR): The difference between the outcome rates of the control and experimental groups.
- Number Needed to Treat (NNT): The number of patients needed to treat for one to benefit from the intervention.
What’s a Healthy or Unhealthy Range?
- NNT:
- A low NNT (e.g., 2-5) indicates a highly effective treatment, as fewer patients need treatment to achieve a positive outcome.
- A high NNT (e.g., >50) suggests that the intervention may not be significantly impactful or necessary for the majority of patients.
- ARR:
- A higher ARR reflects a more substantial difference in effectiveness between the control and experimental groups.
How to Use the NNT Calculator?
Let's say we'd like to calculate the NNT for the health benefits of dark chocolate. 🍫
We conducted a unique study that lasted for 10 years. Our primary outcome was the incidence of strokes among people who eat small amounts of dark chocolate (experimental group), versus those who don't eat any (control group).
Let's assume both the control and experimental groups were:
- Of a similar size;
- Had the same gender ratios; and
- The patients were of similar age,and ethnicity, and had the same chronic diseases.
1. Results in percentage
The incidence of strokes in the experimental group (chocolate) was 1%, while the rate of strokes in the control group (no chocolate) was 2%. We'll use the following number needed to treat formulas:
ARR = (Control group)−(Experimental group); and
NNT = 1/ARR.
❗ Remember, you need to transform the percentages (2% = 0.02) ❗
ARR = 0.02 - 0.01 = 0.01; and
NNT = 1/ 0.01 = 100.
Our number needed to treat is equal to 100, which means that out of every 100 people who eat chocolate 1 person will benefit and not have a stroke.
Note, that our NNT is positive – it means that our intervention (eating chocolate) will help avoid a particular event, instead of causing it.
2. Results in patient-years
We've observed 200 patients for 2 years. During that period, 2 people in the control group and 1 person in the experimental group had strokes. We can calculate our patient years as patient-years = 200 × 2 = 400. We're gonna use the equations presented below:
R0 = 1 − e-Control group/Patient-years
R1 = 1 − e-Experimental group/Patient-years
ARR = R₀ - R₁
NNT = 1/ARR
R₀ = 0.004988
R₁ = 0.002497
ARR = 0.0024906
NNT = 401.5
This means that for every 401.5 people who eat chocolate, one will avoid a stroke.
Number needed to harm formula
The NNH formula is the same as the number to treat equation:
NNT = 1/ARR
So, what is the difference?
The number needed to harm describes the amount of side effects or any kind of harm.
NNH calculations look for bad things, while NNT focuses on the positive.
An example: ☢️ We're checking how many people have to be exposed to radioactive debris in order to develop a given kind of cancer.
Absolute risk reduction calculation
Absolute risk reduction describes the proportion of patients that benefited from the use of experimental therapy. It's a measure of a patient's gain from a given treatment.
The formulas for ARR are as follows:
ARR = Control event rate - Experimental event rate,
ARR = R₀ - R₁
ARR = 1/NNT.
Why Use This Calculator?
- Evaluate Treatment Effectiveness: Quickly assess the benefits of new or existing treatments.
- Guide Clinical Decisions: Support healthcare providers in determining whether to adopt a specific intervention.
- Research Insights: Provide evidence-based conclusions for clinical trials or population studies.
- Accessible and Accur****te: Simplifies complex statistical calculations with user-friendly inputs and clear outputs.