A screening test for tuberculosis has a sensitivity of 95% and a specificity of 90%. What is the correct interpretation of sensitivity in this context?

Question

Accepted Answer

A. The probability that a person with tuberculosis will test positive. ## Definition of Sensitivity

**Key Point:** Sensitivity is the ability of a test to correctly identify those WITH the disease. It answers the question: "If someone has the disease, what is the probability the test will be positive?"

### Formula

$$	ext{Sensitivity} = \frac{TP}{TP + FN}$$

Where:
- TP = True Positives (diseased individuals who test positive)
- FN = False Negatives (diseased individuals who test negative)

### Clinical Interpretation

A sensitivity of 95% means that if 100 people with tuberculosis are tested, 95 will test positive and 5 will be missed (false negatives).

**High-Yield:** Sensitivity is a **disease-centric** metric — it focuses on the diseased population and the test's ability to catch them. A test with high sensitivity is good for **ruling out disease** (high sensitivity = low false negative rate = safe screening test).

### Mnemonic

**SNOUT** — **S**ensitivity rules **OUT** disease. If sensitivity is high and the test is negative, you can confidently exclude the disease.

### Comparison with Other Metrics

| Metric | Formula | Interpretation | Population Focus |
|--------|---------|-----------------|------------------|
| **Sensitivity** | TP / (TP + FN) | Probability test is **+** given disease is present | **Diseased** |
| **Specificity** | TN / (TN + FP) | Probability test is **−** given disease is absent | **Non-diseased** |
| **PPV** | TP / (TP + FP) | Probability disease is present given test is **+** | **Test result** |
| **NPV** | TN / (TN + FN) | Probability disease is absent given test is **−** | **Test result** |

**Clinical Pearl:** In screening programs for serious but treatable diseases (e.g., TB, cancer), high sensitivity is prioritized to avoid missing cases, even if specificity is lower (leading to more false positives that can be confirmed with a second test).

Answer

B. The probability that a person with a negative test does not have tuberculosis

Answer

C. The probability that a person with a positive test actually has tuberculosis

Answer

D. The probability that a person without tuberculosis will test negative

Metric	Formula	Interpretation	Population Focus
Sensitivity	TP / (TP + FN)	Probability test is + given disease is present	Diseased
Specificity	TN / (TN + FP)	Probability test is − given disease is absent	Non-diseased
PPV	TP / (TP + FP)	Probability disease is present given test is +	Test result
NPV	TN / (TN + FN)	Probability disease is absent given test is −	Test result

A screening test for tuberculosis has a sensitivity of 95% and a specificity of 90%. What is the correct interpretation of sensitivity in this context?

Explanation

Definition of Sensitivity

Formula

Clinical Interpretation

Mnemonic

Comparison with Other Metrics

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