Sensitivity
- Measure
Of all the people who have the disease, the share the test correctly calls positive.
What it is
Sensitivity is a test's ability to pick up people who are ill: the proportion of true positives among everyone who has the disease by the reference standard. A highly sensitive test misses few cases (few false negatives), so a negative result helps rule the disease out. It is the property wanted in a screening test.
Formula and reading
- Sensitivity = TP / (TP + FN).
- It ranges from 0 to 1 (or 0 to 100%). 100% = no diseased person is missed.
- Reading: a sensitivity of 92% misses 8 of every 100 people with the disease.
- It is linked to specificity through the cutoff: gaining one usually costs the other.
Worked example
- Data: a rapid test is given to 200 people who have the disease by the reference standard.
- Result: 184 test positive (true positives) and 16 test negative (false negatives).
- Sensitivity = 184 / (184 + 16) = 184 / 200 = 0.92, that is 92%.
- False negative rate = 16 / 200 = 8%.
- Reading: the test detects 92 of every 100 diseased people; a negative makes the disease unlikely, especially when suspicion was low.
Where sensitivity sits in the 2×2 table
| Test result | Diseased | Healthy |
|---|---|---|
| Positive | TP (a) | FP (b) |
| Negative | FN (c) | TN (d) |
| Column measure | Sensitivity = a/(a+c) | Specificity = d/(b+d) |
Markers
- Se
- TP
- FN
How to read it
- Population screening tests aim for high sensitivity so cases are not missed; positives are confirmed afterwards.
- In the emergency department, a negative result on a highly sensitive test can support not pursuing an unlikely cause further.
Common pitfalls
- Calculating sensitivity with all positives in the denominator (that is the positive predictive value).
- Believing a sensitive test confirms the disease when it is positive.
- Measuring sensitivity only in severe cases, which inflates it (spectrum bias).
Test yourself
Think of the answer, then tap the question to see it.
Of 80 diseased people, a test detects 72. What is its sensitivity?
72 / 80 = 0.90, that is 90%.
Why does a negative result on a highly sensitive test help rule out the disease?
Because it gives few false negatives: almost every diseased person tests positive, so a negative makes the disease unlikely.
Which property is prioritised in a screening test?
Sensitivity, so that cases are not missed; positives are then confirmed with a more specific test.
Connections
Educational content on epidemiological and statistical methods; the examples use made-up numbers to teach the calculation. Not a clinical or legal guide: current Colombian rules are in the official sources.
Sources: Sensitivity, Specificity, and Predictive Values: Foundations, Pliabilities, and Pitfalls in Research and Practice (Frontiers in Public Health, 2017); Statistical Guidance on Reporting Results from Studies Evaluating Diagnostic Tests - Guidance for Industry and FDA Staff (U.S. Food and Drug Administration, 2007).
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Representative model, for educational purposes only.